DETAILED ACTION
This action is in response to the Applicant Response filed 03 December 2025 for application 18/051,535 filed 01 November 2022.
Claim(s) 1, 3, 5-6, 8-10, 12, 14-15, 17-19 is/are currently amended.
Claim(s) 1-20 is/are pending.
Claim(s) 1-20 is/are rejected.
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 .
Response to Arguments
Applicant's arguments regarding the objections to the claims have been fully considered and, in light of the amendments to the claims, are persuasive.
Applicant’s arguments regarding the 35 U.S.C. 112(b) rejections of claims 1-20 for antecedent basis and relative term issues have been fully considered but are not persuasive. While applicant states that the claims have been amended to correct the issues, there is no evidence in the filed claim set of such corrections.
Applicant’s arguments regarding the 35 U.S.C. 112(a) and 35 U.S.C. 112(b) rejections of claims 19-20 associated with the claim interpretation under 35 U.S.C. 112(f) have been fully considered but are not persuasive. While applicant states that the claims have been amended to correct the issues, there is no evidence in the filed claim set of such corrections. Currently the claim recites a processing subsystem on a server which controls communications among modules, but there is no recited structure for the modules.
Applicant’s arguments regarding the 35 U.S.C. 101 rejection of claims 1-20 have been fully considered but are not persuasive.
Applicant first argues that the claims are not directed to an abstract idea. Examiner respectfully disagrees. As noted by applicant, the claims are directed to categorizing data. As discussed in more detail below, this is an abstract idea. Further applicant argues that the claims recite modules to perform the steps of data categorization and is beyond human capacity. First, examiner notes that claims 1-18 do not recite modules. Additionally, as noted in the MPEP, it is important to note that a general purpose computer that applies a judicial exception, such as an abstract idea, by use of conventional computer functions does not qualify as a particular machine. MPEP 2106.05(f)(I). Further, when the machine is merely an object on which the method operates, the exception is not integrated into a practical application and does not provide significantly more. MPEP 2106.05(f)(I). Here the modules are simply generic computer components used to apply the abstract idea.
Applicant next argues that the modules are arranged in such a way as to integrate the abstract idea into a practical application. Examiner respectfully disagrees. First, examiner notes that claims 1-18 do not recite modules. Additionally, as noted above, the modules are simply generic computer components used to apply the exception. Further, there is no evidence in the claims of any specific arrangement of the modules or whether any arrangement would be meaningful.
Applicant next argues that the modules provide significantly more. Examiner respectfully disagrees. First, examiner notes that claims 1-18 do not recite modules. Additionally, as noted above, the modules are simply generic computer components used to apply the exception.
Therefore, the 35 U.S.C. 101 rejection of claims 1-20 is maintained.
Applicant’s arguments regarding the 35 U.S.C. 103 rejections of claims 1-20 have been fully considered but are not persuasive.
Applicant first argues that the cited references do not teach table structures of the data. Examiner respectfully disagrees. Hu, teaches that the data from the sources are used to populate list, which is a table (Hu, section 1).
Applicant next argues that the references do not teach a combination of complex and discrete feature or an embedding of the features. Examiner respectfully disagrees. Hu teaches extracting features from cookie data (section 3.2.1). Modarresi further teaches that the data can be categorical and numerical (Modarresi, [0016]). Modarresi teaches that categorical data is a non-numerical form of data having a categorical variable that includes multiple classes, the values of which are defined using at least some alphabetical characters (Modarresi, [0016]). The specification states provides an example of a complex feature such as cookie-name, where the values are regular expressions. Further, Hu teaches embedding tokens [discrete] into categories (Hu, section 3.2) and Modarresi teaches classifying the data (Modarresi, [0016]-[0021]).
Applicant next argues that the references do not teach an ensemble model based on the embeddings. Examiner respectfully disagrees. As noted in Hu, the model uses both an MNB classifier and an n-gram based classifier to classify the cookie tokens [embeddings] (Hu, section 3.3.5).
Applicant next argues that there is no motivation to combine the references. Examiner respectfully disagrees. Examiner recognizes that obviousness may be established by combining or modifying the teachings of the prior art to produce the claimed invention where there is some teaching, suggestion, or motivation to do so found either in the references themselves or in the knowledge generally available to one of ordinary skill in the art. See In re Fine, 837 F.2d 1071, 5 USPQ2d 1596 (Fed. Cir. 1988), In re Jones, 958 F.2d 347, 21 USPQ2d 1941 (Fed. Cir. 1992), and KSR International Co. v. Teleflex, Inc., 550 U.S. 398, 82 USPQ2d 1385 (2007). In this case, while Modarresi may involve more generic data as opposed to the specific use of cookies in Hu, both references teach converting complex data into discrete data and classifying the discrete data/embeddings using machine learning.
Applicant next argues that the references do not teach the merging module. However, applicant argues limitations and/or elements that are not recited in the claims.
Lastly, applicant argues that the claimed invention provides advantages not achieved by the references. Examiner notes that the 103 rejections address all of the limitations of the recited claims. Further any potential improvements are addressed in the 35 U.S.C. 101 section.
Therefore, the 35 U.S.C. 103 rejections are maintained.
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.
