DETAILED ACTION
Claims 1-20 have been examined.
Notice of Pre-AIA or AIA Status
The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
Claim Rejections - 35 U.S.C. § 101
35 U.S.C. § 101 reads as follows:
Whoever invents or discovers any new and useful process, machine, manufacture, or composition of matter, or any new and useful improvement thereof, may obtain a patent therefor, subject to the conditions and requirements of this title.
Claims 1-20 are rejected under 35 U.S.C. § 101.
The claimed invention is directed to “mental steps” and “mathematical concepts” without significantly more.
The claims recite:
• an unlabeled dataset
• a labeled data set
• a plurality of documents
• personally identifiable information (PII)
• determining, based on results received from a PII detection module that applies applying a PII rule stored in the rulebase comprising the plurality of rules for detecting PII to a first portion of a document selected from the unlabeled dataset
• a PII rule
• a rulebase comprising the plurality of rules for detecting PII
• results received from a PII detection module
• a first portion of a document
• a confidence value
• selecting
• second portion of the document
• associating
• a likelihood value
Claim 1
Step 1 inquiry: Does this claim fall within a statutory category?
The preamble of the claim recites “1. A method comprising …” Therefore, it is a “method” (or “process”), which is a statutory category of invention. Therefore, the answer to the inquiry is: “YES”.
Step 2A (Prong One) inquiry:
Are there limitations in Claim 1 that recite abstract ideas?
YES. The following limitations in Claim 1 recite abstract ideas that fall within at least one of the groupings of abstract ideas enumerated in the 2019 PEG. Specifically, they are “mental steps”:
• an unlabeled dataset
• a labeled data set
• a plurality of documents
• personally identifiable information (PII)
• determining, based on results received from a PII detection module that applies applying a PII rule stored in the rulebase comprising the plurality of rules for detecting PII to a first portion of a document selected from the unlabeled dataset
• a PII rule
• a rulebase comprising the plurality of rules for detecting PII
• results received from a PII detection module
• a first portion of a document
• a confidence value
• selecting
• second portion of the document
• associating
• a likelihood value
Step 2A (Prong Two) inquiry:
Are there additional elements or a combination of elements in the claim that apply, rely on, or use the judicial exception in a manner that imposes a meaningful limit on the judicial exception, such that it is more than a drafting effort designed to monopolize the exception?
Applicant’s claims contain the following “additional elements”:
(1) A “training”/“training the content classifier using both the results received from a PII detection module and the second portion of the document”
(2) A content classifier
(3) One or more storage devices
(4) A document
(5) A content management system
(6) Receiving, over a network and at a content management server of a content management system, a plurality of documents from respective network interfaces of a plurality of user devices
(7) limiting, by a limiter component in the content management system, access to the respective documents in the labeled dataset of the content management system by respective user devices of the plurality of user devices based on at least the one or more labels applied to either the individual ones of the respective documents as a whole or to specific portions thereof by the content classifier
(1) A “training”/“training the content classifier using both the results received from a PII detection module and the second portion of the document” is a broad term which is described at a high level. Applicant’s Specification recites:
[0083] The figure depicts one possible implementation of step 204 (FIG. 2) This implementation takes as inputs (1) a labeled dataset 222 and (2) a PII detection rulebase 117, and produces adjusted weights (e.g., weight type1 and weight type2) The error correction module 408 receives two incoming values from two conditionally-independent sets of inputs (e.g., the vector processor value and the rule processor value, as shown), compares them to an error calculation, and then adjusts the weights to reduce the error. The weight adjustment method could be a gradient descent algorithm employing, for example, one or more of several back-propagation methods. In one example implementation of back-propagation, the vector processor 404 is a feed forward deep neural network and adjustments are computed by (1) differentiating the loss function for each input in each layer of the network, and (2) iteratively choosing a weight adjustment that would reduce the error by a precalculated maximum amount and then (3) applying the adjustment. The iterations are repeated until the overall error (e.g., as measured by a loss function) reaches an acceptable value, and/or when no more weight adjustment improvements are possible. In this specific example, the back- propagation algorithm analyzes labels that are generated by the rule based module 117, which can potentially produce noisy label outputs. However, due to the mathematic lemmas that arise as a result of choosing two conditionally independent sets of inputs, back-propagation will converge, resulting in a classifier that is as good (e.g., in terms of precision and recall) as a classifier that had been trained on non-noisy (e.g., perfectly accurate) labels.
Note that, according to the Specification, the claimed “training” could be any one of the many generic gradient descent algorithms. It is unspecified. Note further that the Specification recites:
[00102] In some embodiments, hard-wired circuitry may be used in place of or in combination with software instructions to implement aspects of the disclosure. Thus, embodiments of the disclosure are not limited to any specific combination of hardware circuitry and/or software. In embodiments, the term "logic" shall mean any combination of software or hardware that is used to implement all or part of the disclosure.
This “training”/“training the content classifier using both the results received from a PII detection module and the second portion of the document” limitation does not integrate the additional element into a practical application and represents “insignificant extra-solution activity”. (See, M.P.E.P. § 2106.05(I)(A))
(2) A “content classifier” is a broad term which is described at a high level. Applicant’s Specification recites:
[0083] The figure depicts one possible implementation of step 204 (FIG. 2) This implementation takes as inputs (1) a labeled dataset 222 and (2) a PII detection rulebase 117, and produces adjusted weights (e.g., weight type1 and weight type2) The error correction module 408 receives two incoming values from two conditionally-independent sets of inputs (e.g., the vector processor value and the rule processor value, as shown), compares them to an error calculation, and then adjusts the weights to reduce the error. The weight adjustment method could be a gradient descent algorithm employing, for example, one or more of several back-propagation methods. In one example implementation of back-propagation, the vector processor 404 is a feed forward deep neural network and adjustments are computed by (1) differentiating the loss function for each input in each layer of the network, and (2) iteratively choosing a weight adjustment that would reduce the error by a precalculated maximum amount and then (3) applying the adjustment. The iterations are repeated until the overall error (e.g., as measured by a loss function) reaches an acceptable value, and/or when no more weight adjustment improvements are possible. In this specific example, the back- propagation algorithm analyzes labels that are generated by the rule based module 117, which can potentially produce noisy label outputs. However, due to the mathematic lemmas that arise as a result of choosing two conditionally independent sets of inputs, back-propagation will converge, resulting in a classifier that is as good (e.g., in terms of precision and recall) as a classifier that had been trained on non-noisy (e.g., perfectly accurate) labels.
Note that, according to the Specification, the claimed “content classifier” could be any one of the many generic vector processor algorithms. It is unspecified. Note further that the Specification recites:
[00102] In some embodiments, hard-wired circuitry may be used in place of or in combination with software instructions to implement aspects of the disclosure. Thus, embodiments of the disclosure are not limited to any specific combination of hardware circuitry and/or software. In embodiments, the term "logic" shall mean any combination of software or hardware that is used to implement all or part of the disclosure.
This “content classifier” limitation does not integrate the additional element into a practical application and represents “insignificant extra-solution activity”. (See, M.P.E.P. § 2106.05(I)(A))
(3) “One or more storage devices” is a broad term which is described at a high level. M.P.E.P. § 2106.05(d)(II) recites:
The courts have recognized the following computer functions as well‐understood, routine, and conventional functions when they are claimed in a merely generic manner (e.g., at a high level of generality) or as insignificant extra-solution activity.
***
iv. Storing and retrieving information in memory, Versata Dev. Group, Inc. v. SAP Am., Inc., 793 F.3d 1306, 1334, 115 USPQ2d 1681, 1701 (Fed. Cir. 2015); OIP Techs., 788 F.3d at 1363, 115 USPQ2d at 1092-93;
This “one or more storage devices” limitation does not integrate the additional element into a practical application and represents “insignificant extra-solution activity”. (See, M.P.E.P. § 2106.05(I)(A)).
(4) A “document” is a broad term which is described at a high level. M.P.E.P. § 2106.05(d)(II) recites:
The courts have recognized the following computer functions as well‐understood, routine, and conventional functions when they are claimed in a merely generic manner (e.g., at a high level of generality) or as insignificant extra-solution activity.
***
iii. Electronic recordkeeping, Alice Corp. Pty. Ltd. v. CLS Bank Int'l, 573 U.S. 208, 225, 110 USPQ2d 1984 (2014) (creating and maintaining “shadow accounts”); Ultramercial, 772 F.3d at 716, 112 USPQ2d at 1755 (updating an activity log);
This “document” limitation does not integrate the additional element into a practical application and represents “insignificant extra-solution activity”. (See, M.P.E.P. § 2106.05(I)(A)).
(5) A “content management system” is a broad term which is described at a high level. The term “content management system” is Applicant's name for the overall claimed invention. See, body of independent claims and FIG. 5, box 104 (no patentable weight given to data input). Applicant essentially argues that the claimed invention must be eligible because it is itself.
Applicant's assertion that it reduces document processing operations, reduces false positives, and training the classifier are simply nonfunctional descriptions of what it already does (except for the training, which was discussed above.)
This “content management system” limitation does not integrate the additional element into a practical application and represents “insignificant extra-solution activity”. (See, M.P.E.P. § 2106.05(I)(A)).
(6) A “receiving, over a network and at a content management server of a content management system, a plurality of documents from respective network interfaces of a plurality of user devices” is a broad term which is described at a high level. M.P.E.P. § 2106.05 (f)(2) recites in part:
(2) Whether the claim invokes computers or other machinery merely as a tool to perform an existing process. Use of a computer or other machinery in its ordinary capacity for economic or other tasks (e.g., to receive, store, or transmit data) or simply adding a general purpose computer or computer components after the fact to an abstract idea (e.g., a fundamental economic practice or mathematical equation) does not integrate a judicial exception into a practical application or provide significantly more. See Affinity Labs v. DirecTV, 838 F.3d 1253, 1262, 120 USPQ2d 1201, 1207 (Fed. Cir. 2016) (cellular telephone); TLI Communications LLC v. AV Auto, LLC, 823 F.3d 607, 613, 118 USPQ2d 1744, 1748 (Fed. Cir. 2016) (computer server and telephone unit). Similarly, “claiming the improved speed or efficiency inherent with applying the abstract idea on a computer” does not integrate a judicial exception into a practical application or provide an inventive concept. Intellectual Ventures I LLC v. Capital One Bank (USA), 792 F.3d 1363, 1367, 115 USPQ2d 1636, 1639 (Fed. Cir. 2015). In contrast, a claim that purports to improve computer capabilities or to improve an existing technology may integrate a judicial exception into a practical application or provide significantly more. McRO, Inc. v. Bandai Namco Games Am. Inc., 837 F.3d 1299, 1314-15, 120 USPQ2d 1091, 1101-02 (Fed. Cir. 2016); Enfish, LLC v. Microsoft Corp., 822 F.3d 1327, 1335-36, 118 USPQ2d 1684, 1688-89 (Fed. Cir. 2016). See MPEP §§ 2106.04(d)(1) and 2106.05(a) for a discussion of improvements to the functioning of a computer or to another technology or technical field.
TLI Communications provides an example of a claim invoking computers and other machinery merely as a tool to perform an existing process. The court stated that the claims describe steps of recording, administration and archiving of digital images, and found them to be directed to the abstract idea of classifying and storing digital images in an organized manner. 823 F.3d at 612, 118 USPQ2d at 1747. The court then turned to the additional elements of performing these functions using a telephone unit and a server and noted that these elements were being used in their ordinary capacity (i.e., the telephone unit is used to make calls and operate as a digital camera including compressing images and transmitting those images, and the server simply receives data, extracts classification information from the received data, and stores the digital images based on the extracted information). 823 F.3d at 612-13, 118 USPQ2d at 1747-48. In other words, the claims invoked the telephone unit and server merely as tools to execute the abstract idea. Thus, the court found that the additional elements did not add significantly more to the abstract idea because they were simply applying the abstract idea on a telephone network without any recitation of details of how to carry out the abstract idea.
This “receiving, over a network and at a content management server of a content management system, a plurality of documents from respective network interfaces of a plurality of user devices” limitation does not integrate the additional element into a practical application and represents “insignificant extra-solution activity”. (See, M.P.E.P. § 2106.05(I)(A)).
(7) A “limiting, by a limiter component in the content management system, access to the respective documents in the labeled dataset of the content management system by respective user devices of the plurality of user devices based on at least the one or more labels applied to either the individual ones of the respective documents as a whole or to specific portions thereof by the content classifier” is a broad term which is described at a high level. Applicant's Specification recites:
[00110] FIG. 7B depicts a block diagram of an instance of a cloud-based environment 7B00. Such a cloud-based environment supports access to workspaces through the execution of workspace access code (e.g., workspace access code 7420, workspace access code 7421, and workspace access code 7422). Workspace access code can be executed on any of access devices 752 (e.g., laptop device 7524, workstation device 7525, IP phone device 7523, tablet device 7522, smart phone device 7521, etc.), and can be configured to access any type of object. Strictly as examples, such objects can be folders or directories or can be files of any filetype. The files or folders or directories can be organized into any hierarchy. Any type of object can comprise or be associated with access permissions. The access permissions in turn may correspond to different actions to be taken over the object. Strictly as one example, a first permission (e.g., PREVIEWONLY) may be associated with a first action (e.g., preview), while a second permission (e.g., READ) may be associated with a second action (e.g., download), etc. Furthermore, permissions may be associated to any particular user or any particular group of users.
Further, M.P.E.P. § 2106.05 (f)(2) recites in part:
(2) Whether the claim invokes computers or other machinery merely as a tool to perform an existing process. Use of a computer or other machinery in its ordinary capacity for economic or other tasks (e.g., to receive, store, or transmit data) or simply adding a general purpose computer or computer components after the fact to an abstract idea (e.g., a fundamental economic practice or mathematical equation) does not integrate a judicial exception into a practical application or provide significantly more. See Affinity Labs v. DirecTV, 838 F.3d 1253, 1262, 120 USPQ2d 1201, 1207 (Fed. Cir. 2016) (cellular telephone); TLI Communications LLC v. AV Auto, LLC, 823 F.3d 607, 613, 118 USPQ2d 1744, 1748 (Fed. Cir. 2016) (computer server and telephone unit). Similarly, “claiming the improved speed or efficiency inherent with applying the abstract idea on a computer” does not integrate a judicial exception into a practical application or provide an inventive concept. Intellectual Ventures I LLC v. Capital One Bank (USA), 792 F.3d 1363, 1367, 115 USPQ2d 1636, 1639 (Fed. Cir. 2015). In contrast, a claim that purports to improve computer capabilities or to improve an existing technology may integrate a judicial exception into a practical application or provide significantly more. McRO, Inc. v. Bandai Namco Games Am. Inc., 837 F.3d 1299, 1314-15, 120 USPQ2d 1091, 1101-02 (Fed. Cir. 2016); Enfish, LLC v. Microsoft Corp., 822 F.3d 1327, 1335-36, 118 USPQ2d 1684, 1688-89 (Fed. Cir. 2016). See MPEP §§ 2106.04(d)(1) and 2106.05(a) for a discussion of improvements to the functioning of a computer or to another technology or technical field.
TLI Communications provides an example of a claim invoking computers and other machinery merely as a tool to perform an existing process. The court stated that the claims describe steps of recording, administration and archiving of digital images, and found them to be directed to the abstract idea of classifying and storing digital images in an organized manner. 823 F.3d at 612, 118 USPQ2d at 1747. The court then turned to the additional elements of performing these functions using a telephone unit and a server and noted that these elements were being used in their ordinary capacity (i.e., the telephone unit is used to make calls and operate as a digital camera including compressing images and transmitting those images, and the server simply receives data, extracts classification information from the received data, and stores the digital images based on the extracted information). 823 F.3d at 612-13, 118 USPQ2d at 1747-48. In other words, the claims invoked the telephone unit and server merely as tools to execute the abstract idea. Thus, the court found that the additional elements did not add significantly more to the abstract idea because they were simply applying the abstract idea on a telephone network without any recitation of details of how to carry out the abstract idea.
Therefore, the option to limit access permissions is a standard feature of any server in a cloud-based environment.
This “limiting, by a limiter component in the content management system, access to the respective documents in the labeled dataset of the content management system by respective user devices of the plurality of user devices based on at least the one or more labels applied to either the individual ones of the respective documents as a whole or to specific portions thereof by the content classifier” limitation does not integrate the additional element into a practical application and represents “insignificant extra-solution activity”. (See, M.P.E.P. § 2106.05(I)(A)).
The answer to the inquiry is “NO”, no additional elements integrate the claimed abstract idea into a practical application.
Step 2B inquiry:
Does the claim provide an inventive concept, i.e., does the claim recite additional element(s) or a combination of elements that amount to significantly more than the judicial exception in the claim?
