DETAILED ACTION
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 .
Remarks
This action is in response to the amendments received on 9/4/26. Claims 1-3 and 6-15 are pending in the application. Claims 4 and 5 have been cancelled. Applicants arguments have been respectfully considered.
Claims 1-3 and 6-15 are rejected under 35 U.S.C. 112.
Claims 1-3 and 6-15 are rejected under 35 U.S.C. 101.
Claims 1-3 and 6-15 are rejected under 35 U.S.C. 103 as being unpatentable over Edwards et al. (US 2025/0173603), and further in view of Subramanian et al. (US 2015/0356057).
Claim Interpretation
The following is a quotation of 35 U.S.C. 112(f):
(f) Element in Claim for a Combination. – An element in a claim for a combination may be expressed as a means or step for performing a specified function without the recital of structure, material, or acts in support thereof, and such claim shall be construed to cover the corresponding structure, material, or acts described in the specification and equivalents thereof.
The following is a quotation of pre-AIA 35 U.S.C. 112, sixth paragraph:
An element in a claim for a combination may be expressed as a means or step for performing a specified function without the recital of structure, material, or acts in support thereof, and such claim shall be construed to cover the corresponding structure, material, or acts described in the specification and equivalents thereof.
Claims 10-15 in this application are given their broadest reasonable interpretation using the plain meaning of the claim language in light of the specification as it would be understood by one of ordinary skill in the art. The broadest reasonable interpretation of a claim element (also commonly referred to as a claim limitation) is limited by the description in the specification when 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, is invoked.
As explained in MPEP § 2181, subsection I, claim limitations that meet the following three-prong test will be interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph:
(A) the claim limitation uses the term “means” or “step” or a term used as a substitute for “means” that is a generic placeholder (also called a nonce term or a non-structural term having no specific structural meaning) for performing the claimed function;
(B) the term “means” or “step” or the generic placeholder is modified by functional language, typically, but not always linked by the transition word “for” (e.g., “means for”) or another linking word or phrase, such as “configured to” or “so that”; and
(C) the term “means” or “step” or the generic placeholder is not modified by sufficient structure, material, or acts for performing the claimed function.
Use of the word “means” (or “step”) in a claim with functional language creates a rebuttable presumption that the claim limitation is to be treated in accordance with 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph. The presumption that the claim limitation is interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, is rebutted when the claim limitation recites sufficient structure, material, or acts to entirely perform the recited function.
Absence of the word “means” (or “step”) in a claim creates a rebuttable presumption that the claim limitation is not to be treated in accordance with 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph. The presumption that the claim limitation is not interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, is rebutted when the claim limitation recites function without reciting sufficient structure, material or acts to entirely perform the recited function.
Claim limitations in this application that use the word “means” (or “step”) are being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, except as otherwise indicated in an Office action. Conversely, claim limitations in this application that do not use the word “means” (or “step”) are not being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, except as otherwise indicated in an Office action.
This application includes one or more claim limitations that do not use the word “means,” but are nonetheless being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, because the claim limitation(s) uses a generic placeholder that is coupled with functional language without reciting sufficient structure to perform the recited function and the generic placeholder is not preceded by a structural modifier. Such claim limitation(s) is/are: “a populate module configured to generate,” “a mapper module configured to: (i) receive… and (ii) automatically map,” and “a store module configured to automatically save” in claim 10.
Because these claim limitation(s) are being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, they are being interpreted to cover the corresponding structure described in the specification as performing the claimed function, and equivalents thereof.
If applicant does not intend to have these limitation(s) interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, applicant may: (1) amend the claim limitation(s) to avoid them being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph (e.g., by reciting sufficient structure to perform the claimed function); or (2) present a sufficient showing that the claim limitation(s) recite(s) sufficient structure to perform the claimed function so as to avoid it/them being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph.
Claim Rejections - 35 USC § 112
The following is a quotation of 35 U.S.C. 112(b):
(b) CONCLUSION.—The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the inventor or a joint inventor regards as the invention.
The following is a quotation of 35 U.S.C. 112 (pre-AIA ), second paragraph:
The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the applicant regards as his invention.