The claims 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 collecting module ... is configured to gather ... (Claim 19)
a populating module ... is configured to populate ... (Claim 19)
a machine learning module ... is configured to recognize and determine ... (Claim 19)
a complex feature reduction module configured to convert ... (Claim 19)
a cookie reduction module configured to embed ... (Claim 19)
an ensembling module configured to create ... (Claim 19)
a predicting module ... is configured to predict ... (Claim 19)
a merging module ... is configured to merge ... (Claim 20)
Because this/these claim limitation(s) is/are being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, it/they is/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 this/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 it/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(b)
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 1-20 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 pre-AIA the applicant regards as the invention.
Regarding claim 19-20, various claim limitations reciting a collecting module ... is configured to gather ... (Claim 19), a populating module ... is configured to populate ... (Claim 19), a machine learning module ... is configured to recognize and determine ... (Claim 19), a complex feature reduction module configured to convert ... (Claim 19), a cookie reduction module configured to embed ... (Claim 19), an ensembling module configured to create ... (Claim 19), a predicting module ... is configured to predict ... (Claim 19), a merging module ... is configured to merge ... (Claim 20) … 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 functions and to clearly link the structure, material, or acts to the functions. The specification is devoid of adequate structure to perform the claimed functions. In particular, the specification states that a server hosts a processing subsystem that executes the various modules (Specification, [0023]). This appears to imply that the modules are software; however, this is not definitive. There is no clear disclosure of the particular structure, either explicitly or inherently, to perform the limitations. As would be recognized by those of ordinary skill in the art, the limitations can be performed in any number of ways including in hardware, in software, or a combination of the two. The specification does not provide sufficient details such that one of ordinary skill in the art would understand which structure or structures perform(s) the claimed functions.
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.
Claims 1, 10 recites create a model by using ensembling learning with inputs comprising the reduced-dimensionality output and the actual values of the one or more discrete features while failing to provide a proper antecedent basis for “the reduced-dimensionality output” and “the actual values.” Moreover, it is unclear as to what is meant by “reduced-dimensionality output” as there is no mention of dimension reduction or any process to generate an output in the claim prior to the use of the term. Correction or clarification is required.
Examiner’s Note: For the purposes of examination, “the reduced-dimensionality output” will be interpreted as the discrete features generated from the conversion of the complex values and “the actual values” will be interpreted as the original discrete features. Therefore, the limitation will be interpreted as reciting create a model by using ensembling learning with inputs comprising the discrete features corresponding to the converted complex features and actual values of the discrete features from the plurality of features.
Claim 19 recites an ensembling module configured to create a model by using ensembling learning with inputs comprising the reduced-dimensionality output and the actual values of the one or more discrete features while failing to provide a proper antecedent basis for “the reduced-dimensionality output” and “the actual values.” Moreover, it is unclear as to what is meant by “reduced-dimensionality output” as there is no mention of dimension reduction or any process to generate an output in the claim prior to the use of the term. Correction or clarification is required.
Examiner’s Note: For the purposes of examination, “the reduced-dimensionality output” will be interpreted as the discrete features generated from the conversion of the complex values and “the actual values” will be interpreted as the original discrete features. Therefore, the limitation will be interpreted as reciting an ensembling module configured to create a model by using ensembling learning with inputs comprising the discrete features corresponding to the converted complex features and actual values of the discrete features from the plurality of features.
Claims 1, 10, 19 recite large scale categorization of cookies which is a relative term and renders the claim indefinite. The term “large scale” is not defined by the claim, the specification does not provide a standard for ascertaining the requisite degree, and one of ordinary skill in the art would not be reasonably apprised of the scope of the invention. Correction or clarification is required.
Examiner’s Note: For the purposes of examination, the claims will be interpreted as if “large scale” is not recited (e.g., A computer-implemented method for categorization of cookies comprising ...).
Claims 2-9, 11-18, 20 are rejected under 35 U.S.C. 112(b) due to their dependence, either directly or indirectly, on claims 1, 10, 19-20
Claim Rejections - 35 USC § 112(a)
The following is a quotation of the first paragraph of 35 U.S.C. 112(a):
(a) IN GENERAL.—The specification shall contain a written description of the invention, and of the manner and process of making and using it, in such full, clear, concise, and exact terms as to enable any person skilled in the art to which it pertains, or with which it is most nearly connected, to make and use the same, and shall set forth the best mode contemplated by the inventor or joint inventor of carrying out the invention.
The following is a quotation of the first paragraph of pre-AIA 35 U.S.C. 112:
The specification shall contain a written description of the invention, and of the manner and process of making and using it, in such full, clear, concise, and exact terms as to enable any person skilled in the art to which it pertains, or with which it is most nearly connected, to make and use the same, and shall set forth the best mode contemplated by the inventor of carrying out his invention.
Claims 19-20 are rejected under 35 U.S.C. 112(a) or 35 U.S.C. 112 (pre-AIA ), first paragraph, as failing to comply with the written description requirement.
Claims 19-20 contain subject matter which was not described in the specification in such a way as to reasonably convey to one skilled in the relevant art that the inventor or a joint inventor, or for pre AIA the inventor(s), at the time the application was filed, had possession of the claimed invention. As discussed above, the disclosure does not provide adequate structure to perform the claimed functions of:
a collecting module ... is configured to gather ... (Claim 19)
a populating module ... is configured to populate ... (Claim 19)
a machine learning module ... is configured to recognize and determine ... (Claim 19)
a complex feature reduction module configured to convert ... (Claim 19)
a cookie reduction module configured to embed ... (Claim 19)
an ensembling module configured to create ... (Claim 19)
a predicting module ... is configured to predict ... (Claim 19)
a merging module ... is configured to merge ... (Claim 20)
The specification does not demonstrate that applicant has made an invention that achieves the claimed function because the invention is not described with sufficient detail such that one of ordinary skill in the art can reasonably conclude that the inventor had possession of the claimed invention.