Applicant’s claims contain the following “additional elements”:
(1) A “training”/“training the content classifier using both the results received from a PII detection module and the second portion of the document”
(2) A content classifier
(3) One or more storage devices
(4) A document
(5) A content management system
(6) Receiving, over a network and at a content management server of a content management system, a plurality of documents from respective network interfaces of a plurality of user devices
(7) limiting, by a limiter component in the content management system, access to the respective documents in the labeled dataset of the content management system by respective user devices of the plurality of user devices based on at least the one or more labels applied to either the individual ones of the respective documents as a whole or to specific portions thereof by the content classifier
(1) A “training”/“training the content classifier using both the results received from a PII detection module and the second portion of the document” is a broad term which is described at a high level. Applicant’s Specification recites:
[0083] The figure depicts one possible implementation of step 204 (FIG. 2) This implementation takes as inputs (1) a labeled dataset 222 and (2) a PII detection rulebase 117, and produces adjusted weights (e.g., weight type1 and weight type2) The error correction module 408 receives two incoming values from two conditionally-independent sets of inputs (e.g., the vector processor value and the rule processor value, as shown), compares them to an error calculation, and then adjusts the weights to reduce the error. The weight adjustment method could be a gradient descent algorithm employing, for example, one or more of several back-propagation methods. In one example implementation of back-propagation, the vector processor 404 is a feed forward deep neural network and adjustments are computed by (1) differentiating the loss function for each input in each layer of the network, and (2) iteratively choosing a weight adjustment that would reduce the error by a precalculated maximum amount and then (3) applying the adjustment. The iterations are repeated until the overall error (e.g., as measured by a loss function) reaches an acceptable value, and/or when no more weight adjustment improvements are possible. In this specific example, the back- propagation algorithm analyzes labels that are generated by the rule based module 117, which can potentially produce noisy label outputs. However, due to the mathematic lemmas that arise as a result of choosing two conditionally independent sets of inputs, back-propagation will converge, resulting in a classifier that is as good (e.g., in terms of precision and recall) as a classifier that had been trained on non-noisy (e.g., perfectly accurate) labels.
Note that, according to the Specification, the claimed “training” could be any one of the many generic gradient descent algorithms. It is unspecified. Note further that the Specification recites:
[00102] In some embodiments, hard-wired circuitry may be used in place of or in combination with software instructions to implement aspects of the disclosure. Thus, embodiments of the disclosure are not limited to any specific combination of hardware circuitry and/or software. In embodiments, the term "logic" shall mean any combination of software or hardware that is used to implement all or part of the disclosure.
Therefore, the claim as a whole does not amount to significantly more than the exception itself (i.e., there is no inventive concept in the claim) (See, M.P.E.P. § 2106.05(II))
(2) A “content classifier” is a broad term which is described at a high level. Applicant’s Specification recites:
[0083] The figure depicts one possible implementation of step 204 (FIG. 2) This implementation takes as inputs (1) a labeled dataset 222 and (2) a PII detection rulebase 117, and produces adjusted weights (e.g., weight type1 and weight type2) The error correction module 408 receives two incoming values from two conditionally-independent sets of inputs (e.g., the vector processor value and the rule processor value, as shown), compares them to an error calculation, and then adjusts the weights to reduce the error. The weight adjustment method could be a gradient descent algorithm employing, for example, one or more of several back-propagation methods. In one example implementation of back-propagation, the vector processor 404 is a feed forward deep neural network and adjustments are computed by (1) differentiating the loss function for each input in each layer of the network, and (2) iteratively choosing a weight adjustment that would reduce the error by a precalculated maximum amount and then (3) applying the adjustment. The iterations are repeated until the overall error (e.g., as measured by a loss function) reaches an acceptable value, and/or when no more weight adjustment improvements are possible. In this specific example, the back- propagation algorithm analyzes labels that are generated by the rule based module 117, which can potentially produce noisy label outputs. However, due to the mathematic lemmas that arise as a result of choosing two conditionally independent sets of inputs, back-propagation will converge, resulting in a classifier that is as good (e.g., in terms of precision and recall) as a classifier that had been trained on non-noisy (e.g., perfectly accurate) labels.
Note that, according to the Specification, the claimed “content classifier” could be any one of the many generic vector processor algorithms. It is unspecified. Note further that the Specification recites:
[00102] In some embodiments, hard-wired circuitry may be used in place of or in combination with software instructions to implement aspects of the disclosure. Thus, embodiments of the disclosure are not limited to any specific combination of hardware circuitry and/or software. In embodiments, the term "logic" shall mean any combination of software or hardware that is used to implement all or part of the disclosure.
Therefore, the claim as a whole does not amount to significantly more than the exception itself (i.e., there is no inventive concept in the claim) (See, M.P.E.P. § 2106.05(II))
(3) “One or more storage devices” is a broad term which is described at a high level. M.P.E.P. § 2106.05(d)(II) recites:
The courts have recognized the following computer functions as well‐understood, routine, and conventional functions when they are claimed in a merely generic manner (e.g., at a high level of generality) or as insignificant extra-solution activity.
***
iv. Storing and retrieving information in memory, Versata Dev. Group, Inc. v. SAP Am., Inc., 793 F.3d 1306, 1334, 115 USPQ2d 1681, 1701 (Fed. Cir. 2015); OIP Techs., 788 F.3d at 1363, 115 USPQ2d at 1092-93;
Therefore, the claim as a whole does not amount to significantly more than the exception itself (i.e., there is no inventive concept in the claim) (See, M.P.E.P. § 2106.05(II))
(4) A “document” is a broad term which is described at a high level. M.P.E.P. § 2106.05(d)(II) recites:
The courts have recognized the following computer functions as well‐understood, routine, and conventional functions when they are claimed in a merely generic manner (e.g., at a high level of generality) or as insignificant extra-solution activity.
***
iii. Electronic recordkeeping, Alice Corp. Pty. Ltd. v. CLS Bank Int'l, 573 U.S. 208, 225, 110 USPQ2d 1984 (2014) (creating and maintaining “shadow accounts”); Ultramercial, 772 F.3d at 716, 112 USPQ2d at 1755 (updating an activity log);
Therefore, the claim as a whole does not amount to significantly more than the exception itself (i.e., there is no inventive concept in the claim) (See, M.P.E.P. § 2106.05(II))
(5) A “content management system” is a broad term which is described at a high level. The term “content management system” is Applicant's name for the overall claimed invention. See, body of independent claims and FIG. 5, box 104 (no patentable weight given to data input). Applicant essentially argues that the claimed invention must be eligible because it is itself.
Applicant's assertion that it reduces document processing operations, reduces false positives, and training the classifier are simply nonfunctional descriptions of what it already does (except for the training, which was discussed above.)
Therefore, the claim as a whole does not amount to significantly more than the exception itself (i.e., there is no inventive concept in the claim) (See, M.P.E.P. § 2106.05(II))
(6) A “receiving, over a network and at a content management server of a content management system, a plurality of documents from respective network interfaces of a plurality of user devices” is a broad term which is described at a high level. M.P.E.P. § 2106.05 (f)(2) recites in part:
(2) Whether the claim invokes computers or other machinery merely as a tool to perform an existing process. Use of a computer or other machinery in its ordinary capacity for economic or other tasks (e.g., to receive, store, or transmit data) or simply adding a general purpose computer or computer components after the fact to an abstract idea (e.g., a fundamental economic practice or mathematical equation) does not integrate a judicial exception into a practical application or provide significantly more. See Affinity Labs v. DirecTV, 838 F.3d 1253, 1262, 120 USPQ2d 1201, 1207 (Fed. Cir. 2016) (cellular telephone); TLI Communications LLC v. AV Auto, LLC, 823 F.3d 607, 613, 118 USPQ2d 1744, 1748 (Fed. Cir. 2016) (computer server and telephone unit). Similarly, “claiming the improved speed or efficiency inherent with applying the abstract idea on a computer” does not integrate a judicial exception into a practical application or provide an inventive concept. Intellectual Ventures I LLC v. Capital One Bank (USA), 792 F.3d 1363, 1367, 115 USPQ2d 1636, 1639 (Fed. Cir. 2015). In contrast, a claim that purports to improve computer capabilities or to improve an existing technology may integrate a judicial exception into a practical application or provide significantly more. McRO, Inc. v. Bandai Namco Games Am. Inc., 837 F.3d 1299, 1314-15, 120 USPQ2d 1091, 1101-02 (Fed. Cir. 2016); Enfish, LLC v. Microsoft Corp., 822 F.3d 1327, 1335-36, 118 USPQ2d 1684, 1688-89 (Fed. Cir. 2016). See MPEP §§ 2106.04(d)(1) and 2106.05(a) for a discussion of improvements to the functioning of a computer or to another technology or technical field.
TLI Communications provides an example of a claim invoking computers and other machinery merely as a tool to perform an existing process. The court stated that the claims describe steps of recording, administration and archiving of digital images, and found them to be directed to the abstract idea of classifying and storing digital images in an organized manner. 823 F.3d at 612, 118 USPQ2d at 1747. The court then turned to the additional elements of performing these functions using a telephone unit and a server and noted that these elements were being used in their ordinary capacity (i.e., the telephone unit is used to make calls and operate as a digital camera including compressing images and transmitting those images, and the server simply receives data, extracts classification information from the received data, and stores the digital images based on the extracted information). 823 F.3d at 612-13, 118 USPQ2d at 1747-48. In other words, the claims invoked the telephone unit and server merely as tools to execute the abstract idea. Thus, the court found that the additional elements did not add significantly more to the abstract idea because they were simply applying the abstract idea on a telephone network without any recitation of details of how to carry out the abstract idea.
Therefore, the claim as a whole does not amount to significantly more than the exception itself (i.e., there is no inventive concept in the claim) (See, M.P.E.P. § 2106.05(II))
(7) A “limiting, by a limiter component in the content management system, access to the respective documents in the labeled dataset of the content management system by respective user devices of the plurality of user devices based on at least the one or more labels applied to either the individual ones of the respective documents as a whole or to specific portions thereof by the content classifier” is a broad term which is described at a high level. Applicant's Specification recites:
[00110] FIG. 7B depicts a block diagram of an instance of a cloud-based environment 7B00. Such a cloud-based environment supports access to workspaces through the execution of workspace access code (e.g., workspace access code 7420, workspace access code 7421, and workspace access code 7422). Workspace access code can be executed on any of access devices 752 (e.g., laptop device 7524, workstation device 7525, IP phone device 7523, tablet device 7522, smart phone device 7521, etc.), and can be configured to access any type of object. Strictly as examples, such objects can be folders or directories or can be files of any filetype. The files or folders or directories can be organized into any hierarchy. Any type of object can comprise or be associated with access permissions. The access permissions in turn may correspond to different actions to be taken over the object. Strictly as one example, a first permission (e.g., PREVIEWONLY) may be associated with a first action (e.g., preview), while a second permission (e.g., READ) may be associated with a second action (e.g., download), etc. Furthermore, permissions may be associated to any particular user or any particular group of users.
Further, M.P.E.P. § 2106.05 (f)(2) recites in part:
(2) Whether the claim invokes computers or other machinery merely as a tool to perform an existing process. Use of a computer or other machinery in its ordinary capacity for economic or other tasks (e.g., to receive, store, or transmit data) or simply adding a general purpose computer or computer components after the fact to an abstract idea (e.g., a fundamental economic practice or mathematical equation) does not integrate a judicial exception into a practical application or provide significantly more. See Affinity Labs v. DirecTV, 838 F.3d 1253, 1262, 120 USPQ2d 1201, 1207 (Fed. Cir. 2016) (cellular telephone); TLI Communications LLC v. AV Auto, LLC, 823 F.3d 607, 613, 118 USPQ2d 1744, 1748 (Fed. Cir. 2016) (computer server and telephone unit). Similarly, “claiming the improved speed or efficiency inherent with applying the abstract idea on a computer” does not integrate a judicial exception into a practical application or provide an inventive concept. Intellectual Ventures I LLC v. Capital One Bank (USA), 792 F.3d 1363, 1367, 115 USPQ2d 1636, 1639 (Fed. Cir. 2015). In contrast, a claim that purports to improve computer capabilities or to improve an existing technology may integrate a judicial exception into a practical application or provide significantly more. McRO, Inc. v. Bandai Namco Games Am. Inc., 837 F.3d 1299, 1314-15, 120 USPQ2d 1091, 1101-02 (Fed. Cir. 2016); Enfish, LLC v. Microsoft Corp., 822 F.3d 1327, 1335-36, 118 USPQ2d 1684, 1688-89 (Fed. Cir. 2016). See MPEP §§ 2106.04(d)(1) and 2106.05(a) for a discussion of improvements to the functioning of a computer or to another technology or technical field.
TLI Communications provides an example of a claim invoking computers and other machinery merely as a tool to perform an existing process. The court stated that the claims describe steps of recording, administration and archiving of digital images, and found them to be directed to the abstract idea of classifying and storing digital images in an organized manner. 823 F.3d at 612, 118 USPQ2d at 1747. The court then turned to the additional elements of performing these functions using a telephone unit and a server and noted that these elements were being used in their ordinary capacity (i.e., the telephone unit is used to make calls and operate as a digital camera including compressing images and transmitting those images, and the server simply receives data, extracts classification information from the received data, and stores the digital images based on the extracted information). 823 F.3d at 612-13, 118 USPQ2d at 1747-48. In other words, the claims invoked the telephone unit and server merely as tools to execute the abstract idea. Thus, the court found that the additional elements did not add significantly more to the abstract idea because they were simply applying the abstract idea on a telephone network without any recitation of details of how to carry out the abstract idea.
Therefore, the option to limit access permissions is a standard feature of any server in a cloud-based environment.
Therefore, the claim as a whole does not amount to significantly more than the exception itself (i.e., there is no inventive concept in the claim) (See, M.P.E.P. § 2106.05(II))
Therefore, the answer to the inquiry is “NO”, no additional elements provide an inventive concept that is significantly more than the claimed abstract ideas the claimed abstract idea into a practical application.
Claim 1 is, therefore, NOT ELIGIBLE subject matter under 35 U.S.C. § 101.
Claim 2
Claim 2 recites:
The method of claim 1, further comprising: identifying a selected portion of a subject content object and applying the selected portion to the content classifier to determine whether characteristics of the selected portion are indicative that the document does contain PII.
Applicant’s Claim 2 merely teaches identification and application of data. It does not integrate the abstract idea to a practical application, nor is it anything significantly more than the abstract idea. (See, 2106.05(a)(II))
Claim 2 is, therefore, NOT ELIGIBLE subject matter under 35 U.S.C. § 101.
Claim 3
Claim 3 recites:
The method of claim 2, further comprising: communicating a message to a user device, wherein the message comprises at least a portion of one or more governance restrictions pertaining to communication of personally identifiable information.
Applicant’s Claim 3 merely teaches communication of data (i.e., a pure signal) It does not integrate the abstract idea to a practical application, nor is it anything significantly more than the abstract idea. (See, 2106.05(a)(II))
Claim 3 is, therefore, NOT ELIGIBLE subject matter under 35 U.S.C. § 101.
Claim 4
Claim 4 recites:
The method of claim 1, wherein application of the PII rule to the first portion of the document is used to identify at least one of, one or more infotype designations, one or more infotype locations, or one or more infotype hotwords.
Applicant’s Claim 4 merely teaches identification of data. It does not integrate the abstract idea to a practical application, nor is it anything significantly more than the abstract idea. (See, 2106.05(a)(II))
Claim 4 is, therefore, NOT ELIGIBLE subject matter under 35 U.S.C. § 101.
Claim 5
Claim 5 recites:
The method of claim 4, wherein the second portion of the document selected from the unlabeled dataset does not contain any occurrence of the one or more infotype hotwords.
Applicant’s Claim 5 merely teaches missing data. It does not integrate the abstract idea to a practical application, nor is it anything significantly more than the abstract idea. (See, 2106.05(a)(II))
Claim 5 is, therefore, NOT ELIGIBLE subject matter under 35 U.S.C. § 101.
Claim 6
Claim 6 recites:
The method of claim 1, further comprising: adjusting a weight of either the likelihood value or the confidence value based on a gradient descent algorithm.
Applicant’s Claim 6 merely teaches adjusting of weights (i.e., pure numbers) It does not integrate the abstract idea to a practical application, nor is it anything significantly more than the abstract idea. (See, 2106.05(a)(II))
Claim 6 is, therefore, NOT ELIGIBLE subject matter under 35 U.S.C. § 101.
Claim 7
Claim 7 recites:
The method of claim 1, further comprising: adjusting a weight of either the likelihood value or the confidence value based on an error calculation that compares a vector processor value to a rule processor value.
Applicant’s Claim 7 merely teaches adjusting of weights (i.e., pure numbers) It does not integrate the abstract idea to a practical application, nor is it anything significantly more than the abstract idea. (See, 2106.05(a)(II))
Claim 7 is, therefore, NOT ELIGIBLE subject matter under 35 U.S.C. § 101.
Claim 8
Step 1 inquiry: Does this claim fall within a statutory category?