Claims 1-3 and 6-15 are rejected under 35 U.S.C. 112(b) or 35 U.S.C. 112 (pre-AIA ), second paragraph, as being indefinite for failing to particularly point out and distinctly claim the subject matter which the inventor or a joint inventor (or for applications subject to pre-AIA 35 U.S.C. 112, the applicant), regards as the invention.
Claim 10 recites the limitation "the datapoints to be mapped" in the “populate module” limitation. There is insufficient antecedent basis for this limitation in the claim. The claim discloses “a list of one or more datapoints to be mapped” however, "the datapoints to be mapped" is plural, requiring more than one datapoint. Therefore, it is unclear if this is meant to refer to a new set of datapoints or the claimed “list of one or more datapoints.”
With respect to claims 10-15, claim limitations “a populate module configured to generate,” “a mapper module configured to: (i) receive… and (ii) automatically map,” and “a store module configured to automatically save” invoke 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph. However, the written description fails to disclose the corresponding structure, material, or acts for performing the entire claimed function and to clearly link the structure, material, or acts to the function.
There is insufficient disclosure of the corresponding structure, material, or acts for performing the entire claimed function. Aside from the claim language itself, the specification discloses “the populate, mapper, and compute modules described herein can function independently of the data platform. The modules can connect to any data source (from any business area), enable creation of mappings, compute newly mapped results, and store results and lookup into a target data store.” Pa 0020. The disclosure is devoid of any structure that performs the function in the claim.
Therefore, the claim is indefinite and is rejected under 35 U.S.C. 112(b) or pre-AIA 35 U.S.C. 112, second paragraph.
Applicant may:
(a) Amend the claim so that the claim limitation will no longer be interpreted as a limitation under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph;
(b) Amend the written description of the specification such that it expressly recites what structure, material, or acts perform the entire claimed function, without introducing any new matter (35 U.S.C. 132(a)); or
(c) Amend the written description of the specification such that it clearly links the structure, material, or acts disclosed therein to the function recited in the claim, without introducing any new matter (35 U.S.C. 132(a)).
If applicant is of the opinion that the written description of the specification already implicitly or inherently discloses the corresponding structure, material, or acts and clearly links them to the function so that one of ordinary skill in the art would recognize what structure, material, or acts perform the claimed function, applicant should clarify the record by either:
(a) Amending the written description of the specification such that it expressly recites the corresponding structure, material, or acts for performing the claimed function and clearly links or associates the structure, material, or acts to the claimed function, without introducing any new matter (35 U.S.C. 132(a)); or
(b) Stating on the record what the corresponding structure, material, or acts, which are implicitly or inherently set forth in the written description of the specification, perform the claimed function. For more information, see 37 CFR 1.75(d) and MPEP §§ 608.01(o) and 2181.
Claim Rejections - 35 USC § 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 1-3 and 6-15 are rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more.
Step 2A, Prong One asks: Is the claim directed to a law of nature, a natural phenomenon (product of nature) or an abstract idea? See MPEP 2106.04 Part I. If a claim limitation, under its broadest reasonable interpretation, covers performance of the limitation in the mind but for the recitation of generic computer components, then it falls within the “Mental Processes” grouping of abstract ideas. See MPEP 2106.04(a).
With respect to claims 1 and 10, the limitation of “generating, …, a list of one or more datapoints to be mapped” and “a fetch module … wherein the fetch module is code that can access a selected column, extract values from the selected column, and then return a unique list of values by removing redundant values”, as drafted, is a process that, under its broadest reasonable interpretation, covers performance of the limitation in the mind but for the recitation of generic computer components. That is, nothing in the claim element precludes the step from practically being performed in the mind. For example, “generating” in the context of this claim encompasses the user mentally compiling a list. The limitation “automatically mapping, …, one or more additional datapoints”, as drafted, is a process that, under its broadest reasonable interpretation, covers performance of the limitation in the mind but for the recitation of generic computer components. For example, “automatically mapping” in the context of this claim encompasses the user thinking about data. If a claim limitation, under its broadest reasonable interpretation, covers performance of the limitation in the mind but for the recitation of generic computer components, then it falls within the “Mental Processes” grouping of abstract ideas. Accordingly, the claim recites an abstract idea.