Claim 20 is rejected under 35 U.S.C. 112(a) due to its dependence, either directly or indirectly, on claim 19.
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.
Claim(s) 1-20 is/are rejected under 35 U.S.C. 101, because the claim(s) is/are directed to an abstract idea, and because the claim elements, whether considered individually or in combination, do not amount to significantly more than the abstract idea, see Alice Corporation Pty. Ltd. V. CLS Bank International et al., 573 US 208 (2014).
Regarding claim 1, the claim is rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more.
Step 1 Analysis: Claim 1 is directed to a method, which is directed to a process, one of the statutory categories.
Step 2A Prong One Analysis: The claim recites a(n) method for large scale categorization of cookies.
The limitation of gathering information about a plurality of cookies from a first source and a second source wherein the plurality of cookies comprises a plurality of features wherein the plurality of features comprise a combination of complex features and discrete features, as drafted, is a process that, under its broadest reasonable interpretation, covers a mental process. The limitation is directed to observation, evaluation, judgment and opinion and is a process capable of being performed by a human mentally or using pen and paper.
The limitation of populating the plurality of cookies into a first table and a second table corresponding to the first source and the second source respectively wherein the first source comprises of a plurality of lists and the second source comprises of a plurality of websites, as drafted, is a process that, under its broadest reasonable interpretation, covers a mental process. The limitation is directed to observation, evaluation, judgment and opinion and is a process capable of being performed by a human mentally or using pen and paper.
The limitation of convert the complex features of the plurality of cookies into corresponding discrete features, wherein the discrete features are set by using at least one of external datasets and embedding the complex features, as drafted, is a process that, under its broadest reasonable interpretation, covers a mental process. The limitation is directed to observation, evaluation, judgment and opinion and is a process capable of being performed by a human mentally or using pen and paper.
The limitation of embed the plurality of cookies, upon converting the complex features into corresponding discrete features, wherein a classifier is built as an output of an embedding of the plurality of cookies, wherein the classifier is defined as a feature, as drafted, is a process that, under its broadest reasonable interpretation, covers a mental process. The limitation is directed to observation, evaluation, judgment and opinion and is a process capable of being performed by a human mentally or using pen and paper.
The limitation of create a model by using ensembling learning with inputs comprising the reduced-dimensionality output and the actual values of the discrete features, as drafted, is a process that, under its broadest reasonable interpretation, covers a mental process. The limitation is directed to observation, evaluation, judgment and opinion and is a process capable of being performed by a human mentally or using pen and paper.
The limitation of predicting the categorization of the plurality of cookies... into a plurality of classes based on a threshold wherein the plurality of cookies is populated into a third table and a fourth table corresponding to the first source and second source respectively, as drafted, is a process that, under its broadest reasonable interpretation, covers a mental process. The limitation is directed to observation, evaluation, judgment and opinion and is a process capable of being performed by a human mentally or using pen and paper.
If a claim limitation, under its broadest reasonable interpretation, covers performance of the limitation in the mind, then it falls within the "Mental Processes" grouping. Accordingly, the claim recites an abstract idea.
Step 2A Prong Two Analysis: With respect to the abstract idea, the judicial exception is not integrated into a practical application.
The claim recites additional element(s) – computer-implemented. The additional element(s) is/are recited at a high-level of generality (i.e., as generic computer components performing generic computer functions of executing instructions on the computers) such that it amounts to no more than mere instructions to apply the exception using generic computer components (MPEP 2106.05(b)).
The claim recites additional element(s) – one or more machine learning techniques, classifier, model, ensembling learning. The additional element(s) is/are recited at a high-level of generality such that it amounts to no more than indicating a field of use or technological environment in which to apply the judicial exception (MPEP 2106.05(h)).
The claim recites subjecting the first table and the second table to one or more machine learning techniques to recognize and determine the plurality of features ...; ... through the machine learning technique ... which is simply applying the model recited at a high level of generality and amounts to the recitation of the words “apply it” (or an equivalent) or amounts to no more than mere instructions to implement an abstract idea or other exception on a computer (MPEP 2106.05(f)).
Accordingly, the additional element(s) do(es) not integrate the abstract idea into a practical application because the additional element(s) do(es) not impose any meaningful limits on practicing the abstract idea, and, therefore, the claim is directed to an abstract idea.
Step 2B Analysis: The claim does not include additional elements that are sufficient to amount to significantly more than the judicial exception. As discussed above with respect to the integration of the abstract idea into a practical application, the additional element(s) of:
computer-implemented amount(s) to no more than mere instructions to apply the exception using generic computer components (MPEP 2106.05(b))
applying the model amount(s) to no more than mere instructions to apply the exception (MPEP 2106.05(f))
one or more machine learning techniques, classifier, model, ensembling learning amount(s) to no more than indicating a field of use or technological environment in which to apply the judicial exception (MPEP 2106.05(h))
The additional element(s) do(es) not provide an inventive concept, and, therefore, the claim is not patent eligible.
Regarding claim 2, the claim is rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more.
Step 1 Analysis: Claim 2 is directed to a method, which is directed to a process, one of the statutory categories.
Step 2A Prong One Analysis: The claim recites a(n) method for large scale categorization of cookies.