The preamble of the claim recites “8. A non-transitory computer readable medium having stored thereon a sequence of instructions which, when stored in memory and executed by one or more processors causes the one or more processors to perform a set of acts, the set of acts comprising…” Therefore, it is a “non-transitory computer readable medium” (or “product of manufacture”), which is a statutory category of invention. Therefore, the answer to the inquiry is: “YES”.
Step 2A (Prong One) inquiry:
Are there limitations in Claim 8 that recite abstract ideas?
YES. The following limitations in Claim 8 recite abstract ideas that fall within at least one of the groupings of abstract ideas enumerated in the 2019 PEG. Specifically, they are “mental steps”:
• an unlabeled dataset
• a labeled data set
• a plurality of documents
• personally identifiable information (PII)
• determining, based on results received from a PII detection module that applies applying a PII rule stored in the rulebase comprising the plurality of rules for detecting PII to a first portion of a document selected from the unlabeled dataset
• a PII rule
• a rulebase comprising the plurality of rules for detecting PII
• results received from a PII detection module
• a first portion of a document
• a confidence value
• selecting
• second portion of the document
• associating
• a likelihood value
Step 2A (Prong Two) inquiry:
Are there additional elements or a combination of elements in the claim that apply, rely on, or use the judicial exception in a manner that imposes a meaningful limit on the judicial exception, such that it is more than a drafting effort designed to monopolize the exception?
Applicant’s claims contain the following “additional elements”:
(1) stored in memory/one or more storage devices
(2) processors
(3) A “training”/“training the content classifier using both the results received from a PII detection module and the second portion of the document”
(4) A content classifier
(5) A document
(6) A content management system
(7) Receiving, over a network and at a content management server of a content management system, a plurality of documents from respective network interfaces of a plurality of user devices
(8) limiting, by a limiter component in the content management system, access to the respective documents in the labeled dataset of the content management system by respective user devices of the plurality of user devices based on at least the one or more labels applied to either the individual ones of the respective documents as a whole or to specific portions thereof by the content classifier
(1) A “memory/one or more storage devices” is a broad term which is described at a high level. Applicant’s Specification recites:
[00103] The term "computer readable medium" or "computer usable medium" as used herein refers to any medium that participates in providing instructions to data processor 707 for execution. Such a medium may take many forms including, but not limited to, non-volatile media and volatile media. Non-volatile media includes, for example, optical or magnetic disks such as disk drives or tape drives. Volatile media includes dynamic memory such as RAM.
[00104] Common forms of computer readable media include, for example, floppy disk, flexible disk, hard disk, magnetic tape, or any other magnetic medium; CD-ROM or any other optical medium; punch cards, paper tape, or any other physical medium with patterns of holes; RAM, PROM, EPROM, FLASH-EPROM, or any other memory chip or cartridge, or any other non- transitory computer readable medium. Such data can be stored, for example, in any form of external data repository 731, which in turn can be formatted into any one or more storage areas, and which can comprise parameterized storage 739 accessible by a key (e.g., filename, table name, block address, offset address, etc.)
This “memory/one or more storage devices” limitation does not integrate the additional element into a practical application and represents “insignificant extra-solution activity”. (See, M.P.E.P. § 2106.05(I)(A))
(2) A “processor” is a broad term which is described at a high level. Applicant’s Specification recites:
[0098] FIG. 7A depicts a block diagram of an instance of a computer system 7A00 suitable for implementing embodiments of the present disclosure. Computer system 7A00 includes a bus 706 or other communication mechanism for communicating information. The bus interconnects subsystems and devices such as a central processing unit (CPU), or a multi-core CPU (e.g., data processor 707), a system memory (e.g., main memory 708, or an area of random access memory (RAM)), a non- volatile storage device or non-volatile storage area (e.g., read-only memory 709), an internal storage device 710 or external storage device 713 (e.g., magnetic or optical), a data interface 733, a communications interface 714 (e.g., PHY, MAC, Ethernet interface, modem, etc.) The aforementioned components are shown within processing element partition 701, however other partitions are possible. Computer system 7A00 further comprises a display 711 (e.g., CRT or LCD), various input devices 712 (e.g., keyboard, cursor control), and an external data repository 731.
This “processor” limitation does not integrate the additional element into a practical application and represents “insignificant extra-solution activity”. (See, M.P.E.P. § 2106.05(I)(A))
(3) A “training”/“training the content classifier using both the results received from a PII detection module and the second portion of the document” is a broad term which is described at a high level. Applicant’s Specification recites:
[0083] The figure depicts one possible implementation of step 204 (FIG. 2) This implementation takes as inputs (1) a labeled dataset 222 and (2) a PII detection rulebase 117, and produces adjusted weights (e.g., weight type1 and weight type2) The error correction module 408 receives two incoming values from two conditionally-independent sets of inputs (e.g., the vector processor value and the rule processor value, as shown), compares them to an error calculation, and then adjusts the weights to reduce the error. The weight adjustment method could be a gradient descent algorithm employing, for example, one or more of several back-propagation methods. In one example implementation of back-propagation, the vector processor 404 is a feed forward deep neural network and adjustments are computed by (1) differentiating the loss function for each input in each layer of the network, and (2) iteratively choosing a weight adjustment that would reduce the error by a precalculated maximum amount and then (3) applying the adjustment. The iterations are repeated until the overall error (e.g., as measured by a loss function) reaches an acceptable value, and/or when no more weight adjustment improvements are possible. In this specific example, the back- propagation algorithm analyzes labels that are generated by the rule based module 117, which can potentially produce noisy label outputs. However, due to the mathematic lemmas that arise as a result of choosing two conditionally independent sets of inputs, back-propagation will converge, resulting in a classifier that is as good (e.g., in terms of precision and recall) as a classifier that had been trained on non-noisy (e.g., perfectly accurate) labels.
Note that, according to the Specification, the claimed “training” could be any one of the many generic gradient descent algorithms. It is unspecified. Note further that the Specification recites:
[00102] In some embodiments, hard-wired circuitry may be used in place of or in combination with software instructions to implement aspects of the disclosure. Thus, embodiments of the disclosure are not limited to any specific combination of hardware circuitry and/or software. In embodiments, the term "logic" shall mean any combination of software or hardware that is used to implement all or part of the disclosure.
This “training”/“training the content classifier using both the results received from a PII detection module and the second portion of the document” limitation does not integrate the additional element into a practical application and represents “insignificant extra-solution activity”. (See, M.P.E.P. § 2106.05(I)(A))
(4) A “content classifier” is a broad term which is described at a high level. Applicant’s Specification recites:
[0083] The figure depicts one possible implementation of step 204 (FIG. 2) This implementation takes as inputs (1) a labeled dataset 222 and (2) a PII detection rulebase 117, and produces adjusted weights (e.g., weight type1 and weight type2) The error correction module 408 receives two incoming values from two conditionally-independent sets of inputs (e.g., the vector processor value and the rule processor value, as shown), compares them to an error calculation, and then adjusts the weights to reduce the error. The weight adjustment method could be a gradient descent algorithm employing, for example, one or more of several back-propagation methods. In one example implementation of back-propagation, the vector processor 404 is a feed forward deep neural network and adjustments are computed by (1) differentiating the loss function for each input in each layer of the network, and (2) iteratively choosing a weight adjustment that would reduce the error by a precalculated maximum amount and then (3) applying the adjustment. The iterations are repeated until the overall error (e.g., as measured by a loss function) reaches an acceptable value, and/or when no more weight adjustment improvements are possible. In this specific example, the back- propagation algorithm analyzes labels that are generated by the rule based module 117, which can potentially produce noisy label outputs. However, due to the mathematic lemmas that arise as a result of choosing two conditionally independent sets of inputs, back-propagation will converge, resulting in a classifier that is as good (e.g., in terms of precision and recall) as a classifier that had been trained on non-noisy (e.g., perfectly accurate) labels.
Note that, according to the Specification, the claimed “content classifier” could be any one of the many generic vector processor algorithms. It is unspecified. Note further that the Specification recites:
[00102] In some embodiments, hard-wired circuitry may be used in place of or in combination with software instructions to implement aspects of the disclosure. Thus, embodiments of the disclosure are not limited to any specific combination of hardware circuitry and/or software. In embodiments, the term "logic" shall mean any combination of software or hardware that is used to implement all or part of the disclosure.
This “content classifier” limitation does not integrate the additional element into a practical application and represents “insignificant extra-solution activity”. (See, M.P.E.P. § 2106.05(I)(A))
(5) A “document” is a broad term which is described at a high level. M.P.E.P. § 2106.05(d)(II) recites:
The courts have recognized the following computer functions as well‐understood, routine, and conventional functions when they are claimed in a merely generic manner (e.g., at a high level of generality) or as insignificant extra-solution activity.
***
iii. Electronic recordkeeping, Alice Corp. Pty. Ltd. v. CLS Bank Int'l, 573 U.S. 208, 225, 110 USPQ2d 1984 (2014) (creating and maintaining “shadow accounts”); Ultramercial, 772 F.3d at 716, 112 USPQ2d at 1755 (updating an activity log);
This “document” limitation does not integrate the additional element into a practical application and represents “insignificant extra-solution activity”. (See, M.P.E.P. § 2106.05(I)(A)).
(6) A “content management system” is a broad term which is described at a high level. The term “content management system” is Applicant's name for the overall claimed invention. See, body of independent claims and FIG. 5, box 104 (no patentable weight given to data input). Applicant essentially argues that the claimed invention must be eligible because it is itself.
Applicant's assertion that it reduces document processing operations, reduces false positives, and training the classifier are simply nonfunctional descriptions of what it already does (except for the training, which was discussed above.)
This “content management system” limitation does not integrate the additional element into a practical application and represents “insignificant extra-solution activity”. (See, M.P.E.P. § 2106.05(I)(A)).
(7) A “receiving, over a network and at a content management server of a content management system, a plurality of documents from respective network interfaces of a plurality of user devices” is a broad term which is described at a high level. M.P.E.P. § 2106.05 (f)(2) recites in part:
(2) Whether the claim invokes computers or other machinery merely as a tool to perform an existing process. Use of a computer or other machinery in its ordinary capacity for economic or other tasks (e.g., to receive, store, or transmit data) or simply adding a general purpose computer or computer components after the fact to an abstract idea (e.g., a fundamental economic practice or mathematical equation) does not integrate a judicial exception into a practical application or provide significantly more. See Affinity Labs v. DirecTV, 838 F.3d 1253, 1262, 120 USPQ2d 1201, 1207 (Fed. Cir. 2016) (cellular telephone); TLI Communications LLC v. AV Auto, LLC, 823 F.3d 607, 613, 118 USPQ2d 1744, 1748 (Fed. Cir. 2016) (computer server and telephone unit). Similarly, “claiming the improved speed or efficiency inherent with applying the abstract idea on a computer” does not integrate a judicial exception into a practical application or provide an inventive concept. Intellectual Ventures I LLC v. Capital One Bank (USA), 792 F.3d 1363, 1367, 115 USPQ2d 1636, 1639 (Fed. Cir. 2015). In contrast, a claim that purports to improve computer capabilities or to improve an existing technology may integrate a judicial exception into a practical application or provide significantly more. McRO, Inc. v. Bandai Namco Games Am. Inc., 837 F.3d 1299, 1314-15, 120 USPQ2d 1091, 1101-02 (Fed. Cir. 2016); Enfish, LLC v. Microsoft Corp., 822 F.3d 1327, 1335-36, 118 USPQ2d 1684, 1688-89 (Fed. Cir. 2016). See MPEP §§ 2106.04(d)(1) and 2106.05(a) for a discussion of improvements to the functioning of a computer or to another technology or technical field.
TLI Communications provides an example of a claim invoking computers and other machinery merely as a tool to perform an existing process. The court stated that the claims describe steps of recording, administration and archiving of digital images, and found them to be directed to the abstract idea of classifying and storing digital images in an organized manner. 823 F.3d at 612, 118 USPQ2d at 1747. The court then turned to the additional elements of performing these functions using a telephone unit and a server and noted that these elements were being used in their ordinary capacity (i.e., the telephone unit is used to make calls and operate as a digital camera including compressing images and transmitting those images, and the server simply receives data, extracts classification information from the received data, and stores the digital images based on the extracted information). 823 F.3d at 612-13, 118 USPQ2d at 1747-48. In other words, the claims invoked the telephone unit and server merely as tools to execute the abstract idea. Thus, the court found that the additional elements did not add significantly more to the abstract idea because they were simply applying the abstract idea on a telephone network without any recitation of details of how to carry out the abstract idea.
This “receiving, over a network and at a content management server of a content management system, a plurality of documents from respective network interfaces of a plurality of user devices” limitation does not integrate the additional element into a practical application and represents “insignificant extra-solution activity”. (See, M.P.E.P. § 2106.05(I)(A)).
(8) A “limiting, by a limiter component in the content management system, access to the respective documents in the labeled dataset of the content management system by respective user devices of the plurality of user devices based on at least the one or more labels applied to either the individual ones of the respective documents as a whole or to specific portions thereof by the content classifier” is a broad term which is described at a high level. Applicant's Specification recites:
[00110] FIG. 7B depicts a block diagram of an instance of a cloud-based environment 7B00. Such a cloud-based environment supports access to workspaces through the execution of workspace access code (e.g., workspace access code 7420, workspace access code 7421, and workspace access code 7422). Workspace access code can be executed on any of access devices 752 (e.g., laptop device 7524, workstation device 7525, IP phone device 7523, tablet device 7522, smart phone device 7521, etc.), and can be configured to access any type of object. Strictly as examples, such objects can be folders or directories or can be files of any filetype. The files or folders or directories can be organized into any hierarchy. Any type of object can comprise or be associated with access permissions. The access permissions in turn may correspond to different actions to be taken over the object. Strictly as one example, a first permission (e.g., PREVIEWONLY) may be associated with a first action (e.g., preview), while a second permission (e.g., READ) may be associated with a second action (e.g., download), etc. Furthermore, permissions may be associated to any particular user or any particular group of users.
Further, M.P.E.P. § 2106.05 (f)(2) recites in part:
(2) Whether the claim invokes computers or other machinery merely as a tool to perform an existing process. Use of a computer or other machinery in its ordinary capacity for economic or other tasks (e.g., to receive, store, or transmit data) or simply adding a general purpose computer or computer components after the fact to an abstract idea (e.g., a fundamental economic practice or mathematical equation) does not integrate a judicial exception into a practical application or provide significantly more. See Affinity Labs v. DirecTV, 838 F.3d 1253, 1262, 120 USPQ2d 1201, 1207 (Fed. Cir. 2016) (cellular telephone); TLI Communications LLC v. AV Auto, LLC, 823 F.3d 607, 613, 118 USPQ2d 1744, 1748 (Fed. Cir. 2016) (computer server and telephone unit). Similarly, “claiming the improved speed or efficiency inherent with applying the abstract idea on a computer” does not integrate a judicial exception into a practical application or provide an inventive concept. Intellectual Ventures I LLC v. Capital One Bank (USA), 792 F.3d 1363, 1367, 115 USPQ2d 1636, 1639 (Fed. Cir. 2015). In contrast, a claim that purports to improve computer capabilities or to improve an existing technology may integrate a judicial exception into a practical application or provide significantly more. McRO, Inc. v. Bandai Namco Games Am. Inc., 837 F.3d 1299, 1314-15, 120 USPQ2d 1091, 1101-02 (Fed. Cir. 2016); Enfish, LLC v. Microsoft Corp., 822 F.3d 1327, 1335-36, 118 USPQ2d 1684, 1688-89 (Fed. Cir. 2016). See MPEP §§ 2106.04(d)(1) and 2106.05(a) for a discussion of improvements to the functioning of a computer or to another technology or technical field.
TLI Communications provides an example of a claim invoking computers and other machinery merely as a tool to perform an existing process. The court stated that the claims describe steps of recording, administration and archiving of digital images, and found them to be directed to the abstract idea of classifying and storing digital images in an organized manner. 823 F.3d at 612, 118 USPQ2d at 1747. The court then turned to the additional elements of performing these functions using a telephone unit and a server and noted that these elements were being used in their ordinary capacity (i.e., the telephone unit is used to make calls and operate as a digital camera including compressing images and transmitting those images, and the server simply receives data, extracts classification information from the received data, and stores the digital images based on the extracted information). 823 F.3d at 612-13, 118 USPQ2d at 1747-48. In other words, the claims invoked the telephone unit and server merely as tools to execute the abstract idea. Thus, the court found that the additional elements did not add significantly more to the abstract idea because they were simply applying the abstract idea on a telephone network without any recitation of details of how to carry out the abstract idea.
Therefore, the option to limit access permissions is a standard feature of any server in a cloud-based environment.
This “limiting, by a limiter component in the content management system, access to the respective documents in the labeled dataset of the content management system by respective user devices of the plurality of user devices based on at least the one or more labels applied to either the individual ones of the respective documents as a whole or to specific portions thereof by the content classifier” limitation does not integrate the additional element into a practical application and represents “insignificant extra-solution activity”. (See, M.P.E.P. § 2106.05(I)(A)).