At step 2a, prong two, this judicial exception is not integrated into a practical application. Claim 1 recites a data mapping system, however, this is recited as a high-level of generality a generic computer components. Additionally, the claim recites “providing the list of one or more datapoints to be mapped,” “receiving a mapping input,” and “automatically saving the new mapping.” These elements do not integrate the abstract idea into a practical application because they do not impose a meaningful limit on the judicial exception and provide only insignificant extra solution activity that is mere data gathering in conjunction with the abstract idea.
The claims do not include additional elements that are sufficient to amount to significantly more than the judicial exception. As discussed above with respect to integration of the abstract idea into a practical application, the additional elements amount to no more than mere instructions to apply an exception using generic computer components. Mere instructions to apply an exception using generic computer components cannot provide an inventive concept.
With respect to “providing the list of one or more datapoints to be mapped” and “receiving a mapping input”, the courts have found limitations directed towards data gathering to be well-understood, routine, and conventional. See MPEP 2106.05(d)(II). Receiving or transmitting data over a network, e.g., using the Internet to gather data, Symantec, 838 F.3d at 1321, 120 USPQ2d at 1362 (utilizing an intermediary computer to forward information).
With respect to “automatically saving the new mapping”, the courts have found limitations directed towards storing to be well-understood, routine, and conventional. See MPEP 2106.05(d)(II). 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") and “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).
Considering the additional elements individually and in combination and the claim as a whole, the additional elements do not provide significantly more than the abstract idea. The claim is not patent eligible.
With respect to claims 2 and 11, the limitations add “a trained data mapping machine learning system.” This is recited as a high-level of generality a generic computer components. These elements do not integrate the abstract idea into a practical application because they do not impose a meaningful limit on the judicial exception.
With respect to claims 3 and 12, the limitations are directed towards providing and receiving data from a user interface. The courts have found limitations directed towards storing to be well-understood, routine, and conventional. See MPEP 2106.05(d)(II). Presenting offers and gathering statistics, OIP Techs., 788 F.3d at 1362-63, 115 USPQ2d at 1092-93.
With respect to claims 6 and 13, the limitations further define elements discussed above and do not integrate the abstract idea into a practical application.
With respect to claims 7 and 14, “automatically mapping” is a process that, under its broadest reasonable interpretation, covers performance of the limitation in the mind but for the recitation of generic computer components. For example, “automatically mapping” in the context of this claim encompasses the user thinking that the most-used icons should be ranked higher than the least-used icons. Additionally, the claim recites “automatically saving the mapping.” These elements do not integrate the abstract idea into a practical application because they do not impose a meaningful limit on the judicial exception and provide only insignificant extra solution activity that is mere data gathering in conjunction with the abstract idea.
The claims do not include additional elements that are sufficient to amount to significantly more than the judicial exception. As discussed above with respect to integration of the abstract idea into a practical application, the additional elements amount to no more than mere instructions to apply an exception using generic computer components. Mere instructions to apply an exception using generic computer components cannot provide an inventive concept.
With respect to “automatically saving the new mapping”, the courts have found limitations directed towards storing to be well-understood, routine, and conventional. See MPEP 2106.05(d)(II). 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") and “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).
With respect to claims 8 and 15, “a command to update received from the user via the user interface” These elements do not integrate the abstract idea into a practical application because they do not impose a meaningful limit on the judicial exception and provide only insignificant extra solution activity that is mere data gathering in conjunction with the abstract idea. The courts have found limitations directed towards data gathering to be well-understood, routine, and conventional. See MPEP 2106.05(d)(II). Receiving or transmitting data over a network, e.g., using the Internet to gather data, Symantec, 838 F.3d at 1321, 120 USPQ2d at 1362 (utilizing an intermediary computer to forward information).