The limitation of wherein the plurality of classes from the third table and the fourth table, upon prediction, are merged together with precedence to manually categorized cookies, as drafted, is a process that, under its broadest reasonable interpretation, covers a mental process. The limitation is directed to observation, evaluation, judgment and opinion and is a process capable of being performed by a human mentally or using pen and paper.
If a claim limitation, under its broadest reasonable interpretation, covers performance of the limitation in the mind, then it falls within the "Mental Processes" grouping. Accordingly, the claim recites an abstract idea.
Step 2A Prong Two Analysis: With respect to the abstract idea, the judicial exception is not integrated into a practical application.
The claim recites subsequently storing the third table and the fourth table, upon merging, into a fifth table, which is simply storing data recited at a high level of generality. This is nothing more than insignificant extra-solution activity (MPEP 2106.05(g)).
Accordingly, the additional element(s) do(es) not integrate the abstract idea into a practical application because the additional element(s) do(es) not impose any meaningful limits on practicing the abstract idea, and, therefore, the claim is directed to an abstract idea.
Step 2B Analysis: The claim does not include additional elements that are sufficient to amount to significantly more than the judicial exception. As discussed above with respect to the integration of the abstract idea into a practical application, the additional element(s) of:
storing data amount(s) to no more than insignificant extra-solution activity (MPEP 2106.05(g)), wherein the insignificant extra-solution activity is the well-understood routine and conventional activit(y/ies) of storing and retrieving information in memory (MPEP 2016.05(d))
The additional element(s) do(es) not provide an inventive concept, and, therefore, the claim is not patent eligible.
Regarding claim 3, the claim is rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more.
Step 1 Analysis: Claim 3 is directed to a method, which is directed to a process, one of the statutory categories.
Step 2A Prong One Analysis: The claim recites a(n) method for large scale categorization of cookies. The Step 2A Prong One Analysis for claim 1 is applicable here since claim 3 carries out the method of claim 1 but for the recitation of additional element(s) of wherein the information about the plurality of cookies is automatically retrieved from the second source by crawling the plurality of websites with a special plugin and subsequently storing the information in the second table.
Step 2A Prong Two Analysis: With respect to the abstract idea, the judicial exception is not integrated into a practical application.
The claim recites wherein the information about the plurality of cookies is automatically retrieved from the second source by crawling the plurality of websites with a special plugin and subsequently storing the information in the second table, which is simply retrieving and storing data recited at a high level of generality. This is nothing more than insignificant extra-solution activity (MPEP 2106.05(g)).
Accordingly, the additional element(s) do(es) not integrate the abstract idea into a practical application because the additional element(s) do(es) not impose any meaningful limits on practicing the abstract idea, and, therefore, the claim is directed to an abstract idea.
Step 2B Analysis: The claim does not include additional elements that are sufficient to amount to significantly more than the judicial exception. As discussed above with respect to the integration of the abstract idea into a practical application, the additional element(s) of:
retrieving and storing data amount(s) to no more than insignificant extra-solution activity (MPEP 2106.05(g)), wherein the insignificant extra-solution activity is the well-understood routine and conventional activit(y/ies) of receiving or transmitting data over a network and/or storing and retrieving information in memory (MPEP 2016.05(d))
The additional element(s) do(es) not provide an inventive concept, and, therefore, the claim is not patent eligible.
Regarding claim 4, the claim is rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more.
Step 1 Analysis: Claim 4 is directed to a method, which is directed to a process, one of the statutory categories.
Step 2A Prong One Analysis: The claim recites a(n) method for large scale categorization of cookies. The Step 2A Prong One Analysis for claim 1 is applicable here since claim 4 carries out the method of claim 1 but for the recitation of additional element(s) of wherein a part of the first table and the second table comprises manually categorized cookies.
Step 2A Prong Two Analysis: With respect to the abstract idea, the judicial exception is not integrated into a practical application. In particular, the claim recites additional information regarding the data and the element(s) do(es) not apply the exception in a meaningful way (MPEP 2106.05(e)). Accordingly, the additional element(s) do(es) not integrate the abstract idea into a practical application because the additional element(s) do(es) not impose any meaningful limits on practicing the abstract idea, and, therefore, the claim is directed to an abstract idea.
Step 2B Analysis: The claim does not include additional elements that are sufficient to amount to significantly more than the judicial exception. As discussed above with respect to the integration of the abstract idea into a practical application, the additional element(s) of additional information regarding the data do(es) not apply the exception in a meaningful way (MPEP 2106.05(e)). Not applying the exception in a meaningful way does not provide an inventive concept, and, therefore, the claim is not patent eligible.
Regarding claim 5, the claim is rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more.
Step 1 Analysis: Claim 5 is directed to a method, which is directed to a process, one of the statutory categories.
Step 2A Prong One Analysis: The claim recites a(n) method for large scale categorization of cookies.
The limitation of ... learns the relationship between the plurality of features of the plurality of cookies and corresponding categories, as drafted, is a process that, under its broadest reasonable interpretation, covers a mental process. The limitation is directed to observation, evaluation, judgment and opinion and is a process capable of being performed by a human mentally or using pen and paper.
If a claim limitation, under its broadest reasonable interpretation, covers performance of the limitation in the mind, then it falls within the "Mental Processes" grouping. Accordingly, the claim recites an abstract idea.
Step 2A Prong Two Analysis: With respect to the abstract idea, the judicial exception is not integrated
into a practical application. The claim does not recite any additional elements which integrate the
abstract idea into a practical application and, therefore, does not impose any meaningful limits on
practicing the abstract idea. Therefore, the claim is directed to an abstract idea.