The answer to the inquiry is “NO”, no additional elements integrate the claimed abstract idea into a practical application.
Step 2B inquiry:
Does the claim provide an inventive concept, i.e., does the claim recite additional element(s) or a combination of elements that amount to significantly more than the judicial exception in the claim?
Applicant’s claims contain the following “additional elements”:
(1) stored in memory/one or more storage devices
(2) processors
(3) A “training”/“training the content classifier using both the results received from a PII detection module and the second portion of the document”
(4) A content classifier
(5) A document
(6) A content management system
(7) Receiving, over a network and at a content management server of a content management system, a plurality of documents from respective network interfaces of a plurality of user devices
(8) limiting, by a limiter component in the content management system, access to the respective documents in the labeled dataset of the content management system by respective user devices of the plurality of user devices based on at least the one or more labels applied to either the individual ones of the respective documents as a whole or to specific portions thereof by the content classifier
(1) A “memory” is a broad term which is described at a high level. Applicant’s Specification recites:
[00103] The term "computer readable medium" or "computer usable medium" as used herein refers to any medium that participates in providing instructions to data processor 707 for execution. Such a medium may take many forms including, but not limited to, non-volatile media and volatile media. Non-volatile media includes, for example, optical or magnetic disks such as disk drives or tape drives. Volatile media includes dynamic memory such as RAM.
[00104] Common forms of computer readable media include, for example, floppy disk, flexible disk, hard disk, magnetic tape, or any other magnetic medium; CD-ROM or any other optical medium; punch cards, paper tape, or any other physical medium with patterns of holes; RAM, PROM, EPROM, FLASH-EPROM, or any other memory chip or cartridge, or any other non- transitory computer readable medium. Such data can be stored, for example, in any form of external data repository 731, which in turn can be formatted into any one or more storage areas, and which can comprise parameterized storage 739 accessible by a key (e.g., filename, table name, block address, offset address, etc.)
Therefore, the claim as a whole does not amount to significantly more than the exception itself (i.e., there is no inventive concept in the claim) (See, M.P.E.P. § 2106.05(II))
(2) A “processor” is a broad term which is described at a high level. Applicant’s Specification recites:
[0098] FIG. 7A depicts a block diagram of an instance of a computer system 7A00 suitable for implementing embodiments of the present disclosure. Computer system 7A00 includes a bus 706 or other communication mechanism for communicating information. The bus interconnects subsystems and devices such as a central processing unit (CPU), or a multi-core CPU (e.g., data processor 707), a system memory (e.g., main memory 708, or an area of random access memory (RAM)), a non- volatile storage device or non-volatile storage area (e.g., read-only memory 709), an internal storage device 710 or external storage device 713 (e.g., magnetic or optical), a data interface 733, a communications interface 714 (e.g., PHY, MAC, Ethernet interface, modem, etc.) The aforementioned components are shown within processing element partition 701, however other partitions are possible. Computer system 7A00 further comprises a display 711 (e.g., CRT or LCD), various input devices 712 (e.g., keyboard, cursor control), and an external data repository 731.
Therefore, the claim as a whole does not amount to significantly more than the exception itself (i.e., there is no inventive concept in the claim) (See, M.P.E.P. § 2106.05(II))
(3) A “training”/“training the content classifier using both the results received from a PII detection module and the second portion of the document” is a broad term which is described at a high level. Applicant’s Specification recites:
[0083] The figure depicts one possible implementation of step 204 (FIG. 2) This implementation takes as inputs (1) a labeled dataset 222 and (2) a PII detection rulebase 117, and produces adjusted weights (e.g., weight type1 and weight type2) The error correction module 408 receives two incoming values from two conditionally-independent sets of inputs (e.g., the vector processor value and the rule processor value, as shown), compares them to an error calculation, and then adjusts the weights to reduce the error. The weight adjustment method could be a gradient descent algorithm employing, for example, one or more of several back-propagation methods. In one example implementation of back-propagation, the vector processor 404 is a feed forward deep neural network and adjustments are computed by (1) differentiating the loss function for each input in each layer of the network, and (2) iteratively choosing a weight adjustment that would reduce the error by a precalculated maximum amount and then (3) applying the adjustment. The iterations are repeated until the overall error (e.g., as measured by a loss function) reaches an acceptable value, and/or when no more weight adjustment improvements are possible. In this specific example, the back- propagation algorithm analyzes labels that are generated by the rule based module 117, which can potentially produce noisy label outputs. However, due to the mathematic lemmas that arise as a result of choosing two conditionally independent sets of inputs, back-propagation will converge, resulting in a classifier that is as good (e.g., in terms of precision and recall) as a classifier that had been trained on non-noisy (e.g., perfectly accurate) labels.
Note that, according to the Specification, the claimed “training” could be any one of the many generic gradient descent algorithms. It is unspecified. Note further that the Specification recites:
[00102] In some embodiments, hard-wired circuitry may be used in place of or in combination with software instructions to implement aspects of the disclosure. Thus, embodiments of the disclosure are not limited to any specific combination of hardware circuitry and/or software. In embodiments, the term "logic" shall mean any combination of software or hardware that is used to implement all or part of the disclosure.
Therefore, the claim as a whole does not amount to significantly more than the exception itself (i.e., there is no inventive concept in the claim) (See, M.P.E.P. § 2106.05(II))
(4) A “content classifier” is a broad term which is described at a high level. Applicant’s Specification recites:
[0083] The figure depicts one possible implementation of step 204 (FIG. 2) This implementation takes as inputs (1) a labeled dataset 222 and (2) a PII detection rulebase 117, and produces adjusted weights (e.g., weight type1 and weight type2) The error correction module 408 receives two incoming values from two conditionally-independent sets of inputs (e.g., the vector processor value and the rule processor value, as shown), compares them to an error calculation, and then adjusts the weights to reduce the error. The weight adjustment method could be a gradient descent algorithm employing, for example, one or more of several back-propagation methods. In one example implementation of back-propagation, the vector processor 404 is a feed forward deep neural network and adjustments are computed by (1) differentiating the loss function for each input in each layer of the network, and (2) iteratively choosing a weight adjustment that would reduce the error by a precalculated maximum amount and then (3) applying the adjustment. The iterations are repeated until the overall error (e.g., as measured by a loss function) reaches an acceptable value, and/or when no more weight adjustment improvements are possible. In this specific example, the back- propagation algorithm analyzes labels that are generated by the rule based module 117, which can potentially produce noisy label outputs. However, due to the mathematic lemmas that arise as a result of choosing two conditionally independent sets of inputs, back-propagation will converge, resulting in a classifier that is as good (e.g., in terms of precision and recall) as a classifier that had been trained on non-noisy (e.g., perfectly accurate) labels.
Note that, according to the Specification, the claimed “content classifier” could be any one of the many generic vector processor algorithms. It is unspecified. Note further that the Specification recites:
[00102] In some embodiments, hard-wired circuitry may be used in place of or in combination with software instructions to implement aspects of the disclosure. Thus, embodiments of the disclosure are not limited to any specific combination of hardware circuitry and/or software. In embodiments, the term "logic" shall mean any combination of software or hardware that is used to implement all or part of the disclosure.
Therefore, the claim as a whole does not amount to significantly more than the exception itself (i.e., there is no inventive concept in the claim) (See, M.P.E.P. § 2106.05(II))
(5) A “document” is a broad term which is described at a high level. M.P.E.P. § 2106.05(d)(II) recites:
The courts have recognized the following computer functions as well‐understood, routine, and conventional functions when they are claimed in a merely generic manner (e.g., at a high level of generality) or as insignificant extra-solution activity.
***
iii. Electronic recordkeeping, Alice Corp. Pty. Ltd. v. CLS Bank Int'l, 573 U.S. 208, 225, 110 USPQ2d 1984 (2014) (creating and maintaining “shadow accounts”); Ultramercial, 772 F.3d at 716, 112 USPQ2d at 1755 (updating an activity log);
Therefore, the claim as a whole does not amount to significantly more than the exception itself (i.e., there is no inventive concept in the claim) (See, M.P.E.P. § 2106.05(II))
(6) A “content management system” is a broad term which is described at a high level. The term “content management system” is Applicant's name for the overall claimed invention. See, body of independent claims and FIG. 5, box 104 (no patentable weight given to data input). Applicant essentially argues that the claimed invention must be eligible because it is itself.
Applicant's assertion that it reduces document processing operations, reduces false positives, and training the classifier are simply nonfunctional descriptions of what it already does (except for the training, which was discussed above.)
Therefore, the claim as a whole does not amount to significantly more than the exception itself (i.e., there is no inventive concept in the claim) (See, M.P.E.P. § 2106.05(II))
(7) A “receiving, over a network and at a content management server of a content management system, a plurality of documents from respective network interfaces of a plurality of user devices” is a broad term which is described at a high level. M.P.E.P. § 2106.05 (f)(2) recites in part:
(2) Whether the claim invokes computers or other machinery merely as a tool to perform an existing process. Use of a computer or other machinery in its ordinary capacity for economic or other tasks (e.g., to receive, store, or transmit data) or simply adding a general purpose computer or computer components after the fact to an abstract idea (e.g., a fundamental economic practice or mathematical equation) does not integrate a judicial exception into a practical application or provide significantly more. See Affinity Labs v. DirecTV, 838 F.3d 1253, 1262, 120 USPQ2d 1201, 1207 (Fed. Cir. 2016) (cellular telephone); TLI Communications LLC v. AV Auto, LLC, 823 F.3d 607, 613, 118 USPQ2d 1744, 1748 (Fed. Cir. 2016) (computer server and telephone unit). Similarly, “claiming the improved speed or efficiency inherent with applying the abstract idea on a computer” does not integrate a judicial exception into a practical application or provide an inventive concept. Intellectual Ventures I LLC v. Capital One Bank (USA), 792 F.3d 1363, 1367, 115 USPQ2d 1636, 1639 (Fed. Cir. 2015). In contrast, a claim that purports to improve computer capabilities or to improve an existing technology may integrate a judicial exception into a practical application or provide significantly more. McRO, Inc. v. Bandai Namco Games Am. Inc., 837 F.3d 1299, 1314-15, 120 USPQ2d 1091, 1101-02 (Fed. Cir. 2016); Enfish, LLC v. Microsoft Corp., 822 F.3d 1327, 1335-36, 118 USPQ2d 1684, 1688-89 (Fed. Cir. 2016). See MPEP §§ 2106.04(d)(1) and 2106.05(a) for a discussion of improvements to the functioning of a computer or to another technology or technical field.
TLI Communications provides an example of a claim invoking computers and other machinery merely as a tool to perform an existing process. The court stated that the claims describe steps of recording, administration and archiving of digital images, and found them to be directed to the abstract idea of classifying and storing digital images in an organized manner. 823 F.3d at 612, 118 USPQ2d at 1747. The court then turned to the additional elements of performing these functions using a telephone unit and a server and noted that these elements were being used in their ordinary capacity (i.e., the telephone unit is used to make calls and operate as a digital camera including compressing images and transmitting those images, and the server simply receives data, extracts classification information from the received data, and stores the digital images based on the extracted information). 823 F.3d at 612-13, 118 USPQ2d at 1747-48. In other words, the claims invoked the telephone unit and server merely as tools to execute the abstract idea. Thus, the court found that the additional elements did not add significantly more to the abstract idea because they were simply applying the abstract idea on a telephone network without any recitation of details of how to carry out the abstract idea.
This “receiving, over a network and at a content management server of a content management system, a plurality of documents from respective network interfaces of a plurality of user devices” limitation does not integrate the additional element into a practical application and represents “insignificant extra-solution activity”. (See, M.P.E.P. § 2106.05(I)(A)).
(8) A “limiting, by a limiter component in the content management system, access to the respective documents in the labeled dataset of the content management system by respective user devices of the plurality of user devices based on at least the one or more labels applied to either the individual ones of the respective documents as a whole or to specific portions thereof by the content classifier” is a broad term which is described at a high level. Applicant's Specification recites:
[00110] FIG. 7B depicts a block diagram of an instance of a cloud-based environment 7B00. Such a cloud-based environment supports access to workspaces through the execution of workspace access code (e.g., workspace access code 7420, workspace access code 7421, and workspace access code 7422). Workspace access code can be executed on any of access devices 752 (e.g., laptop device 7524, workstation device 7525, IP phone device 7523, tablet device 7522, smart phone device 7521, etc.), and can be configured to access any type of object. Strictly as examples, such objects can be folders or directories or can be files of any filetype. The files or folders or directories can be organized into any hierarchy. Any type of object can comprise or be associated with access permissions. The access permissions in turn may correspond to different actions to be taken over the object. Strictly as one example, a first permission (e.g., PREVIEWONLY) may be associated with a first action (e.g., preview), while a second permission (e.g., READ) may be associated with a second action (e.g., download), etc. Furthermore, permissions may be associated to any particular user or any particular group of users.
Further, M.P.E.P. § 2106.05 (f)(2) recites in part:
(2) Whether the claim invokes computers or other machinery merely as a tool to perform an existing process. Use of a computer or other machinery in its ordinary capacity for economic or other tasks (e.g., to receive, store, or transmit data) or simply adding a general purpose computer or computer components after the fact to an abstract idea (e.g., a fundamental economic practice or mathematical equation) does not integrate a judicial exception into a practical application or provide significantly more. See Affinity Labs v. DirecTV, 838 F.3d 1253, 1262, 120 USPQ2d 1201, 1207 (Fed. Cir. 2016) (cellular telephone); TLI Communications LLC v. AV Auto, LLC, 823 F.3d 607, 613, 118 USPQ2d 1744, 1748 (Fed. Cir. 2016) (computer server and telephone unit). Similarly, “claiming the improved speed or efficiency inherent with applying the abstract idea on a computer” does not integrate a judicial exception into a practical application or provide an inventive concept. Intellectual Ventures I LLC v. Capital One Bank (USA), 792 F.3d 1363, 1367, 115 USPQ2d 1636, 1639 (Fed. Cir. 2015). In contrast, a claim that purports to improve computer capabilities or to improve an existing technology may integrate a judicial exception into a practical application or provide significantly more. McRO, Inc. v. Bandai Namco Games Am. Inc., 837 F.3d 1299, 1314-15, 120 USPQ2d 1091, 1101-02 (Fed. Cir. 2016); Enfish, LLC v. Microsoft Corp., 822 F.3d 1327, 1335-36, 118 USPQ2d 1684, 1688-89 (Fed. Cir. 2016). See MPEP §§ 2106.04(d)(1) and 2106.05(a) for a discussion of improvements to the functioning of a computer or to another technology or technical field.
TLI Communications provides an example of a claim invoking computers and other machinery merely as a tool to perform an existing process. The court stated that the claims describe steps of recording, administration and archiving of digital images, and found them to be directed to the abstract idea of classifying and storing digital images in an organized manner. 823 F.3d at 612, 118 USPQ2d at 1747. The court then turned to the additional elements of performing these functions using a telephone unit and a server and noted that these elements were being used in their ordinary capacity (i.e., the telephone unit is used to make calls and operate as a digital camera including compressing images and transmitting those images, and the server simply receives data, extracts classification information from the received data, and stores the digital images based on the extracted information). 823 F.3d at 612-13, 118 USPQ2d at 1747-48. In other words, the claims invoked the telephone unit and server merely as tools to execute the abstract idea. Thus, the court found that the additional elements did not add significantly more to the abstract idea because they were simply applying the abstract idea on a telephone network without any recitation of details of how to carry out the abstract idea.
Therefore, the option to limit access permissions is a standard feature of any server in a cloud-based environment.
This “limiting, by a limiter component in the content management system, access to the respective documents in the labeled dataset of the content management system by respective user devices of the plurality of user devices based on at least the one or more labels applied to either the individual ones of the respective documents as a whole or to specific portions thereof by the content classifier” limitation does not integrate the additional element into a practical application and represents “insignificant extra-solution activity”. (See, M.P.E.P. § 2106.05(I)(A)).
Therefore, the answer to the inquiry is “NO”, no additional elements provide an inventive concept that is significantly more than the claimed abstract ideas the claimed abstract idea into a practical application.
Claim 8 is, therefore, NOT ELIGIBLE subject matter under 35 U.S.C. § 101.
Claim 9
Claim 9 recites:
The non-transitory computer readable medium of claim 8, further comprising instructions which, when stored in memory and executed by the one or more processors causes the one or more processors to perform acts of: identifying a selected portion of a subject content object and applying the selected portion to the content classifier to determine whether characteristics of the selected portion are indicative that the document does contain PII.
Applicant’s Claim 9 merely teaches identification and application of data. It does not integrate the abstract idea to a practical application, nor is it anything significantly more than the abstract idea. (See, 2106.05(a)(II))
Claim 9 is, therefore, NOT ELIGIBLE subject matter under 35 U.S.C. § 101.