With respect to claim 9, “further comprising the step of performing, using the mapped datapoints in the results database, analytics” is a process that, under its broadest reasonable interpretation, covers performance of the limitation in the mind but for the recitation of generic computer components. That is, nothing in the claim element precludes the step from practically being performed in the mind. For example, “performing” in the context of this claim encompasses the user manually calculating the amount of use of each icon.
Claim Rejections - 35 USC § 103
The following is a quotation of 35 U.S.C. 103 which forms the basis for all obviousness rejections set forth in this Office action:
A patent for a claimed invention may not be obtained, notwithstanding that the claimed invention is not identically disclosed as set forth in section 102, if the differences between the claimed invention and the prior art are such that the claimed invention as a whole would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to which the claimed invention pertains. Patentability shall not be negated by the manner in which the invention was made.
Claims 1-3 and 6-15 are rejected under 35 U.S.C. 103 as being unpatentable over Edwards et al. (US 2025/0173603), and further in view of Subramanian et al. (US 2015/0356057).
With respect to claim 1, Edwards teaches a method for mapping data using semantic mapping by a data mapping system, comprising:
generating, by the data mapping system by a fetch module from a database of datapoints, a list of one or more datapoints to be mapped (Edwards, pa 0049, the data source may comprise a raw data source (e.g., data source 206). In some embodiments, the raw unlabeled data may be sourced from a commonly accessible data lake., pa 0078, At step 402, process 400 (e.g., using one or more components described above) retrieves a first portion from an unlabeled dataset, & pa 0079, random sampling comprises retrieving a subset (or portion) of individuals from a larger a population (e.g., the unlabeled dataset)), wherein each datapoint in the list of one or more datapoints to be mapped comprises a type of mapping and a data value (Edwards, pa 0078, At step 402, process 400 (e.g., using one or more components described above) retrieves a first portion from an unlabeled dataset … The system may gather raw and unstructured data from various sources. This could be images, text documents, audio recordings, videos, sensor data, etc., pa 0087, At step 404, process 400 (e.g., using one or more components described above) generates a first labeled dataset based on the first portion. For example, the system may generate a first labeled dataset based on the first portion, wherein the first labeled dataset comprises a first plurality of labeled samples, and wherein the first plurality of labeled samples is generated using a first data labeling routine. & pa 0088, each data routine may comprise individually selected data collection (e.g., how data is gathered), labeling guidelines (e.g., clear and detailed guidelines that define how each type of data should be labeled to ensure consistency in the labeling process, making sure that different annotators or labelers interpret and apply labels in the same way), labeler selection (e.g., choosing labelers or annotators who have a good understanding of the labeling guidelines and the domain of the data in addition to whether labelers are human (e.g., human annotators or even crowdsourced workers), models, and/or a mixture thereof), labeling process (e.g., how prescribed labels or annotations to the raw data are applied using tasks such as bounding box annotations, image segmentation, text categorization, sentiment analysis, etc.)), wherein the list of one or more datapoints is saved in a datapoints results table, and wherein the datapoints to be mapped are not yet mapped in the database of datapoints (Edwards, pa 0049, System 200 comprises a data source (e.g., data source 206), …, and wherein the data source comprises unlabeled data sourced from the first data source.);
providing the list of one or more datapoints to be mapped (Edwards, pa 0078, At step 402, process 400 (e.g., using one or more components described above) retrieves a first portion from an unlabeled dataset);
receiving a mapping input comprising a new mapping of one or more of the datapoints, the mapping comprising a new label for a datapoint (Edwards, pa 0087, At step 404, process 400 (e.g., using one or more components described above) generates a first labeled dataset based on the first portion. & pa 0088, the system may use a plurality of data labeling routines. The data labeling routines may each have differing characteristics. For example, each data routine may comprise individually selected … labeler selection (e.g., choosing labelers or annotators who have a good understanding of the labeling guidelines and the domain of the data in addition to whether labelers are human (e.g., human annotators or even crowdsourced workers), models, and/or a mixture thereof));
automatically mapping, by the data mapping system based on the received mapping input, one or more additional datapoints from the database of datapoints (Edwards, pa 0091-0092, At step 410, process 400 (e.g., using one or more components described above) generates a second labeled dataset. For example, the system may generate, using the second data labeling routine, a second labeled dataset based on the second portion, wherein the second labeled dataset comprises a second plurality of labeled samples. (0092] In some embodiments, the second data labeling routine may comprise a model that can automate and assist with data labeling tasks.).