Step 2B Analysis: The claim does not include additional elements that are sufficient to amount to
significantly more than the judicial exception. As discussed above with respect to the integration of the
abstract idea into a practical application, the claim does not recite any additional elements which
provide an inventive concept, and, therefore, the claim is not patent eligible.
Regarding claim 6, the claim is rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more.
Step 1 Analysis: Claim 6 is directed to a method, which is directed to a process, one of the statutory categories.
Step 2A Prong One Analysis: The claim recites a(n) method for large scale categorization of cookies. The Step 2A Prong One Analysis for claim 2 is applicable here since claim 6 carries out the method of claim 2 but for the recitation of additional element(s) of wherein the fifth table comprises the categorization of the plurality of cookies and metadata used for subsequent training of the one or more machine learning technique.
Step 2A Prong Two Analysis: With respect to the abstract idea, the judicial exception is not integrated into a practical application. In particular, the claim recites additional information regarding the data and the element(s) do(es) not apply the exception in a meaningful way (MPEP 2106.05(e)). Accordingly, the additional element(s) do(es) not integrate the abstract idea into a practical application because the additional element(s) do(es) not impose any meaningful limits on practicing the abstract idea, and, therefore, the claim is directed to an abstract idea.
Step 2B Analysis: The claim does not include additional elements that are sufficient to amount to significantly more than the judicial exception. As discussed above with respect to the integration of the abstract idea into a practical application, the additional element(s) of additional information regarding the data do(es) not apply the exception in a meaningful way (MPEP 2106.05(e)). Not applying the exception in a meaningful way does not provide an inventive concept, and, therefore, the claim is not patent eligible.
Regarding claim 7, the claim is rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more.
Step 1 Analysis: Claim 7 is directed to a method, which is directed to a process, one of the statutory categories.
Step 2A Prong One Analysis: The claim recites a(n) method for large scale categorization of cookies. The Step 2A Prong One Analysis for claim 1 is applicable here since claim 7 carries out the method of claim 1 but for the recitation of additional element(s) of wherein the plurality of cookies is categorized online and offline.
Step 2A Prong Two Analysis: With respect to the abstract idea, the judicial exception is not integrated into a practical application. In particular, the claim recites additional information regarding the data categorization and the element(s) do(es) not apply the exception in a meaningful way (MPEP 2106.05(e)). Accordingly, the additional element(s) do(es) not integrate the abstract idea into a practical application because the additional element(s) do(es) not impose any meaningful limits on practicing the abstract idea, and, therefore, the claim is directed to an abstract idea.
Step 2B Analysis: The claim does not include additional elements that are sufficient to amount to significantly more than the judicial exception. As discussed above with respect to the integration of the abstract idea into a practical application, the additional element(s) of additional information regarding the data categorization do(es) not apply the exception in a meaningful way (MPEP 2106.05(e)). Not applying the exception in a meaningful way does not provide an inventive concept, and, therefore, the claim is not patent eligible.
Regarding claim 8, the claim is rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more.
Step 1 Analysis: Claim 8 is directed to a method, which is directed to a process, one of the statutory categories.
Step 2A Prong One Analysis: The claim recites a(n) method for large scale categorization of cookies. The Step 2A Prong One Analysis for claim 1 is applicable here since claim 8 carries out the method of claim 1 but for the recitation of additional element(s) of wherein the plurality of cookies are website cookies.
Step 2A Prong Two Analysis: With respect to the abstract idea, the judicial exception is not integrated into a practical application. In particular, the claim recites additional information regarding the data and the element(s) do(es) not apply the exception in a meaningful way (MPEP 2106.05(e)). Accordingly, the additional element(s) do(es) not integrate the abstract idea into a practical application because the additional element(s) do(es) not impose any meaningful limits on practicing the abstract idea, and, therefore, the claim is directed to an abstract idea.
Step 2B Analysis: The claim does not include additional elements that are sufficient to amount to significantly more than the judicial exception. As discussed above with respect to the integration of the abstract idea into a practical application, the additional element(s) of additional information regarding the data do(es) not apply the exception in a meaningful way (MPEP 2106.05(e)). Not applying the exception in a meaningful way does not provide an inventive concept, and, therefore, the claim is not patent eligible.
Regarding claim 9, the claim is rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more.
Step 1 Analysis: Claim 9 is directed to a method, which is directed to a process, one of the statutory categories.
Step 2A Prong One Analysis: The claim recites a(n) method for large scale categorization of cookies. The Step 2A Prong One Analysis for claim 1 is applicable here since claim 9 carries out the method of claim 1 but for the recitation of additional element(s) of wherein the one or more machine learning techniques are Ensemble Deep Learning modelling approach and End-to-End Deep Learning modelling approach.
Step 2A Prong Two Analysis: With respect to the abstract idea, the judicial exception is not integrated into a practical application.
The claim recites wherein the one or more machine learning techniques are Ensemble Deep Learning modelling approach and End-to-End Deep Learning modelling approach which is simply additional information regarding the machine learning techniques, and the element(s) do(es) not apply the exception in a meaningful way (MPEP 2106.05(e)).
The claim recites additional element(s) – Ensemble Deep Learning, End-to-End Deep Learning. The additional element(s) is/are recited at a high-level of generality such that it amounts to no more than indicating a field of use or technological environment in which to apply the judicial exception (MPEP 2106.05(h)).