Claim 10
Claim 10 recites:
The non-transitory computer readable medium of claim 9, further comprising instructions which, when stored in memory and executed by the one or more processors causes the one or more processors to perform acts of: communicating a message to a user device, wherein the message comprises at least a portion of one or more governance restrictions pertaining to communication of personally identifiable information.
Applicant’s Claim 10 merely teaches communication of data (i.e., a pure signal) It does not integrate the abstract idea to a practical application, nor is it anything significantly more than the abstract idea. (See, 2106.05(a)(II))
Claim 10 is, therefore, NOT ELIGIBLE subject matter under 35 U.S.C. § 101.
Claim 11
Claim 11 recites:
The non-transitory computer readable medium of claim 8, wherein application of the PII rule to the first portion of the document is used to identify at least one of, one or more infotype designations, one or more infotype locations, or one or more infotype hotwords.
Applicant’s Claim 11 merely teaches identification of data. It does not integrate the abstract idea to a practical application, nor is it anything significantly more than the abstract idea. (See, 2106.05(a)(II))
Claim 11 is, therefore, NOT ELIGIBLE subject matter under 35 U.S.C. § 101.
Claim 12
Claim 12 recites:
The non-transitory computer readable medium of claim 11, wherein the second portion of the document selected from the unlabeled dataset does not contain any occurrence of the one or more infotype hotwords.
Applicant’s Claim 12 merely teaches missing data. It does not integrate the abstract idea to a practical application, nor is it anything significantly more than the abstract idea. (See, 2106.05(a)(II))
Claim 12 is, therefore, NOT ELIGIBLE subject matter under 35 U.S.C. § 101.
Claim 13
Claim 13 recites:
The non-transitory computer readable medium of claim 8, further comprising instructions which, when stored in memory and executed by the one or more processors causes the one or more processors to perform acts of: adjusting a weight of either the likelihood value or the confidence value based on a gradient descent algorithm.
Applicant’s Claim 13 merely teaches adjusting of weights (i.e., pure numbers) It does not integrate the abstract idea to a practical application, nor is it anything significantly more than the abstract idea. (See, 2106.05(a)(II))
Claim 13 is, therefore, NOT ELIGIBLE subject matter under 35 U.S.C. § 101.
Claim 14
Claim 14 recites:
The non-transitory computer readable medium of claim 8, further comprising instructions which, when stored in memory and executed by the one or more processors causes the one or more processors to perform acts of: adjusting a weight of either the likelihood value or the confidence value based on an error calculation that compares a vector processor value to a rule processor value.
Applicant’s Claim 14 merely teaches adjusting of weights (i.e., pure numbers) It does not integrate the abstract idea to a practical application, nor is it anything significantly more than the abstract idea. (See, 2106.05(a)(II))
Claim 14 is, therefore, NOT ELIGIBLE subject matter under 35 U.S.C. § 101.
Claim 15
Step 1 inquiry: Does this claim fall within a statutory category?
The preamble of the claim recites “15. A system comprising…” Therefore, it is a “system” (or “apparatus”), which is a statutory category of invention. Therefore, the answer to the inquiry is: “YES”.
Step 2A (Prong One) inquiry:
Are there limitations in Claim 15 that recite abstract ideas?
YES. The following limitations in Claim 15 recite abstract ideas that fall within at least one of the groupings of abstract ideas enumerated in the 2019 PEG. Specifically, they are “mental steps”:
• an unlabeled dataset
• a labeled data set
• a plurality of documents
• personally identifiable information (PII)
• determining, based on results received from a PII detection module that applies applying a PII rule stored in the rulebase comprising the plurality of rules for detecting PII to a first portion of a document selected from the unlabeled dataset
• a PII rule
• a rulebase comprising the plurality of rules for detecting PII
• results received from a PII detection module
• a first portion of a document
• a confidence value
• selecting
• second portion of the document
• associating
• a likelihood value
Step 2A (Prong Two) inquiry:
Are there additional elements or a combination of elements in the claim that apply, rely on, or use the judicial exception in a manner that imposes a meaningful limit on the judicial exception, such that it is more than a drafting effort designed to monopolize the exception?
Applicant’s claims contain the following “additional elements”:
(1) stored in memory/one or more storage devices
(2) processors
(3) A “training”/“training the content classifier using both the results received from a PII detection module and the second portion of the document”
(4) A content classifier
(5) A document
(6) A content management system
(7) Receiving, over a network and at a content management server of a content management system, a plurality of documents from respective network interfaces of a plurality of user devices
(8) limiting, by a limiter component in the content management system, access to the respective documents in the labeled dataset of the content management system by respective user devices of the plurality of user devices based on at least the one or more labels applied to either the individual ones of the respective documents as a whole or to specific portions thereof by the content classifier
(1) A “memory/one or more storage devices” is a broad term which is described at a high level. Applicant’s Specification recites:
[00103] The term "computer readable medium" or "computer usable medium" as used herein refers to any medium that participates in providing instructions to data processor 707 for execution. Such a medium may take many forms including, but not limited to, non-volatile media and volatile media. Non-volatile media includes, for example, optical or magnetic disks such as disk drives or tape drives. Volatile media includes dynamic memory such as RAM.
[00104] Common forms of computer readable media include, for example, floppy disk, flexible disk, hard disk, magnetic tape, or any other magnetic medium; CD-ROM or any other optical medium; punch cards, paper tape, or any other physical medium with patterns of holes; RAM, PROM, EPROM, FLASH-EPROM, or any other memory chip or cartridge, or any other non- transitory computer readable medium. Such data can be stored, for example, in any form of external data repository 731, which in turn can be formatted into any one or more storage areas, and which can comprise parameterized storage 739 accessible by a key (e.g., filename, table name, block address, offset address, etc.)
This “memory/one or more storage devices” limitation does not integrate the additional element into a practical application and represents “insignificant extra-solution activity”. (See, M.P.E.P. § 2106.05(I)(A))
(2) A “processor” is a broad term which is described at a high level. Applicant’s Specification recites:
[0098] FIG. 7A depicts a block diagram of an instance of a computer system 7A00 suitable for implementing embodiments of the present disclosure. Computer system 7A00 includes a bus 706 or other communication mechanism for communicating information. The bus interconnects subsystems and devices such as a central processing unit (CPU), or a multi-core CPU (e.g., data processor 707), a system memory (e.g., main memory 708, or an area of random access memory (RAM)), a non- volatile storage device or non-volatile storage area (e.g., read-only memory 709), an internal storage device 710 or external storage device 713 (e.g., magnetic or optical), a data interface 733, a communications interface 714 (e.g., PHY, MAC, Ethernet interface, modem, etc.) The aforementioned components are shown within processing element partition 701, however other partitions are possible. Computer system 7A00 further comprises a display 711 (e.g., CRT or LCD), various input devices 712 (e.g., keyboard, cursor control), and an external data repository 731.
This “processor” limitation does not integrate the additional element into a practical application and represents “insignificant extra-solution activity”. (See, M.P.E.P. § 2106.05(I)(A))
(3) A “training”/“training the content classifier using both the results received from a PII detection module and the second portion of the document” is a broad term which is described at a high level. Applicant’s Specification recites:
[0083] The figure depicts one possible implementation of step 204 (FIG. 2) This implementation takes as inputs (1) a labeled dataset 222 and (2) a PII detection rulebase 117, and produces adjusted weights (e.g., weight type1 and weight type2) The error correction module 408 receives two incoming values from two conditionally-independent sets of inputs (e.g., the vector processor value and the rule processor value, as shown), compares them to an error calculation, and then adjusts the weights to reduce the error. The weight adjustment method could be a gradient descent algorithm employing, for example, one or more of several back-propagation methods. In one example implementation of back-propagation, the vector processor 404 is a feed forward deep neural network and adjustments are computed by (1) differentiating the loss function for each input in each layer of the network, and (2) iteratively choosing a weight adjustment that would reduce the error by a precalculated maximum amount and then (3) applying the adjustment. The iterations are repeated until the overall error (e.g., as measured by a loss function) reaches an acceptable value, and/or when no more weight adjustment improvements are possible. In this specific example, the back- propagation algorithm analyzes labels that are generated by the rule based module 117, which can potentially produce noisy label outputs. However, due to the mathematic lemmas that arise as a result of choosing two conditionally independent sets of inputs, back-propagation will converge, resulting in a classifier that is as good (e.g., in terms of precision and recall) as a classifier that had been trained on non-noisy (e.g., perfectly accurate) labels.
Note that, according to the Specification, the claimed “training” could be any one of the many generic gradient descent algorithms. It is unspecified. Note further that the Specification recites:
[00102] In some embodiments, hard-wired circuitry may be used in place of or in combination with software instructions to implement aspects of the disclosure. Thus, embodiments of the disclosure are not limited to any specific combination of hardware circuitry and/or software. In embodiments, the term "logic" shall mean any combination of software or hardware that is used to implement all or part of the disclosure.
This “training”/“training the content classifier using both the results received from a PII detection module and the second portion of the document” limitation does not integrate the additional element into a practical application and represents “insignificant extra-solution activity”. (See, M.P.E.P. § 2106.05(I)(A))
(4) A “content classifier” is a broad term which is described at a high level. Applicant’s Specification recites:
[0083] The figure depicts one possible implementation of step 204 (FIG. 2) This implementation takes as inputs (1) a labeled dataset 222 and (2) a PII detection rulebase 117, and produces adjusted weights (e.g., weight type1 and weight type2) The error correction module 408 receives two incoming values from two conditionally-independent sets of inputs (e.g., the vector processor value and the rule processor value, as shown), compares them to an error calculation, and then adjusts the weights to reduce the error. The weight adjustment method could be a gradient descent algorithm employing, for example, one or more of several back-propagation methods. In one example implementation of back-propagation, the vector processor 404 is a feed forward deep neural network and adjustments are computed by (1) differentiating the loss function for each input in each layer of the network, and (2) iteratively choosing a weight adjustment that would reduce the error by a precalculated maximum amount and then (3) applying the adjustment. The iterations are repeated until the overall error (e.g., as measured by a loss function) reaches an acceptable value, and/or when no more weight adjustment improvements are possible. In this specific example, the back- propagation algorithm analyzes labels that are generated by the rule based module 117, which can potentially produce noisy label outputs. However, due to the mathematic lemmas that arise as a result of choosing two conditionally independent sets of inputs, back-propagation will converge, resulting in a classifier that is as good (e.g., in terms of precision and recall) as a classifier that had been trained on non-noisy (e.g., perfectly accurate) labels.
Note that, according to the Specification, the claimed “content classifier” could be any one of the many generic vector processor algorithms. It is unspecified. Note further that the Specification recites:
[00102] In some embodiments, hard-wired circuitry may be used in place of or in combination with software instructions to implement aspects of the disclosure. Thus, embodiments of the disclosure are not limited to any specific combination of hardware circuitry and/or software. In embodiments, the term "logic" shall mean any combination of software or hardware that is used to implement all or part of the disclosure.
This “content classifier” limitation does not integrate the additional element into a practical application and represents “insignificant extra-solution activity”. (See, M.P.E.P. § 2106.05(I)(A))
(5) A “document” is a broad term which is described at a high level. M.P.E.P. § 2106.05(d)(II) recites:
The courts have recognized the following computer functions as well‐understood, routine, and conventional functions when they are claimed in a merely generic manner (e.g., at a high level of generality) or as insignificant extra-solution activity.
***
iii. Electronic recordkeeping, Alice Corp. Pty. Ltd. v. CLS Bank Int'l, 573 U.S. 208, 225, 110 USPQ2d 1984 (2014) (creating and maintaining “shadow accounts”); Ultramercial, 772 F.3d at 716, 112 USPQ2d at 1755 (updating an activity log);
This “document” limitation does not integrate the additional element into a practical application and represents “insignificant extra-solution activity”. (See, M.P.E.P. § 2106.05(I)(A)).
(6) A “content management system” is a broad term which is described at a high level. The term “content management system” is Applicant's name for the overall claimed invention. See, body of independent claims and FIG. 5, box 104 (no patentable weight given to data input). Applicant essentially argues that the claimed invention must be eligible because it is itself.
Applicant's assertion that it reduces document processing operations, reduces false positives, and training the classifier are simply nonfunctional descriptions of what it already does (except for the training, which was discussed above.)
This “content management system” limitation does not integrate the additional element into a practical application and represents “insignificant extra-solution activity”. (See, M.P.E.P. § 2106.05(I)(A)).
(7) A “receiving, over a network and at a content management server of a content management system, a plurality of documents from respective network interfaces of a plurality of user devices” is a broad term which is described at a high level. M.P.E.P. § 2106.05 (f)(2) recites in part:
(2) Whether the claim invokes computers or other machinery merely as a tool to perform an existing process. Use of a computer or other machinery in its ordinary capacity for economic or other tasks (e.g., to receive, store, or transmit data) or simply adding a general purpose computer or computer components after the fact to an abstract idea (e.g., a fundamental economic practice or mathematical equation) does not integrate a judicial exception into a practical application or provide significantly more. See Affinity Labs v. DirecTV, 838 F.3d 1253, 1262, 120 USPQ2d 1201, 1207 (Fed. Cir. 2016) (cellular telephone); TLI Communications LLC v. AV Auto, LLC, 823 F.3d 607, 613, 118 USPQ2d 1744, 1748 (Fed. Cir. 2016) (computer server and telephone unit). Similarly, “claiming the improved speed or efficiency inherent with applying the abstract idea on a computer” does not integrate a judicial exception into a practical application or provide an inventive concept. Intellectual Ventures I LLC v. Capital One Bank (USA), 792 F.3d 1363, 1367, 115 USPQ2d 1636, 1639 (Fed. Cir. 2015). In contrast, a claim that purports to improve computer capabilities or to improve an existing technology may integrate a judicial exception into a practical application or provide significantly more. McRO, Inc. v. Bandai Namco Games Am. Inc., 837 F.3d 1299, 1314-15, 120 USPQ2d 1091, 1101-02 (Fed. Cir. 2016); Enfish, LLC v. Microsoft Corp., 822 F.3d 1327, 1335-36, 118 USPQ2d 1684, 1688-89 (Fed. Cir. 2016). See MPEP §§ 2106.04(d)(1) and 2106.05(a) for a discussion of improvements to the functioning of a computer or to another technology or technical field.
TLI Communications provides an example of a claim invoking computers and other machinery merely as a tool to perform an existing process. The court stated that the claims describe steps of recording, administration and archiving of digital images, and found them to be directed to the abstract idea of classifying and storing digital images in an organized manner. 823 F.3d at 612, 118 USPQ2d at 1747. The court then turned to the additional elements of performing these functions using a telephone unit and a server and noted that these elements were being used in their ordinary capacity (i.e., the telephone unit is used to make calls and operate as a digital camera including compressing images and transmitting those images, and the server simply receives data, extracts classification information from the received data, and stores the digital images based on the extracted information). 823 F.3d at 612-13, 118 USPQ2d at 1747-48. In other words, the claims invoked the telephone unit and server merely as tools to execute the abstract idea. Thus, the court found that the additional elements did not add significantly more to the abstract idea because they were simply applying the abstract idea on a telephone network without any recitation of details of how to carry out the abstract idea.
This “receiving, over a network and at a content management server of a content management system, a plurality of documents from respective network interfaces of a plurality of user devices” limitation does not integrate the additional element into a practical application and represents “insignificant extra-solution activity”. (See, M.P.E.P. § 2106.05(I)(A)).
(8) A “limiting, by a limiter component in the content management system, access to the respective documents in the labeled dataset of the content management system by respective user devices of the plurality of user devices based on at least the one or more labels applied to either the individual ones of the respective documents as a whole or to specific portions thereof by the content classifier” is a broad term which is described at a high level. Applicant's Specification recites:
[00110] FIG. 7B depicts a block diagram of an instance of a cloud-based environment 7B00. Such a cloud-based environment supports access to workspaces through the execution of workspace access code (e.g., workspace access code 7420, workspace access code 7421, and workspace access code 7422). Workspace access code can be executed on any of access devices 752 (e.g., laptop device 7524, workstation device 7525, IP phone device 7523, tablet device 7522, smart phone device 7521, etc.), and can be configured to access any type of object. Strictly as examples, such objects can be folders or directories or can be files of any filetype. The files or folders or directories can be organized into any hierarchy. Any type of object can comprise or be associated with access permissions. The access permissions in turn may correspond to different actions to be taken over the object. Strictly as one example, a first permission (e.g., PREVIEWONLY) may be associated with a first action (e.g., preview), while a second permission (e.g., READ) may be associated with a second action (e.g., download), etc. Furthermore, permissions may be associated to any particular user or any particular group of users.