Edwards doesn't expressly discuss automatically saving the new mapping of one or more of the datapoints and the mapped one or more additional datapoints from the database of datapoints in a results database, wherein each mapped datapoint in the results database is associated with a reference to the corresponding unmapped datapoint in the database of datapoints.
Subramanian teaches automatically saving the new mapping of one or more of the datapoints and the mapped one or more additional datapoints from the database of datapoints (Subramanian, pa 0149, Annotations 1220, which may be generated by a NLU engine ( e.g., NLU engine 1020) or a human annotator (e.g., annotator 1030) may include a medical code ( e.g., a medical billing code) for each appropriate portion of the text 1210.) in a results database, wherein each mapped datapoint in the results database is associated with a reference to the corresponding unmapped datapoint in the database of datapoints (Subramanian, pa 0149, The diagnostic code 1222 may be associated with the diagnosis 1212 using a link 1232, and the procedure code 1224 may be associated with the procedure 1214 using a link 1234. The links 1232 and 1234 may be entries in a field of a database table associating annotations 1220 with portions of the text 1210, or they may be pointers or any other suitable data association.).
It would have been obvious at the effective filing date of the invention to a person having ordinary skill in the art to which said subject matter pertains to have modified Edwards with the teachings of Subramanian because it increases the accuracy of annotations (Subramanian, pa 0028).
Edwards in view of Subramanian doesn’t expressly discuss wherein the fetch module is code that can access a selected column, extract values from the selected column, and then return a unique list of values by removing redundant values.
Biswas teaches generating, by the data mapping system by a fetch module from a database of datapoints, a list of one or more datapoints to be mapped, wherein the fetch module is code that can access a selected column, extract values from the selected column, and then return a unique list of values by removing redundant values (Biswas, Col. 32 Li. 18-30, The first data and/or the second data is then cleansed and filtered. The system identifies and recognizes location of the first data based on at least one of a predefined rule, and an input from a user. The input may comprise selecting particular data sets from the data. The second data, and/or the data desired by the user are only left after the cleansing and filtering step. The cleansing and filtering data comprises at least one of removing duplicate data, filtering data by search queries, fix spelling errors, filter incomplete data and aggregate values, etc. The data is also then cataloged to record a directory of information of at least meta data, data sets, files, and database information onto the database.).
It would have been obvious at the effective filing date of the invention to a person having ordinary skill in the art to which said subject matter pertains to have modified Edwards in view of Subramanian with the teachings of Biswas because it removes unwanted data (Biswas, Col. 21 Li. 27-32).
With respect to claim 2, Edwards in view of Subramanian and Biswas teaches the method of claim 1, wherein at least some of the mapping input is generated by a trained data mapping machine learning algorithm (Edwards, pa 0088, the system may use a plurality of data labeling routines. The data labeling routines may each have differing characteristics. For example, each data routine may comprise individually selected … labeler selection (e.g., choosing labelers or annotators who have a good understanding of the labeling guidelines and the domain of the data in addition to whether labelers are human (e.g., human annotators or even crowdsourced workers), models, and/or a mixture thereof)).
With respect to claim 3, Edwards in view of Subramanian and Biswas teaches the method of claim 1, wherein the list of one or more datapoints to be mapped is provided to a user via a user interface of the data mapping system (Subramanian, pa 0124, the CAC system may be configured to provide a user interface via which the automatically suggested codes may be reviewed by a user such as a medical coder.), and wherein the mapping input is received from the user via the user interface (Edwards, pa 0025, Using user interface 150, a data labeler may review one or more labels. For example, user interface 150 may represent a data label that was automatically generated. & Subramanian, pa 0129, Exemplary GUI 700 further allows the user to accept or reject each of the automatically suggested codes).