Accordingly, the additional element(s) do(es) not integrate the abstract idea into a practical application because the additional element(s) do(es) not impose any meaningful limits on practicing the abstract idea, and, therefore, the claim is directed to an abstract idea.
Step 2B Analysis: The claim does not include additional elements that are sufficient to amount to significantly more than the judicial exception. As discussed above with respect to the integration of the abstract idea into a practical application, the additional element(s) of:
Ensemble Deep Learning, End-to-End Deep Learning amount(s) to no more than indicating a field of use or technological environment in which to apply the judicial exception (MPEP 2106.05(h))
additional information regarding the machine learning techniques do(es) not apply the exception in a meaningful way (MPEP 2106.05(e))
The additional element(s) do(es) not provide an inventive concept, and, therefore, the claim is not patent eligible.
Regarding claim 10, the claim is rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more.
Step 1 Analysis: Claim 10 is directed to a computer-readable medium, which is directed to an article of manufacture, one of the statutory categories.
Step 2A Prong One Analysis: The claim recites a(n) computer-readable medium ... to perform a method for large scale categorization of cookies.
The limitation of gathering information about a plurality of cookies from a first source and a second source wherein the plurality of cookies comprises a plurality of features wherein the plurality of features comprise a combination of complex features and discrete features, as drafted, is a process that, under its broadest reasonable interpretation, covers a mental process. The limitation is directed to observation, evaluation, judgment and opinion and is a process capable of being performed by a human mentally or using pen and paper.
The limitation of populating the plurality of cookies into a first table and a second table corresponding to the first source and the second source respectively wherein the first source comprises of a plurality of lists and the second source comprises of a plurality of websites, as drafted, is a process that, under its broadest reasonable interpretation, covers a mental process. The limitation is directed to observation, evaluation, judgment and opinion and is a process capable of being performed by a human mentally or using pen and paper.
The limitation of convert the complex features of the plurality of cookies into corresponding discrete features, wherein the discrete features are set by using at least one of external datasets and embedding the complex features, as drafted, is a process that, under its broadest reasonable interpretation, covers a mental process. The limitation is directed to observation, evaluation, judgment and opinion and is a process capable of being performed by a human mentally or using pen and paper.
The limitation of embed the plurality of cookies, upon converting the complex features into corresponding discrete features, wherein a classifier is built as an output of an embedding of the plurality of cookies, wherein the classifier is defined as a feature, as drafted, is a process that, under its broadest reasonable interpretation, covers a mental process. The limitation is directed to observation, evaluation, judgment and opinion and is a process capable of being performed by a human mentally or using pen and paper.
The limitation of create a model by using ensembling learning with inputs comprising the reduced-dimensionality output and the actual values of the discrete features, as drafted, is a process that, under its broadest reasonable interpretation, covers a mental process. The limitation is directed to observation, evaluation, judgment and opinion and is a process capable of being performed by a human mentally or using pen and paper.
The limitation of predicting the categorization of the plurality of cookies ... into a plurality of classes based on a threshold wherein the plurality of cookies is populated into a third table and a fourth table corresponding to the first source and second source respectively, as drafted, is a process that, under its broadest reasonable interpretation, covers a mental process. The limitation is directed to observation, evaluation, judgment and opinion and is a process capable of being performed by a human mentally or using pen and paper.
If a claim limitation, under its broadest reasonable interpretation, covers performance of the limitation in the mind, then it falls within the "Mental Processes" grouping. Accordingly, the claim recites an abstract idea.
Step 2A Prong Two Analysis: With respect to the abstract idea, the judicial exception is not integrated into a practical application.
The claim recites additional element(s) – computer-readable medium, computer program, processor. The additional element(s) is/are recited at a high-level of generality (i.e., as generic computer components performing generic computer functions of executing instructions on the computers) such that it amounts to no more than mere instructions to apply the exception using generic computer components (MPEP 2106.05(b)).
The claim recites additional element(s) – one or more machine learning techniques, classifier, model, ensembling learning. The additional element(s) is/are recited at a high-level of generality such that it amounts to no more than indicating a field of use or technological environment in which to apply the judicial exception (MPEP 2106.05(h)).
The claim recites subjecting the first table and the second table to one or more machine learning techniques to recognize and determine the plurality of features ...; ... through the machine learning technique ... which is simply applying the model recited at a high level of generality and amounts to the recitation of the words “apply it” (or an equivalent) or amounts to no more than mere instructions to implement an abstract idea or other exception on a computer (MPEP 2106.05(f)).
Accordingly, the additional element(s) do(es) not integrate the abstract idea into a practical application because the additional element(s) do(es) not impose any meaningful limits on practicing the abstract idea, and, therefore, the claim is directed to an abstract idea.
Step 2B Analysis: The claim does not include additional elements that are sufficient to amount to significantly more than the judicial exception. As discussed above with respect to the integration of the abstract idea into a practical application, the additional element(s) of:
computer-readable medium, computer program, processor amount(s) to no more than mere instructions to apply the exception using generic computer components (MPEP 2106.05(b))
applying the model amount(s) to no more than mere instructions to apply the exception (MPEP 2106.05(f))
one or more machine learning techniques, classifier, model, ensembling learning amount(s) to no more than indicating a field of use or technological environment in which to apply the judicial exception (MPEP 2106.05(h))
The additional element(s) do(es) not provide an inventive concept, and, therefore, the claim is not patent eligible.