Further, M.P.E.P. § 2106.05 (f)(2) recites in part:
(2) Whether the claim invokes computers or other machinery merely as a tool to perform an existing process. Use of a computer or other machinery in its ordinary capacity for economic or other tasks (e.g., to receive, store, or transmit data) or simply adding a general purpose computer or computer components after the fact to an abstract idea (e.g., a fundamental economic practice or mathematical equation) does not integrate a judicial exception into a practical application or provide significantly more. See Affinity Labs v. DirecTV, 838 F.3d 1253, 1262, 120 USPQ2d 1201, 1207 (Fed. Cir. 2016) (cellular telephone); TLI Communications LLC v. AV Auto, LLC, 823 F.3d 607, 613, 118 USPQ2d 1744, 1748 (Fed. Cir. 2016) (computer server and telephone unit). Similarly, “claiming the improved speed or efficiency inherent with applying the abstract idea on a computer” does not integrate a judicial exception into a practical application or provide an inventive concept. Intellectual Ventures I LLC v. Capital One Bank (USA), 792 F.3d 1363, 1367, 115 USPQ2d 1636, 1639 (Fed. Cir. 2015). In contrast, a claim that purports to improve computer capabilities or to improve an existing technology may integrate a judicial exception into a practical application or provide significantly more. McRO, Inc. v. Bandai Namco Games Am. Inc., 837 F.3d 1299, 1314-15, 120 USPQ2d 1091, 1101-02 (Fed. Cir. 2016); Enfish, LLC v. Microsoft Corp., 822 F.3d 1327, 1335-36, 118 USPQ2d 1684, 1688-89 (Fed. Cir. 2016). See MPEP §§ 2106.04(d)(1) and 2106.05(a) for a discussion of improvements to the functioning of a computer or to another technology or technical field.
TLI Communications provides an example of a claim invoking computers and other machinery merely as a tool to perform an existing process. The court stated that the claims describe steps of recording, administration and archiving of digital images, and found them to be directed to the abstract idea of classifying and storing digital images in an organized manner. 823 F.3d at 612, 118 USPQ2d at 1747. The court then turned to the additional elements of performing these functions using a telephone unit and a server and noted that these elements were being used in their ordinary capacity (i.e., the telephone unit is used to make calls and operate as a digital camera including compressing images and transmitting those images, and the server simply receives data, extracts classification information from the received data, and stores the digital images based on the extracted information). 823 F.3d at 612-13, 118 USPQ2d at 1747-48. In other words, the claims invoked the telephone unit and server merely as tools to execute the abstract idea. Thus, the court found that the additional elements did not add significantly more to the abstract idea because they were simply applying the abstract idea on a telephone network without any recitation of details of how to carry out the abstract idea.
Therefore, the option to limit access permissions is a standard feature of any server in a cloud-based environment.
This “limiting, by a limiter component in the content management system, access to the respective documents in the labeled dataset of the content management system by respective user devices of the plurality of user devices based on at least the one or more labels applied to either the individual ones of the respective documents as a whole or to specific portions thereof by the content classifier” limitation does not integrate the additional element into a practical application and represents “insignificant extra-solution activity”. (See, M.P.E.P. § 2106.05(I)(A)).
The answer to the inquiry is “NO”, no additional elements integrate the claimed abstract idea into a practical application.
Step 2B inquiry:
Does the claim provide an inventive concept, i.e., does the claim recite additional element(s) or a combination of elements that amount to significantly more than the judicial exception in the claim?
Applicant’s claims contain the following “additional elements”:
(1) stored in memory/one or more storage devices
(2) processors
(3) A “training”/“training the content classifier using both the results received from a PII detection module and the second portion of the document”
(4) A content classifier
(5) A document
(6) A content management system
(7) Receiving, over a network and at a content management server of a content management system, a plurality of documents from respective network interfaces of a plurality of user devices
(8) limiting, by a limiter component in the content management system, access to the respective documents in the labeled dataset of the content management system by respective user devices of the plurality of user devices based on at least the one or more labels applied to either the individual ones of the respective documents as a whole or to specific portions thereof by the content classifier
(1) A “memory” is a broad term which is described at a high level. Applicant’s Specification recites:
[00103] The term "computer readable medium" or "computer usable medium" as used herein refers to any medium that participates in providing instructions to data processor 707 for execution. Such a medium may take many forms including, but not limited to, non-volatile media and volatile media. Non-volatile media includes, for example, optical or magnetic disks such as disk drives or tape drives. Volatile media includes dynamic memory such as RAM.
[00104] Common forms of computer readable media include, for example, floppy disk, flexible disk, hard disk, magnetic tape, or any other magnetic medium; CD-ROM or any other optical medium; punch cards, paper tape, or any other physical medium with patterns of holes; RAM, PROM, EPROM, FLASH-EPROM, or any other memory chip or cartridge, or any other non- transitory computer readable medium. Such data can be stored, for example, in any form of external data repository 731, which in turn can be formatted into any one or more storage areas, and which can comprise parameterized storage 739 accessible by a key (e.g., filename, table name, block address, offset address, etc.)
Therefore, the claim as a whole does not amount to significantly more than the exception itself (i.e., there is no inventive concept in the claim) (See, M.P.E.P. § 2106.05(II))
(2) A “processor” is a broad term which is described at a high level. Applicant’s Specification recites:
[0098] FIG. 7A depicts a block diagram of an instance of a computer system 7A00 suitable for implementing embodiments of the present disclosure. Computer system 7A00 includes a bus 706 or other communication mechanism for communicating information. The bus interconnects subsystems and devices such as a central processing unit (CPU), or a multi-core CPU (e.g., data processor 707), a system memory (e.g., main memory 708, or an area of random access memory (RAM)), a non- volatile storage device or non-volatile storage area (e.g., read-only memory 709), an internal storage device 710 or external storage device 713 (e.g., magnetic or optical), a data interface 733, a communications interface 714 (e.g., PHY, MAC, Ethernet interface, modem, etc.) The aforementioned components are shown within processing element partition 701, however other partitions are possible. Computer system 7A00 further comprises a display 711 (e.g., CRT or LCD), various input devices 712 (e.g., keyboard, cursor control), and an external data repository 731.
Therefore, the claim as a whole does not amount to significantly more than the exception itself (i.e., there is no inventive concept in the claim) (See, M.P.E.P. § 2106.05(II))
(3) A “training”/“training the content classifier using both the results received from a PII detection module and the second portion of the document” is a broad term which is described at a high level. Applicant’s Specification recites:
[0083] The figure depicts one possible implementation of step 204 (FIG. 2) This implementation takes as inputs (1) a labeled dataset 222 and (2) a PII detection rulebase 117, and produces adjusted weights (e.g., weight type1 and weight type2) The error correction module 408 receives two incoming values from two conditionally-independent sets of inputs (e.g., the vector processor value and the rule processor value, as shown), compares them to an error calculation, and then adjusts the weights to reduce the error. The weight adjustment method could be a gradient descent algorithm employing, for example, one or more of several back-propagation methods. In one example implementation of back-propagation, the vector processor 404 is a feed forward deep neural network and adjustments are computed by (1) differentiating the loss function for each input in each layer of the network, and (2) iteratively choosing a weight adjustment that would reduce the error by a precalculated maximum amount and then (3) applying the adjustment. The iterations are repeated until the overall error (e.g., as measured by a loss function) reaches an acceptable value, and/or when no more weight adjustment improvements are possible. In this specific example, the back- propagation algorithm analyzes labels that are generated by the rule based module 117, which can potentially produce noisy label outputs. However, due to the mathematic lemmas that arise as a result of choosing two conditionally independent sets of inputs, back-propagation will converge, resulting in a classifier that is as good (e.g., in terms of precision and recall) as a classifier that had been trained on non-noisy (e.g., perfectly accurate) labels.
Note that, according to the Specification, the claimed “training” could be any one of the many generic gradient descent algorithms. It is unspecified. Note further that the Specification recites:
[00102] In some embodiments, hard-wired circuitry may be used in place of or in combination with software instructions to implement aspects of the disclosure. Thus, embodiments of the disclosure are not limited to any specific combination of hardware circuitry and/or software. In embodiments, the term "logic" shall mean any combination of software or hardware that is used to implement all or part of the disclosure.
Therefore, the claim as a whole does not amount to significantly more than the exception itself (i.e., there is no inventive concept in the claim) (See, M.P.E.P. § 2106.05(II))
(4) A “content classifier” is a broad term which is described at a high level. Applicant’s Specification recites:
[0083] The figure depicts one possible implementation of step 204 (FIG. 2) This implementation takes as inputs (1) a labeled dataset 222 and (2) a PII detection rulebase 117, and produces adjusted weights (e.g., weight type1 and weight type2) The error correction module 408 receives two incoming values from two conditionally-independent sets of inputs (e.g., the vector processor value and the rule processor value, as shown), compares them to an error calculation, and then adjusts the weights to reduce the error. The weight adjustment method could be a gradient descent algorithm employing, for example, one or more of several back-propagation methods. In one example implementation of back-propagation, the vector processor 404 is a feed forward deep neural network and adjustments are computed by (1) differentiating the loss function for each input in each layer of the network, and (2) iteratively choosing a weight adjustment that would reduce the error by a precalculated maximum amount and then (3) applying the adjustment. The iterations are repeated until the overall error (e.g., as measured by a loss function) reaches an acceptable value, and/or when no more weight adjustment improvements are possible. In this specific example, the back- propagation algorithm analyzes labels that are generated by the rule based module 117, which can potentially produce noisy label outputs. However, due to the mathematic lemmas that arise as a result of choosing two conditionally independent sets of inputs, back-propagation will converge, resulting in a classifier that is as good (e.g., in terms of precision and recall) as a classifier that had been trained on non-noisy (e.g., perfectly accurate) labels.
Note that, according to the Specification, the claimed “content classifier” could be any one of the many generic vector processor algorithms. It is unspecified. Note further that the Specification recites:
[00102] In some embodiments, hard-wired circuitry may be used in place of or in combination with software instructions to implement aspects of the disclosure. Thus, embodiments of the disclosure are not limited to any specific combination of hardware circuitry and/or software. In embodiments, the term "logic" shall mean any combination of software or hardware that is used to implement all or part of the disclosure.
Therefore, the claim as a whole does not amount to significantly more than the exception itself (i.e., there is no inventive concept in the claim) (See, M.P.E.P. § 2106.05(II))
(5) A “document” is a broad term which is described at a high level. M.P.E.P. § 2106.05(d)(II) recites:
The courts have recognized the following computer functions as well‐understood, routine, and conventional functions when they are claimed in a merely generic manner (e.g., at a high level of generality) or as insignificant extra-solution activity.
***
iii. Electronic recordkeeping, Alice Corp. Pty. Ltd. v. CLS Bank Int'l, 573 U.S. 208, 225, 110 USPQ2d 1984 (2014) (creating and maintaining “shadow accounts”); Ultramercial, 772 F.3d at 716, 112 USPQ2d at 1755 (updating an activity log);
Therefore, the claim as a whole does not amount to significantly more than the exception itself (i.e., there is no inventive concept in the claim) (See, M.P.E.P. § 2106.05(II))
(6) A “content management system” is a broad term which is described at a high level. The term “content management system” is Applicant's name for the overall claimed invention. See, body of independent claims and FIG. 5, box 104 (no patentable weight given to data input). Applicant essentially argues that the claimed invention must be eligible because it is itself.
Applicant's assertion that it reduces document processing operations, reduces false positives, and training the classifier are simply nonfunctional descriptions of what it already does (except for the training, which was discussed above.)
Therefore, the claim as a whole does not amount to significantly more than the exception itself (i.e., there is no inventive concept in the claim) (See, M.P.E.P. § 2106.05(II))
(5) A “receiving, over a network and at a content management server of a content management system, a plurality of documents from respective network interfaces of a plurality of user devices” is a broad term which is described at a high level. M.P.E.P. § 2106.05 (f)(2) recites in part:
(2) Whether the claim invokes computers or other machinery merely as a tool to perform an existing process. Use of a computer or other machinery in its ordinary capacity for economic or other tasks (e.g., to receive, store, or transmit data) or simply adding a general purpose computer or computer components after the fact to an abstract idea (e.g., a fundamental economic practice or mathematical equation) does not integrate a judicial exception into a practical application or provide significantly more. See Affinity Labs v. DirecTV, 838 F.3d 1253, 1262, 120 USPQ2d 1201, 1207 (Fed. Cir. 2016) (cellular telephone); TLI Communications LLC v. AV Auto, LLC, 823 F.3d 607, 613, 118 USPQ2d 1744, 1748 (Fed. Cir. 2016) (computer server and telephone unit). Similarly, “claiming the improved speed or efficiency inherent with applying the abstract idea on a computer” does not integrate a judicial exception into a practical application or provide an inventive concept. Intellectual Ventures I LLC v. Capital One Bank (USA), 792 F.3d 1363, 1367, 115 USPQ2d 1636, 1639 (Fed. Cir. 2015). In contrast, a claim that purports to improve computer capabilities or to improve an existing technology may integrate a judicial exception into a practical application or provide significantly more. McRO, Inc. v. Bandai Namco Games Am. Inc., 837 F.3d 1299, 1314-15, 120 USPQ2d 1091, 1101-02 (Fed. Cir. 2016); Enfish, LLC v. Microsoft Corp., 822 F.3d 1327, 1335-36, 118 USPQ2d 1684, 1688-89 (Fed. Cir. 2016). See MPEP §§ 2106.04(d)(1) and 2106.05(a) for a discussion of improvements to the functioning of a computer or to another technology or technical field.
TLI Communications provides an example of a claim invoking computers and other machinery merely as a tool to perform an existing process. The court stated that the claims describe steps of recording, administration and archiving of digital images, and found them to be directed to the abstract idea of classifying and storing digital images in an organized manner. 823 F.3d at 612, 118 USPQ2d at 1747. The court then turned to the additional elements of performing these functions using a telephone unit and a server and noted that these elements were being used in their ordinary capacity (i.e., the telephone unit is used to make calls and operate as a digital camera including compressing images and transmitting those images, and the server simply receives data, extracts classification information from the received data, and stores the digital images based on the extracted information). 823 F.3d at 612-13, 118 USPQ2d at 1747-48. In other words, the claims invoked the telephone unit and server merely as tools to execute the abstract idea. Thus, the court found that the additional elements did not add significantly more to the abstract idea because they were simply applying the abstract idea on a telephone network without any recitation of details of how to carry out the abstract idea.
Therefore, the claim as a whole does not amount to significantly more than the exception itself (i.e., there is no inventive concept in the claim) (See, M.P.E.P. § 2106.05(II))
(6) A “limiting, by a limiter component in the content management system, access to the respective documents in the labeled dataset of the content management system by respective user devices of the plurality of user devices based on at least the one or more labels applied to either the individual ones of the respective documents as a whole or to specific portions thereof by the content classifier” is a broad term which is described at a high level. Applicant's Specification recites:
[00110] FIG. 7B depicts a block diagram of an instance of a cloud-based environment 7B00. Such a cloud-based environment supports access to workspaces through the execution of workspace access code (e.g., workspace access code 7420, workspace access code 7421, and workspace access code 7422). Workspace access code can be executed on any of access devices 752 (e.g., laptop device 7524, workstation device 7525, IP phone device 7523, tablet device 7522, smart phone device 7521, etc.), and can be configured to access any type of object. Strictly as examples, such objects can be folders or directories or can be files of any filetype. The files or folders or directories can be organized into any hierarchy. Any type of object can comprise or be associated with access permissions. The access permissions in turn may correspond to different actions to be taken over the object. Strictly as one example, a first permission (e.g., PREVIEWONLY) may be associated with a first action (e.g., preview), while a second permission (e.g., READ) may be associated with a second action (e.g., download), etc. Furthermore, permissions may be associated to any particular user or any particular group of users.
Further, M.P.E.P. § 2106.05 (f)(2) recites in part:
(2) Whether the claim invokes computers or other machinery merely as a tool to perform an existing process. Use of a computer or other machinery in its ordinary capacity for economic or other tasks (e.g., to receive, store, or transmit data) or simply adding a general purpose computer or computer components after the fact to an abstract idea (e.g., a fundamental economic practice or mathematical equation) does not integrate a judicial exception into a practical application or provide significantly more. See Affinity Labs v. DirecTV, 838 F.3d 1253, 1262, 120 USPQ2d 1201, 1207 (Fed. Cir. 2016) (cellular telephone); TLI Communications LLC v. AV Auto, LLC, 823 F.3d 607, 613, 118 USPQ2d 1744, 1748 (Fed. Cir. 2016) (computer server and telephone unit). Similarly, “claiming the improved speed or efficiency inherent with applying the abstract idea on a computer” does not integrate a judicial exception into a practical application or provide an inventive concept. Intellectual Ventures I LLC v. Capital One Bank (USA), 792 F.3d 1363, 1367, 115 USPQ2d 1636, 1639 (Fed. Cir. 2015). In contrast, a claim that purports to improve computer capabilities or to improve an existing technology may integrate a judicial exception into a practical application or provide significantly more. McRO, Inc. v. Bandai Namco Games Am. Inc., 837 F.3d 1299, 1314-15, 120 USPQ2d 1091, 1101-02 (Fed. Cir. 2016); Enfish, LLC v. Microsoft Corp., 822 F.3d 1327, 1335-36, 118 USPQ2d 1684, 1688-89 (Fed. Cir. 2016). See MPEP §§ 2106.04(d)(1) and 2106.05(a) for a discussion of improvements to the functioning of a computer or to another technology or technical field.