It would have been obvious at the effective filing date of the invention to a person having ordinary skill in the art to which said subject matter pertains to have further modified Edwards with the teachings of Subramanian because it allows users not familiar with the particular domain to provide appropriate labels (Subramanian, pa 0122-0123).
With respect to claim 6, Edwards in view of Subramanian and Biswas teaches the method of claim 1, wherein each datapoint in the list of one or more datapoints to be mapped is representative of a plurality of datapoints in the database of datapoints (Edwards, pa 0079, random sampling comprises a retrieving a subset (or portion) of individuals from a larger population (e.g., the unlabeled dataset) in a way that each individual has an equal chance of being included in the sample. This process helps ensure that the sample is representative of the larger population, which is important for making valid inferences.).
With respect to claim 7, Edwards in view of Subramanian and Biswas teaches the method of claim 1, further comprising the step of updating the mapping, comprising the steps of:
automatically mapping, by the data mapping system based on the mapping input received from the user, one or more new datapoints from the database of datapoints (Edwards, pa 0089, once the system generates a random sampling, the system may train a model to predict the likely labels for a larger set of data (e.g., the second portion). & pa 0090, At step 408, process 400 ( e.g., using one or more components described above) retrieves a second portion from the unlabeled dataset.); and
automatically saving the mapping of the one or more new datapoints from the database of datapoints in a results database (Subramanian, pa 0149, Annotations 1220, which may be generated by a NLU engine ( e.g., NLU engine 1020) or a human annotator (e.g., annotator 1030) may include a medical code ( e.g., a medical billing code) for each appropriate portion of the text 1210. … The diagnostic code 1222 may be associated with the diagnosis 1212 using a link 1232, and the procedure code 1224 may be associated with the procedure 1214 using a link 1234. The links 1232 and 1234 may be entries in a field of a database table associating annotations 1220 with portions of the text 1210, or they may be pointers or any other suitable data association.).
With respect to claim 8, Edwards in view of Subramanian and Biswas teaches the method of claim 7, wherein the mapping is updated in response to a command to update received from the user via the user interface (Subramanian, pa 0130, GUI 700 may also allow the user to replace a code with a different code).
With respect to claim 9, Edwards in view of Subramanian and Biswas teaches the method of claim 1, further comprising the step of performing, using the mapped datapoints in the results database, analytics (Edwards, pa 0001, Data labeling is a crucial step in the process of creating training datasets for supervised machine learning algorithms. These labels help the algorithms learn patterns and make predictions or classifications based on new, unseen data.).
With respect to claim 10, Edwards teaches a system for mapping data using semantic mapping, comprising:
a database of datapoints (Edwards, pa 0051, The system may query the first data source for the first label, wherein the first data source comprises a plurality of labeled data archives, wherein each of the plurality of labeled data archives is specific to a respective workspace. & pa 0052, the first data source may comprise a relational database service that pushes changes to a specific archive (e.g., corresponding to a given workspace).);
a populate module configured to generate, by a fetch module, from the database of datapoints, a list of one or more datapoints to be mapped (Edwards, pa 0079, random sampling comprises retrieving a subset (or portion) of individuals from a larger a population (e.g., the unlabeled dataset)), , wherein each datapoint in the list of one or more datapoints to be mapped comprises a type of mapping and a data value (Edwards, pa 0078, At step 402, process 400 (e.g., using one or more components described above) retrieves a first portion from an unlabeled dataset … The system may gather raw and unstructured data from various sources. This could be images, text documents, audio recordings, videos, sensor data, etc., pa 0087, At step 404, process 400 (e.g., using one or more components described above) generates a first labeled dataset based on the first portion. For example, the system may generate a first labeled dataset based on the first portion, wherein the first labeled dataset comprises a first plurality of labeled samples, and wherein the first plurality of labeled samples is generated using a first data labeling routine. & pa 0088, each data routine may comprise individually selected data collection (e.g., how data is gathered), labeling guidelines (e.g., clear and detailed guidelines that define how each type of data should be labeled to ensure consistency in the labeling process, making sure that different annotators or labelers interpret and apply labels in the same way), labeler selection (e.g., choosing labelers or annotators who have a good understanding of the labeling guidelines and the domain of the data in addition to whether labelers are human (e.g., human annotators or even crowdsourced workers), models, and/or a mixture thereof), labeling process (e.g., how prescribed labels or annotations to the raw data are applied using tasks such as bounding box annotations, image segmentation, text categorization, sentiment analysis, etc.)), wherein the list of one or more datapoints is saved in a datapoints results table, and wherein the datapoints to be mapped are not yet mapped in the database of datapoints (Edwards, pa 0049, System 200 comprises a data source (e.g., data source 206), …, and wherein the data source comprises unlabeled data sourced from the first data source.);
a mapper module configured to: (i) receive a mapping input comprising a new mapping of one or more of the datapoints, the mapping comprising a new label for a datapoint (Edwards, pa 0087, At step 404, process 400 (e.g., using one or more components described above) generates a first labeled dataset based on the first portion. & pa 0088, the system may use a plurality of data labeling routines. The data labeling routines may each have differing characteristics. For example, each data routine may comprise individually selected … labeler selection (e.g., choosing labelers or annotators who have a good understanding of the labeling guidelines and the domain of the data in addition to whether labelers are human (e.g., human annotators or even crowdsourced workers), models, and/or a mixture thereof)); and (ii) automatically map, based on the received mapping input, one or more additional datapoints from the database of datapoints (Edwards, pa 0091-0092, At step 410, process 400 (e.g., using one or more components described above) generates a second labeled dataset. For example, the system may generate, using the second data labeling routine, a second labeled dataset based on the second portion, wherein the second labeled dataset comprises a second plurality of labeled samples. (0092] In some embodiments, the second data labeling routine may comprise a model that can automate and assist with data labeling tasks.).
Edwards doesn't expressly discuss automatically saving the new mapping of one or more of the datapoints and the mapped one or more additional datapoints from the database of datapoints in a results database, wherein each mapped datapoint in the results database is associated with a reference to the corresponding unmapped datapoint in the database of datapoints.
Subramanian teaches a store module configured to automatically save the new mapping of one or more of the datapoints and the mapped one or more additional datapoints from the database of datapoints (Subramanian, pa 0149, Annotations 1220, which may be generated by a NLU engine ( e.g., NLU engine 1020) or a human annotator (e.g., annotator 1030) may include a medical code ( e.g., a medical billing code) for each appropriate portion of the text 1210.) in a results database, wherein each mapped datapoint in the results database is associated with a reference to the corresponding unmapped datapoint in the database of datapoints (Subramanian, pa 0149, The diagnostic code 1222 may be associated with the diagnosis 1212 using a link 1232, and the procedure code 1224 may be associated with the procedure 1214 using a link 1234. The links 1232 and 1234 may be entries in a field of a database table associating annotations 1220 with portions of the text 1210, or they may be pointers or any other suitable data association.).
It would have been obvious at the effective filing date of the invention to a person having ordinary skill in the art to which said subject matter pertains to have modified Edwards with the teachings of Subramanian because it increases the accuracy of annotations (Subramanian, pa 0028).
Edwards in view of Subramanian doesn’t expressly discuss wherein the fetch module is code that can access a selected column, extract values from the selected column, and then return a unique list of values by removing redundant values.
Biswas teaches generate, by a fetch module, from the database of datapoints, a list of one or more datapoints to be mapped, wherein the fetch module is code that can access a selected column, extract values from the selected column, and then return a unique list of values by removing redundant values (Biswas, Col. 32 Li. 18-30, The first data and/or the second data is then cleansed and filtered. The system identifies and recognizes location of the first data based on at least one of a predefined rule, and an input from a user. The input may comprise selecting particular data sets from the data. The second data, and/or the data desired by the user are only left after the cleansing and filtering step. The cleansing and filtering data comprises at least one of removing duplicate data, filtering data by search queries, fix spelling errors, filter incomplete data and aggregate values, etc. The data is also then cataloged to record a directory of information of at least meta data, data sets, files, and database information onto the database.).