Regarding claim 11, the claim is rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more.
Step 1 Analysis: Claim 11 is directed to a computer-readable medium, which is directed to an article of manufacture, one of the statutory categories.
Step 2A Prong One Analysis: The claim recites a(n) computer-readable medium ... to perform a method for large scale categorization of cookies.
The limitation of wherein the plurality of classes from the third table and the fourth table, upon prediction, are merged together with precedence to manually categorized cookies, as drafted, is a process that, under its broadest reasonable interpretation, covers a mental process. The limitation is directed to observation, evaluation, judgment and opinion and is a process capable of being performed by a human mentally or using pen and paper.
If a claim limitation, under its broadest reasonable interpretation, covers performance of the limitation in the mind, then it falls within the "Mental Processes" grouping. Accordingly, the claim recites an abstract idea.
Step 2A Prong Two Analysis: With respect to the abstract idea, the judicial exception is not integrated into a practical application.
The claim recites subsequently storing the third table and the fourth table, upon merging, into a fifth table, which is simply storing data recited at a high level of generality. This is nothing more than insignificant extra-solution activity (MPEP 2106.05(g)).
Accordingly, the additional element(s) do(es) not integrate the abstract idea into a practical application because the additional element(s) do(es) not impose any meaningful limits on practicing the abstract idea, and, therefore, the claim is directed to an abstract idea.
Step 2B Analysis: The claim does not include additional elements that are sufficient to amount to significantly more than the judicial exception. As discussed above with respect to the integration of the abstract idea into a practical application, the additional element(s) of:
storing data amount(s) to no more than insignificant extra-solution activity (MPEP 2106.05(g)), wherein the insignificant extra-solution activity is the well-understood routine and conventional activit(y/ies) of storing and retrieving information in memory (MPEP 2016.05(d))
The additional element(s) do(es) not provide an inventive concept, and, therefore, the claim is not patent eligible.
Regarding claim 12, the claim is rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more.
Step 1 Analysis: Claim 12 is directed to a computer-readable medium, which is directed to an article of manufacture, one of the statutory categories.
Step 2A Prong One Analysis: The claim recites a(n) computer-readable medium ... to perform a method for large scale categorization of cookies. The Step 2A Prong One Analysis for claim 10 is applicable here since claim 12 carries out the computer-readable medium of claim 10 but for the recitation of additional element(s) of wherein the information about the plurality of cookies is automatically retrieved from the second source by crawling the plurality of websites with a special plugin and subsequently storing the information in the second table.
Step 2A Prong Two Analysis: With respect to the abstract idea, the judicial exception is not integrated into a practical application.
The claim recites wherein the information about the plurality of cookies is automatically retrieved from the second source by crawling the plurality of websites with a special plugin and subsequently storing the information in the second table, which is simply retrieving and storing data recited at a high level of generality. This is nothing more than insignificant extra-solution activity (MPEP 2106.05(g)).
Accordingly, the additional element(s) do(es) not integrate the abstract idea into a practical application because the additional element(s) do(es) not impose any meaningful limits on practicing the abstract idea, and, therefore, the claim is directed to an abstract idea.
Step 2B Analysis: The claim does not include additional elements that are sufficient to amount to significantly more than the judicial exception. As discussed above with respect to the integration of the abstract idea into a practical application, the additional element(s) of:
retrieving and storing data amount(s) to no more than insignificant extra-solution activity (MPEP 2106.05(g)), wherein the insignificant extra-solution activity is the well-understood routine and conventional activit(y/ies) of receiving or transmitting data over a network and/or storing and retrieving information in memory (MPEP 2016.05(d))
The additional element(s) do(es) not provide an inventive concept, and, therefore, the claim is not patent eligible.
Regarding claim 13, the claim is rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more.
Step 1 Analysis: Claim 13 is directed to a computer-readable medium, which is directed to an article of manufacture, one of the statutory categories.
Step 2A Prong One Analysis: The claim recites a(n) computer-readable medium ... to perform a method for large scale categorization of cookies. The Step 2A Prong One Analysis for claim 10 is applicable here since claim 13 carries out the computer-readable medium of claim 10 but for the recitation of additional element(s) of wherein a part of the first table and the second table comprises manually categorized cookies.
Step 2A Prong Two Analysis: With respect to the abstract idea, the judicial exception is not integrated into a practical application. In particular, the claim recites additional information regarding the data and the element(s) do(es) not apply the exception in a meaningful way (MPEP 2106.05(e)). Accordingly, the additional element(s) do(es) not integrate the abstract idea into a practical application because the additional element(s) do(es) not impose any meaningful limits on practicing the abstract idea, and, therefore, the claim is directed to an abstract idea.
Step 2B Analysis: The claim does not include additional elements that are sufficient to amount to significantly more than the judicial exception. As discussed above with respect to the integration of the abstract idea into a practical application, the additional element(s) of additional information regarding the data do(es) not apply the exception in a meaningful way (MPEP 2106.05(e)). Not applying the exception in a meaningful way does not provide an inventive concept, and, therefore, the claim is not patent eligible.
Regarding claim 14, the claim is rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more.
Step 1 Analysis: Claim 14 is directed to a computer-readable medium, which is directed to an article of manufacture, one of the statutory categories.
Step 2A Prong One Analysis: The claim recites a(n) computer-readable medium ... to perform a method for large scale categorization of cookies.