TLI Communications provides an example of a claim invoking computers and other machinery merely as a tool to perform an existing process. The court stated that the claims describe steps of recording, administration and archiving of digital images, and found them to be directed to the abstract idea of classifying and storing digital images in an organized manner. 823 F.3d at 612, 118 USPQ2d at 1747. The court then turned to the additional elements of performing these functions using a telephone unit and a server and noted that these elements were being used in their ordinary capacity (i.e., the telephone unit is used to make calls and operate as a digital camera including compressing images and transmitting those images, and the server simply receives data, extracts classification information from the received data, and stores the digital images based on the extracted information). 823 F.3d at 612-13, 118 USPQ2d at 1747-48. In other words, the claims invoked the telephone unit and server merely as tools to execute the abstract idea. Thus, the court found that the additional elements did not add significantly more to the abstract idea because they were simply applying the abstract idea on a telephone network without any recitation of details of how to carry out the abstract idea.
Therefore, the option to limit access permissions is a standard feature of any server in a cloud-based environment.
Therefore, the claim as a whole does not amount to significantly more than the exception itself (i.e., there is no inventive concept in the claim) (See, M.P.E.P. § 2106.05(II))
Therefore, the answer to the inquiry is “NO”, no additional elements provide an inventive concept that is significantly more than the claimed abstract ideas the claimed abstract idea into a practical application.
Claim 15 is, therefore, NOT ELIGIBLE subject matter under 35 U.S.C. § 101.
Claim 16
Claim 16 recites:
The system of claim 15, further comprising: identifying a selected portion of a subject content object and applying the selected portion to the content classifier to determine whether characteristics of the selected portion are indicative that the document does contain PII.
Applicant’s Claim 16 merely teaches identification and application of data. It does not integrate the abstract idea to a practical application, nor is it anything significantly more than the abstract idea. (See, 2106.05(a)(II))
Claim 16 is, therefore, NOT ELIGIBLE subject matter under 35 U.S.C. § 101.
Claim 17
Claim 17 recites:
The system of claim 16, further comprising: communicating a message to a user device, wherein the message comprises at least a portion of one or more governance restrictions pertaining to communication of personally identifiable information.
Applicant’s Claim 17 merely teaches communication of data (i.e., a pure signal) It does not integrate the abstract idea to a practical application, nor is it anything significantly more than the abstract idea. (See, 2106.05(a)(II))
Claim 17 is, therefore, NOT ELIGIBLE subject matter under 35 U.S.C. § 101.
Claim 18
Claim 18 recites:
The system of claim 15, wherein application of the PII rule to the first portion of the document is used to identify at least one of, one or more infotype designations, one or more infotype locations, or one or more infotype hotwords.
Applicant’s Claim 18 merely teaches identification of data. It does not integrate the abstract idea to a practical application, nor is it anything significantly more than the abstract idea. (See, 2106.05(a)(II))
Claim 18 is, therefore, NOT ELIGIBLE subject matter under 35 U.S.C. § 101.
Claim 19
Claim 19 recites:
The system of claim 18, wherein the second portion of the document selected from the unlabeled dataset does not contain any occurrence of the one or more infotype hotwords.
Applicant’s Claim 19 merely teaches missing data. It does not integrate the abstract idea to a practical application, nor is it anything significantly more than the abstract idea. (See, 2106.05(a)(II))
Claim 19 is, therefore, NOT ELIGIBLE subject matter under 35 U.S.C. § 101.
Claim 20
Claim 20 recites:
The system of claim 15, further comprising: adjusting a weight of either the likelihood value or the confidence value based on a gradient descent algorithm.
Applicant’s Claim 20 merely teaches adjusting of weights (i.e., pure numbers) It does not integrate the abstract idea to a practical application, nor is it anything significantly more than the abstract idea. (See, 2106.05(a)(II))
Claim 20 is, therefore, NOT ELIGIBLE subject matter under 35 U.S.C. § 101.
Reasons for not Rejecting the Clams Under Art of Record
Claims 1-20 are not rejected under art.
The following is an Examiner's statement of reasons for allowance: Claims 1-20 are considered allowable since when reading the claims in light of the specification, as per MPEP § 2111.01, none of the references of record, whether taken alone or in combination, discloses or suggests the combination of limitations specified in independent Claim 1. The closest art of Luo, et al., Privacy Preserving Recalibration under Domain Shift, arXiv:2008.09643, 21 AUG 2020, pp. 1-36 fails to expressly teach an association to a likelihood value based on a confidence value. Specifically:
Claim 1's "...associating with the second portion, based on the confidence value, a likelihood value..."
Further, none of the references of record, whether taken alone or in combination, discloses or suggests the combination of limitations specified in independent Claim 8. The closest art of Luo, et al. fails to expressly teach an association to a likelihood value based on a confidence value. Specifically:
Claim 8's "...associating with the second portion, based on the confidence value, a likelihood value..."
Further, none of the references of record, whether taken alone or in combination, discloses or suggests the combination of limitations specified in independent Claim 15. The closest art of Luo, et al. fails to expressly teach an association to a likelihood value based on a confidence value. Specifically:
Claim 15's "...associating with the second portion, based on the confidence value, a likelihood value..."
Only to the extent that these limitations (specifically as defined above) are not found in the prior art of record is the present case not rejected over the prior art.
Response to Arguments
Applicant's arguments filed 02 MAR 2026 have been fully considered but they are not persuasive. Specifically, Applicant argues:
Argument 1
First, the claims are not drawn to an abstract idea. Under Alice, a claim is eligible for patenting either if it is not drawn to an abstract idea or, even if drawn to an abstract idea, if it contains "an element or combination of elements that is 'sufficient to ensure that the patent in practice amounts to significantly more than a patent upon the ineligible concept itself." See Alice Corp. Pty Ltd. V. CLS Bank Int'l, 134 S.Ct. 2347, 2357 (2014).
a. Recent Appeal Decision - Ex parte Desjardins (Appeal No. 2024-000567)
As an initial matter, Applicant would like to bring the follow to the examiner's attention: Ex Parte Desjardins, Appeal No. 2024-000567 (PTAB September 26, 2025, Appeals Review Panel Decision) (precedential as of November 4th 2025). This decision is of particular relevance here as the claims at issue here and in the decision address machine learning improvements which the panel (which includes the director of the USPTO John Squires) found to be subject matter eligible under 35 U.S.C. § 101.
At a minimum, the claims do recite 1) a confidence value and 2) A likelihood value. These are in fact mathematical concepts contained in the claims.
Regarding Desjardins, Note that Applicant’s Specification recites:
[0083] The figure depicts one possible implementation of step 204 (FIG. 2) This implementation takes as inputs (1) a labeled dataset 222 and (2) a PII detection rulebase 117, and produces adjusted weights (e.g., weight type1 and weight type2) The error correction module 408 receives two incoming values from two conditionally-independent sets of inputs (e.g., the vector processor value and the rule processor value, as shown), compares them to an error calculation, and then adjusts the weights to reduce the error. The weight adjustment method could be a gradient descent algorithm employing, for example, one or more of several back-propagation methods. In one example implementation of back-propagation, the vector processor 404 is a feed forward deep neural network and adjustments are computed by (1) differentiating the loss function for each input in each layer of the network, and (2) iteratively choosing a weight adjustment that would reduce the error by a precalculated maximum amount and then (3) applying the adjustment. The iterations are repeated until the overall error (e.g., as measured by a loss function) reaches an acceptable value, and/or when no more weight adjustment improvements are possible. In this specific example, the back-propagation algorithm analyzes labels that are generated by the rule based module 117, which can potentially produce noisy label outputs. However, due to the mathematic lemmas that arise as a result of choosing two conditionally independent sets of inputs, back-propagation will converge, resulting in a classifier that is as good (e.g., in terms of precision and recall) as a classifier that had been trained on non-noisy (e.g., perfectly accurate) labels.
Note that, according to the Specification, the claimed “content classifier” could be any one of the many generic vector processor algorithms. It is unspecified. Note further that the Specification recites:
[00102] In some embodiments, hard-wired circuitry may be used in place of or in combination with software instructions to implement aspects of the disclosure. Thus, embodiments of the disclosure are not limited to any specific combination of hardware circuitry and/or software. In embodiments, the term "logic" shall mean any combination of software or hardware that is used to implement all or part of the disclosure.
Therefore, the machine learning in the claim is generic.
Applicant's argument is unpersuasive.
The rejections stand.
Argument 2
Applicant respectfully assert that the present claims also incorporate improvements to machine learning into the claims at least with regard to the recitation of the content classifier that is trained at least by selecting a second portion of the document selected from the unlabeled dataset of the content management system, that provides the benefit of a reduction of document processing operations associated with production of the labeled dataset from an unlabeled dataset by reducing false positive results for PII in the respective documents of the plurality of documents, and the false positives are reduced at least by training the content classifier using both the results received from a PII detection module and the second portion of the document. See also, Application paragraph [0057]
"to avoid overfitting the model, selecting a second portion of the document (e.g., a second portion that does not include the first portion), In this example, the occurrence of the word "mobile" in the context around the string that was hit by a rule serves to increase the likelihood that the document, or at least the phone number string and/or its context, contains PII. As such, by combining rule-oriented training with context oriented training when constructing a PII classifier, the problem of false positives that occur when using PII rules alone, as well as the problem of false negatives that occur when using PII rules alone, is solved."
Clearly, a reduction in document processing operations uses less storage capacity (e.g., RAM) and reduces the amount of processing required to be performed to generate the labeled dataset from the unlabeled dataset and thus represents claimed "improvements in training the machine learning model" which are subject matter eligible.
Therefore, even if it is argued that the claims are directed to a judicial exception, Applicant respectfully notes that the claims very clearly integrate the claim recitations into a practical application.
As shown for Argument 1, the content classifier is a generic classifier. The use of that classifier in a new data environment does not improve the classifier or any other technology.
Applicant's argument is unpersuasive.
The rejections stand.
Argument 3
The Office Action asserts that the claims fall under the first grouping of mathematical concepts. See Office Action page 2. Applicant respectfully disagrees.
Instead, Applicant respectfully asserts that the current claims do not fall within this category since the claims recite numerous limitations that go far and beyond any per se recitations of math concepts or claims that recite only on their own mathematical concepts. For example, claim 1 as amended includes limitations directed towards a content management system having a content management server that receives documents over a network from a plurality of user devices and enables the plurality oof users to share and modify those documents using the plurality of user devices. Additionally, the content management system includes an unlabeled dataset on one or more storage devices of the content management system in which those documents are stored. Still further, the content management system generates a labeled dataset using an included content classifier that generates labels for those documents in the unlabeled dataset or portions thereof to indicate a detection of a specific type of information, and the content management system also includes a limiter component that limits access to respective documents in the labeled dataset of the content management system by respective user devices of the plurality of user devices based on at least the one or more labels applied to either the individual ones of the respective documents as a whole or to specific portions thereof by the content classifier. Respectfully, such concepts are not mathematical in nature, but are instead directed towards approaches to manage electronically maintained information that is accessing using technological means such as user devices with network interfaces.
As such, Applicant respectfully submits that since the claims do not per se or on their own recite a mathematical equation, formula, or calculation, this means that the claims do not corresponds to an abstract idea as a mathematical concept.
Applicant's independent claims recite: “determining”…a “confidence value.” In its broadest reasonable interpretation, the “confidence value” is a mathematical quantity and the “determination” is a mathematical calculation.
Further, the claims recite “associating” a mathematical “likelihood value” to a “portion” of data. In its broadest reasonable interpretation, the unspecified “association” is a mathematical calculation.
Applicants’ arguments are unpersuasive.
The rejections stand.
Argument 4
Here, the Office Action does not assert that the claim fall under the second grouping of certain methods of organizing human activity. Furthermore, Applicant respectfully asserts that the current claims do not fall within this category since the claims recite numerous limitations that are directly performed by a content management system such as those discussed above in regard to mathematical concepts which is not a human and is not human activity.
Therefore, since the claims do not per se or on their own recite any of the enumerated methods for organizing human activity, Applicant respectfully submits that the claims do not corresponds to an abstract idea as a method of organizing human activity.
Examiner did not reject the claims on the basis of “organizing human activity”. The process of labeling PII is a mental step.
Applicants’ arguments are unpersuasive.
The rejections stand.
Argument 5
The Office Action asserts that the claim fall under the third grouping of mentals steps. See Office Action page 2. Applicant respectfully disagrees.
Instead, Applicant respectfully asserts that the current claims do not fall within this category since the claims recite numerous limitations that not only are expressly performed by a content management system, but cannot be performed in the human mind. For example, claim 1 as amended includes limitations directed towards a content management system having a content management server that receives documents over a network from a plurality of user devices and enables the plurality oof users to share and modify those documents using the plurality of user devices.
Additionally, the content management system includes an unlabeled dataset on one or more storage devices of the content management system in which those documents are stored. Still further, the content management system generates a labeled dataset using an included content classifier that generates labels for those documents in the unlabeled dataset or portions thereof to indicate a detection of a specific type of information, and the content management system also includes a limiter component that limits access to respective documents in the labeled dataset of the content management system by respective user devices of the plurality of user devices based on at least the one or more labels applied to either the individual ones of the respective documents as a whole or to specific portions thereof by the content classifier. Respectfully, such concepts are not mathematical in nature, but are instead directed towards approaches to manage electronically maintained information that is accessing using technological means such as user devices with network interfaces.
Thus, the recited approach discloses concepts that cannot be performed in the human mind and must be performed by the recited content management system having the recited elements identified above.
Based upon the above, Applicant respectfully submits that the claims do not recite matter within the enumerated groupings of abstract ideas, and therefore should not be treated as reciting an abstract idea.
Mental steps are recited in the independent claims. For instance, the process of labeling PII is a mental step. Further, “selecting” a portion of a “document” is also a mental step.
Applicants’ arguments are unpersuasive.
The rejections stand.
Argument 6
Furthermore, the claims integrate any allege abstract idea into a practical application that is patent eligible. See MPEP § 2106. For instance, Limitations the courts have found indicative that an additional element (or combination of elements) may have integrated the exception into a practical application include: An improvement in the functioning of a computer, or an improvement to other technology or technical field, as discussed in MPEP §§ 2106.04(d)(1) and 2106.05(a).
Here, the present approach provides a practical application of limiting access to respective documents that are not labeled as having sensitive information (PII) when received, but are processed by the content management system using a specific arrangement of components to create labels for said documents which can then be subject to access limitations by a limiter component of a content management system.
Therefore, even if it is argued that the claims are directed to a judicial exception (which they are not as discussed above), Applicant respectfully notes that the claims very clearly integrate the claim recitations into a practical application. Without repeating all of the arguments provided above, it is noted that the claims recite the practical application of an approach to produce a labeled dataset from an unlabeled dataset used in training a content classifier which enables a machine learning process that can generate labels for unlabeled documents. Furthermore, as provided in the present application the specific approach recited improves the ability of the content classifier (thus trained) to provide accurate results which is an improvement to the practical application of content classification.
The option to limit access permissions is a standard feature of any server in a cloud-based environment. Applicant's Specification recites:
[00110] FIG. 7B depicts a block diagram of an instance of a cloud-based environment 7B00. Such a cloud-based environment supports access to workspaces through the execution of workspace access code (e.g., workspace access code 7420, workspace access code 7421, and workspace access code 7422). Workspace access code can be executed on any of access devices 752 (e.g., laptop device 7524, workstation device 7525, IP phone device 7523, tablet device 7522, smart phone device 7521, etc.), and can be configured to access any type of object. Strictly as examples, such objects can be folders or directories or can be files of any filetype. The files or folders or directories can be organized into any hierarchy. Any type of object can comprise or be associated with access permissions. The access permissions in turn may correspond to different actions to be taken over the object. Strictly as one example, a first permission (e.g., PREVIEWONLY) may be associated with a first action (e.g., preview), while a second permission (e.g., READ) may be associated with a second action (e.g., download), etc. Furthermore, permissions may be associated to any particular user or any particular group of users.