It would have been obvious at the effective filing date of the invention to a person having ordinary skill in the art to which said subject matter pertains to have modified Edwards in view of Subramanian with the teachings of Biswas because it removes unwanted data (Biswas, Col. 21 Li. 27-32).
With respect to claims 11-15, the limitations are essentially the same as claims 2, 3, and 6-8, and are rejected for the same reasons.
Response to Amendment
35 U.S.C. 112 - Claim Interpretation
Applicant argues that the claims have sufficient support in the specification and drawings and should not be interpreted under 35 U.S.C. 112(f). The Examiner respectfully disagrees. Applicant has not pointed to portions of the specification that provide support for the claim limitations interpreted under 35 U.S.C. 112(f). The 35 U.S.C. 112(f) rejection is maintained.
35 U.S.C. 112 - Claim Rejections
Applicant’s arguments, with respect to claims 1-15 have been fully considered. A few issues have been cured by amendments, however, issues remain, as discussed above.
Response to Arguments
35 U.S.C. 101
Applicant argues that the claims are similar to Enfish and not directed towards an abstract idea because the claims improves mapping data and systems. The Examiner respectfully disagrees. In order to rely on Enfish, Applicant must specifically be able to show improvement in the functionality of the computer itself. In Enfish, the courts determined that the specification must distinguish between the instant invention and conventional solutions (e.g. by disclosing one or more problems with the conventional solutions). There must also be limitations in the claim that disclose a technological solution to the identified problem. See 2106.04(d)(1). However, the claim merely uses the computer as a tool to process the information (“… the focus of the claims is not on such an improvement in computers as tools, but on certain independently abstract ideas that use computers as tools” see MPEP 2106.05(a)(I)).
McRO’s specific rules were rules that enabled modification of specific automation tasks that previously could not be automated. These rules “improved the existing technological process”, rather than merely using the computer as a tool to automate conventional activity. See MPEP 2106.04(a).
35 U.S.C. 103
Applicant seems to argue a newly amended limitation. Applicant’s amendment has rendered the previous rejection moot. Upon further consideration of the amendment, a new grounds of rejection is made in view of Biswas (US 12,079,737).
Conclusion
Applicant's amendment necessitated the new ground(s) of rejection presented in this Office action. Accordingly, THIS ACTION IS MADE FINAL. See MPEP § 706.07(a). Applicant is reminded of the extension of time policy as set forth in 37 CFR 1.136(a).
A shortened statutory period for reply to this final action is set to expire THREE MONTHS from the mailing date of this action. In the event a first reply is filed within TWO MONTHS of the mailing date of this final action and the advisory action is not mailed until after the end of the THREE-MONTH shortened statutory period, then the shortened statutory period will expire on the date the advisory action is mailed, and any nonprovisional extension fee (37 CFR 1.17(a)) pursuant to 37 CFR 1.136(a) will be calculated from the mailing date of the advisory action. In no event, however, will the statutory period for reply expire later than SIX MONTHS from the mailing date of this final action.
Any inquiry concerning this communication or earlier communications from the examiner should be directed to BRITTANY N ALLEN whose telephone number is (571)270-3566. The examiner can normally be reached M-F 9 am - 5:00 pm EST.
Examiner interviews are available via telephone, in-person, and video conferencing using a USPTO supplied web-based collaboration tool. To schedule an interview, applicant is encouraged to use the USPTO Automated Interview Request (AIR) at http://www.uspto.gov/interviewpractice.
If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Sherief Badawi can be reached at 571-272-9782. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
Information regarding the status of published or unpublished applications may be obtained from Patent Center. Unpublished application information in Patent Center is available to registered users. To file and manage patent submissions in Patent Center, visit: https://patentcenter.uspto.gov. Visit https://www.uspto.gov/patents/apply/patent-center for more information about Patent Center and https://www.uspto.gov/patents/docx for information about filing in DOCX format. For additional questions, contact the Electronic Business Center (EBC) at 866-217-9197 (toll-free). If you would like assistance from a USPTO Customer Service Representative, call 800-786-9199 (IN USA OR CANADA) or 571-272-1000.
/BRITTANY N ALLEN/ Primary Examiner, Art Unit 2169