Further, M.P.E.P. § 2106.05 (f)(2) recites in part:
(2) Whether the claim invokes computers or other machinery merely as a tool to perform an existing process. Use of a computer or other machinery in its ordinary capacity for economic or other tasks (e.g., to receive, store, or transmit data) or simply adding a general purpose computer or computer components after the fact to an abstract idea (e.g., a fundamental economic practice or mathematical equation) does not integrate a judicial exception into a practical application or provide significantly more. See Affinity Labs v. DirecTV, 838 F.3d 1253, 1262, 120 USPQ2d 1201, 1207 (Fed. Cir. 2016) (cellular telephone); TLI Communications LLC v. AV Auto, LLC, 823 F.3d 607, 613, 118 USPQ2d 1744, 1748 (Fed. Cir. 2016) (computer server and telephone unit). Similarly, “claiming the improved speed or efficiency inherent with applying the abstract idea on a computer” does not integrate a judicial exception into a practical application or provide an inventive concept. Intellectual Ventures I LLC v. Capital One Bank (USA), 792 F.3d 1363, 1367, 115 USPQ2d 1636, 1639 (Fed. Cir. 2015). In contrast, a claim that purports to improve computer capabilities or to improve an existing technology may integrate a judicial exception into a practical application or provide significantly more. McRO, Inc. v. Bandai Namco Games Am. Inc., 837 F.3d 1299, 1314-15, 120 USPQ2d 1091, 1101-02 (Fed. Cir. 2016); Enfish, LLC v. Microsoft Corp., 822 F.3d 1327, 1335-36, 118 USPQ2d 1684, 1688-89 (Fed. Cir. 2016). See MPEP §§ 2106.04(d)(1) and 2106.05(a) for a discussion of improvements to the functioning of a computer or to another technology or technical field.
TLI Communications provides an example of a claim invoking computers and other machinery merely as a tool to perform an existing process. The court stated that the claims describe steps of recording, administration and archiving of digital images, and found them to be directed to the abstract idea of classifying and storing digital images in an organized manner. 823 F.3d at 612, 118 USPQ2d at 1747. The court then turned to the additional elements of performing these functions using a telephone unit and a server and noted that these elements were being used in their ordinary capacity (i.e., the telephone unit is used to make calls and operate as a digital camera including compressing images and transmitting those images, and the server simply receives data, extracts classification information from the received data, and stores the digital images based on the extracted information). 823 F.3d at 612-13, 118 USPQ2d at 1747-48. In other words, the claims invoked the telephone unit and server merely as tools to execute the abstract idea. Thus, the court found that the additional elements did not add significantly more to the abstract idea because they were simply applying the abstract idea on a telephone network without any recitation of details of how to carry out the abstract idea.
Therefore, the option to limit access permissions is a standard feature of any server in a cloud-based environment.
Applicants’ arguments are unpersuasive.
The rejections stand.
Argument 7
Here, as was the case in DDR Holdings, the present application addresses a challenge particular to the technology (e.g., how to classify documents in content management system). Applicant disagrees with the Office Action's contention that the claims are directed to an abstract idea. Rather, the claims are directed to a technological problem of labeling an unlabeled dataset and for training a content classifier. This is a challenge that is particular to the technology, and cannot be considered an abstract idea.
The argued “labeling an unlabeled dataset” is a mental step.
Applicants’ arguments are unpersuasive.
The rejections stand.
Argument 8
Additionally, The claims do not merely recite functions that may be performed mentally, but rather impart a specific set of computer-implemented steps to manage unlabeled documents within a content management system, which is a challenge that is particular to technology, as was the case in DDR Holdings.
This specific approach is clearly not directed to an abstract idea, nor any of the delineated excluded categories such as "[f]undamental economic practices; certain methods of organizing human activities; an idea itself; and Mathematical relationships/formulas". Thus, Applicant respectfully avers that the claims are not directed to an abstract idea.
The argued “labeling an unlabeled dataset” is a mental step.
Applicants’ arguments are unpersuasive.
The rejections stand.
Argument 9
The claims are not abstract because they provide a specific implementation of a solution to a problem in the software arts as interpreted under Enfish LLC.
***
Like the claims at issue in Enfish, the claims of the instant patent application are non- abstract since they recite an improvement to the functioning of a computer by providing a specific implementation of an improved way for a content management system to manage documents that may contain PII.
Here, the improvement is directed towards a software issue that arises in the realm of machine learning on unstructured data. Specifically, merely training a content classifier on unlabeled data is likely to result in inaccurate results. The present claims provide for an approach that operates on unlabeled data to generate labels that are associated with documents as a whole or specific portions thereof. Additionally, portions of one document that is associated with a label are used in conjunction with other non-overlapping portions to train the content classifier. This approach avoids at least some of the issues associated with content classifiers by for instance avoiding overfit of the model to a labeled training dataset.
An improvement to the training data is not an improvement to the classifier.
Applicants’ arguments are unpersuasive.
The rejections stand.
Argument 10
Additionally, the claims recite a specific arrangement of “logical structures and processes” to implement the approach that includes limitations directed towards a content management system having a content management server that receives documents over a network from a plurality of user devices and enables the plurality oof users to share and modify those documents using the plurality of user devices.
Applicant's Specification recites:
[00102] In some embodiments, hard-wired circuitry may be used in place of or in combination with software instructions to implement aspects of the disclosure. Thus, embodiments of the disclosure are not limited to any specific combination of hardware circuitry and/or software. In embodiments, the term "logic" shall mean any combination of software or hardware that is used to implement all or part of the disclosure.
In the broadest reasonable interpretation of the term, the limitation of “logic” is “software, per se.”
Applicants’ arguments are unpersuasive.
The rejections stand.
Argument 11
Additionally, the content management system includes an unlabeled dataset on one or more storage devices of the content management system in which those documents are stored.
In the broadest reasonable interpretation of the “storage device” limitations, any portion of the generic server’s RAM serves these purposes. No changes/improvements to the generic server or storage devices are required.
Applicants’ arguments are unpersuasive.
The rejections stand.
Argument 12
Still further, the content management system generates a labeled dataset using an included content classifier that generates labels for those documents in the unlabeled dataset or portions thereof to indicate a detection of a specific type of information, and the content management system also includes a limiter component that limits access to respective documents in the labeled dataset of the content management system by respective user devices of the plurality of user devices based on at least the one or more labels applied to either the individual ones of the respective documents as a whole or to specific portions thereof by the content classifier. Respectfully, such concepts are not mathematical in nature, but are instead directed towards approaches to manage electronically maintained information that is accessing using technological means such as user devices with network interfaces.
Therefore, like the case in Enfish, the pending claims are directed towards a solution to a software problem. Since the pending claims offer a technological solution to a problem in at least software, Appellant submits that the pending claims cannot be considered abstract.
Thus, Appellant respectfully asserts that the claims are not directed towards an abstract idea and are subject matter eligible.
The argued “labeling an unlabeled dataset” is a mental step.
Further, the option to limit access permissions is a standard feature of any server in a cloud-based environment. Applicant's Specification recites:
[00110] FIG. 7B depicts a block diagram of an instance of a cloud-based environment 7B00. Such a cloud-based environment supports access to workspaces through the execution of workspace access code (e.g., workspace access code 7420, workspace access code 7421, and workspace access code 7422). Workspace access code can be executed on any of access devices 752 (e.g., laptop device 7524, workstation device 7525, IP phone device 7523, tablet device 7522, smart phone device 7521, etc.), and can be configured to access any type of object. Strictly as examples, such objects can be folders or directories or can be files of any filetype. The files or folders or directories can be organized into any hierarchy. Any type of object can comprise or be associated with access permissions. The access permissions in turn may correspond to different actions to be taken over the object. Strictly as one example, a first permission (e.g., PREVIEWONLY) may be associated with a first action (e.g., preview), while a second permission (e.g., READ) may be associated with a second action (e.g., download), etc. Furthermore, permissions may be associated to any particular user or any particular group of users.
Further, M.P.E.P. § 2106.05 (f)(2) recites in part:
(2) Whether the claim invokes computers or other machinery merely as a tool to perform an existing process. Use of a computer or other machinery in its ordinary capacity for economic or other tasks (e.g., to receive, store, or transmit data) or simply adding a general purpose computer or computer components after the fact to an abstract idea (e.g., a fundamental economic practice or mathematical equation) does not integrate a judicial exception into a practical application or provide significantly more. See Affinity Labs v. DirecTV, 838 F.3d 1253, 1262, 120 USPQ2d 1201, 1207 (Fed. Cir. 2016) (cellular telephone); TLI Communications LLC v. AV Auto, LLC, 823 F.3d 607, 613, 118 USPQ2d 1744, 1748 (Fed. Cir. 2016) (computer server and telephone unit). Similarly, “claiming the improved speed or efficiency inherent with applying the abstract idea on a computer” does not integrate a judicial exception into a practical application or provide an inventive concept. Intellectual Ventures I LLC v. Capital One Bank (USA), 792 F.3d 1363, 1367, 115 USPQ2d 1636, 1639 (Fed. Cir. 2015). In contrast, a claim that purports to improve computer capabilities or to improve an existing technology may integrate a judicial exception into a practical application or provide significantly more. McRO, Inc. v. Bandai Namco Games Am. Inc., 837 F.3d 1299, 1314-15, 120 USPQ2d 1091, 1101-02 (Fed. Cir. 2016); Enfish, LLC v. Microsoft Corp., 822 F.3d 1327, 1335-36, 118 USPQ2d 1684, 1688-89 (Fed. Cir. 2016). See MPEP §§ 2106.04(d)(1) and 2106.05(a) for a discussion of improvements to the functioning of a computer or to another technology or technical field.
TLI Communications provides an example of a claim invoking computers and other machinery merely as a tool to perform an existing process. The court stated that the claims describe steps of recording, administration and archiving of digital images, and found them to be directed to the abstract idea of classifying and storing digital images in an organized manner. 823 F.3d at 612, 118 USPQ2d at 1747. The court then turned to the additional elements of performing these functions using a telephone unit and a server and noted that these elements were being used in their ordinary capacity (i.e., the telephone unit is used to make calls and operate as a digital camera including compressing images and transmitting those images, and the server simply receives data, extracts classification information from the received data, and stores the digital images based on the extracted information). 823 F.3d at 612-13, 118 USPQ2d at 1747-48. In other words, the claims invoked the telephone unit and server merely as tools to execute the abstract idea. Thus, the court found that the additional elements did not add significantly more to the abstract idea because they were simply applying the abstract idea on a telephone network without any recitation of details of how to carry out the abstract idea.
Therefore, the option to limit access permissions is a standard feature of any server in a cloud-based environment.
Applicants’ arguments are unpersuasive.
The rejections stand.
Argument 13
e. The claims contain an "inventive concept" and thus is not rendered ineligible under Digitech
The claims contain an "inventive concept" apart from any alleged abstract idea. The Supreme Court has explicitly stated that an invention is not rendered ineligible for a patent simply because it involves an abstract concept. Id. at 2354; see also Digitech Image Technologies, LLC V. Electronics for Imaging, Inc. 2014 U.S. App. LEXIS 13149 at 12 (Fed. Cir. 2014) (In determining whether a process claim recites an abstract idea, we must examine the claim as a whole, keeping in mind that an invention is not ineligible just because it relies upon a law of nature or mathematical algorithm.). Claims 1-20 are directed to at least an approach to provide for an improved approach to generating a labeled dataset from an unlabeled data set using a content classifier that is trained in a particular way.
This is true whether the claim elements are "reviewed individually and 'as an ordered combination" See Alice at 7.
An improvement to the training data is not an improvement to the classifier.
Applicants’ arguments are unpersuasive.
The rejections stand.
Argument 14
Like the claims at issue in Bascom, the independent claims, when taken as an ordered combination of claim limitations transform the alleged abstract idea into a particular practical application of the alleged abstract idea. Specifically, the claims provide an approach to identify and limit access to documents that are received which may contain unlabeled occurrences of PII.
The option to limit access permissions is a standard feature of any server in a cloud-based environment. Applicant's Specification recites:
[00110] FIG. 7B depicts a block diagram of an instance of a cloud-based environment 7B00. Such a cloud-based environment supports access to workspaces through the execution of workspace access code (e.g., workspace access code 7420, workspace access code 7421, and workspace access code 7422). Workspace access code can be executed on any of access devices 752 (e.g., laptop device 7524, workstation device 7525, IP phone device 7523, tablet device 7522, smart phone device 7521, etc.), and can be configured to access any type of object. Strictly as examples, such objects can be folders or directories or can be files of any filetype. The files or folders or directories can be organized into any hierarchy. Any type of object can comprise or be associated with access permissions. The access permissions in turn may correspond to different actions to be taken over the object. Strictly as one example, a first permission (e.g., PREVIEWONLY) may be associated with a first action (e.g., preview), while a second permission (e.g., READ) may be associated with a second action (e.g., download), etc. Furthermore, permissions may be associated to any particular user or any particular group of users.
Further, M.P.E.P. § 2106.05 (f)(2) recites in part:
(2) Whether the claim invokes computers or other machinery merely as a tool to perform an existing process. Use of a computer or other machinery in its ordinary capacity for economic or other tasks (e.g., to receive, store, or transmit data) or simply adding a general purpose computer or computer components after the fact to an abstract idea (e.g., a fundamental economic practice or mathematical equation) does not integrate a judicial exception into a practical application or provide significantly more. See Affinity Labs v. DirecTV, 838 F.3d 1253, 1262, 120 USPQ2d 1201, 1207 (Fed. Cir. 2016) (cellular telephone); TLI Communications LLC v. AV Auto, LLC, 823 F.3d 607, 613, 118 USPQ2d 1744, 1748 (Fed. Cir. 2016) (computer server and telephone unit). Similarly, “claiming the improved speed or efficiency inherent with applying the abstract idea on a computer” does not integrate a judicial exception into a practical application or provide an inventive concept. Intellectual Ventures I LLC v. Capital One Bank (USA), 792 F.3d 1363, 1367, 115 USPQ2d 1636, 1639 (Fed. Cir. 2015). In contrast, a claim that purports to improve computer capabilities or to improve an existing technology may integrate a judicial exception into a practical application or provide significantly more. McRO, Inc. v. Bandai Namco Games Am. Inc., 837 F.3d 1299, 1314-15, 120 USPQ2d 1091, 1101-02 (Fed. Cir. 2016); Enfish, LLC v. Microsoft Corp., 822 F.3d 1327, 1335-36, 118 USPQ2d 1684, 1688-89 (Fed. Cir. 2016). See MPEP §§ 2106.04(d)(1) and 2106.05(a) for a discussion of improvements to the functioning of a computer or to another technology or technical field.
TLI Communications provides an example of a claim invoking computers and other machinery merely as a tool to perform an existing process. The court stated that the claims describe steps of recording, administration and archiving of digital images, and found them to be directed to the abstract idea of classifying and storing digital images in an organized manner. 823 F.3d at 612, 118 USPQ2d at 1747. The court then turned to the additional elements of performing these functions using a telephone unit and a server and noted that these elements were being used in their ordinary capacity (i.e., the telephone unit is used to make calls and operate as a digital camera including compressing images and transmitting those images, and the server simply receives data, extracts classification information from the received data, and stores the digital images based on the extracted information). 823 F.3d at 612-13, 118 USPQ2d at 1747-48. In other words, the claims invoked the telephone unit and server merely as tools to execute the abstract idea. Thus, the court found that the additional elements did not add significantly more to the abstract idea because they were simply applying the abstract idea on a telephone network without any recitation of details of how to carry out the abstract idea.
Therefore, the option to limit access permissions is a standard feature of any server in a cloud-based environment.
Applicants’ arguments are unpersuasive.
The rejections stand.
Argument 15
Here that specific approach leverages a plurality of elements that interact to implement the practical application. For example, claim 1 as amended includes limitations directed towards a content management system having a content management server that receives documents over a network from a plurality of user devices and enables the plurality oof users to share and modify those documents using the plurality of user devices. Additionally, the content management system includes an unlabeled dataset on one or more storage devices of the content management system in which those documents are stored. Still further, the content management system generates a labeled dataset using an included content classifier that generates labels for those documents in the unlabeled dataset or portions thereof to indicate a detection of a specific type of information, and the content management system also includes a limiter component that limits access to respective documents in the labeled dataset of the content management system by respective user devices of the plurality of user devices based on at least the one or more labels applied to either the individual ones of the respective documents as a whole or to specific portions thereof by the content classifier. Respectfully, such concepts are not mathematical in nature, but are instead directed towards approaches to manage electronically maintained information that is accessing using technological means such as user devices with network interfaces.
Therefore, like the claims in Bascom, the pending claims recited at least an ordered combination of claim limitations that transform the allegedly abstract idea into a practical application.
Thus, Appellant respectfully asserts that the claims are not directed towards an abstract idea and are subject matter eligible.
For the above reasons, reconsideration and withdrawal of the rejections of claims 1-20 under 35 U.S.C. § 101 is respectfully requested.
Applicant lists claim limitations that were addressed in the rejection of the claims. Please see the rejections for the details.
Applicants’ arguments are unpersuasive.
The rejections stand.
Argument 16
Consequently, for at least the reasons given above, it is respectfully submitted that the independent claims 1, 8, and 15, and their dependent claims are allowable.
Regarding the other independent claims, similar arguments for similar claims are similarly unpersuasive.
Regarding the dependent claims, Applicants’ arguments regarding the independent claims were unpersuasive. Therefore, there is no eligible matter that may be incorporated by reference to the dependent claims.
Applicants’ arguments are unpersuasive.
The rejections stand.
Conclusion
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/WILBERT L STARKS/
Primary Examiner, Art Unit 2122
WLS
05 JUN 2026
Prosecution Insights