The limitation of ... learns the relationship between the plurality of features of the plurality of cookies and corresponding categories, as drafted, is a process that, under its broadest reasonable interpretation, covers a mental process. The limitation is directed to observation, evaluation, judgment and opinion and is a process capable of being performed by a human mentally or using pen and paper.
If a claim limitation, under its broadest reasonable interpretation, covers performance of the limitation in the mind, then it falls within the "Mental Processes" grouping. Accordingly, the claim recites an abstract idea.
Step 2A Prong Two Analysis: With respect to the abstract idea, the judicial exception is not integrated
into a practical application. The claim does not recite any additional elements which integrate the
abstract idea into a practical application and, therefore, does not impose any meaningful limits on
practicing the abstract idea. Therefore, the claim is directed to an abstract idea.
Step 2B Analysis: The claim does not include additional elements that are sufficient to amount to
significantly more than the judicial exception. As discussed above with respect to the integration of the
abstract idea into a practical application, the claim does not recite any additional elements which
provide an inventive concept, and, therefore, the claim is not patent eligible.
Regarding claim 15, the claim is rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more.
Step 1 Analysis: Claim 15 is directed to a computer-readable medium, which is directed to an article of manufacture, one of the statutory categories.
Step 2A Prong One Analysis: The claim recites a(n) computer-readable medium ... to perform a method for large scale categorization of cookies. The Step 2A Prong One Analysis for claim 11 is applicable here since claim 15 carries out the computer-readable medium of claim 11 but for the recitation of additional element(s) of wherein the fifth table comprises the categorization of the plurality of cookies and metadata used for subsequent training of the one or more machine learning technique.
Step 2A Prong Two Analysis: With respect to the abstract idea, the judicial exception is not integrated into a practical application. In particular, the claim recites additional information regarding the data and the element(s) do(es) not apply the exception in a meaningful way (MPEP 2106.05(e)). Accordingly, the additional element(s) do(es) not integrate the abstract idea into a practical application because the additional element(s) do(es) not impose any meaningful limits on practicing the abstract idea, and, therefore, the claim is directed to an abstract idea.
Step 2B Analysis: The claim does not include additional elements that are sufficient to amount to significantly more than the judicial exception. As discussed above with respect to the integration of the abstract idea into a practical application, the additional element(s) of additional information regarding the data do(es) not apply the exception in a meaningful way (MPEP 2106.05(e)). Not applying the exception in a meaningful way does not provide an inventive concept, and, therefore, the claim is not patent eligible.
Regarding claim 16, the claim is rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more.
Step 1 Analysis: Claim 16 is directed to a computer-readable medium, which is directed to an article of manufacture, one of the statutory categories.
Step 2A Prong One Analysis: The claim recites a(n) computer-readable medium ... to perform a method for large scale categorization of cookies. The Step 2A Prong One Analysis for claim 10 is applicable here since claim 16 carries out the computer-readable medium of claim 10 but for the recitation of additional element(s) of wherein the plurality of cookies is categorized online and offline.
Step 2A Prong Two Analysis: With respect to the abstract idea, the judicial exception is not integrated into a practical application. In particular, the claim recites additional information regarding the data categorization and the element(s) do(es) not apply the exception in a meaningful way (MPEP 2106.05(e)). Accordingly, the additional element(s) do(es) not integrate the abstract idea into a practical application because the additional element(s) do(es) not impose any meaningful limits on practicing the abstract idea, and, therefore, the claim is directed to an abstract idea.
Step 2B Analysis: The claim does not include additional elements that are sufficient to amount to significantly more than the judicial exception. As discussed above with respect to the integration of the abstract idea into a practical application, the additional element(s) of additional information regarding the data categorization do(es) not apply the exception in a meaningful way (MPEP 2106.05(e)). Not applying the exception in a meaningful way does not provide an inventive concept, and, therefore, the claim is not patent eligible.
Regarding claim 17, the claim is rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more.
Step 1 Analysis: Claim 17 is directed to a computer-readable medium, which is directed to an article of manufacture, one of the statutory categories.
Step 2A Prong One Analysis: The claim recites a(n) computer-readable medium ... to perform a method for large scale categorization of cookies. The Step 2A Prong One Analysis for claim 10 is applicable here since claim 17 carries out the computer-readable medium of claim 10 but for the recitation of additional element(s) of wherein the plurality of cookies are website cookies.
Step 2A Prong Two Analysis: With respect to the abstract idea, the judicial exception is not integrated into a practical application. In particular, the claim recites additional information regarding the data and the element(s) do(es) not apply the exception in a meaningful way (MPEP 2106.05(e)). Accordingly, the additional element(s) do(es) not integrate the abstract idea into a practical application because the additional element(s) do(es) not impose any meaningful limits on practicing the abstract idea, and, therefore, the claim is directed to an abstract idea.
Step 2B Analysis: The claim does not include additional elements that are sufficient to amount to significantly more than the judicial exception. As discussed above with respect to the integration of the abstract idea into a practical application, the additional element(s) of additional information regarding the data do(es) not apply the exception in a meaningful way (MPEP 2106.05(e)). Not applying the exception in a meaningful way does not provide an inventive concept, and, therefore, the claim is not patent eligible.
Regarding claim 18, the claim is rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more.
Step 1 Analysis: Claim 18 is directed to a computer-readable medium, which is directed to an article of manufacture, one of the statutory categories.
Step 2A Prong One Analysis: The claim recites a(n) computer-readable medium ... to perform a method for large scale categorization of cookies. The Step 2A Prong One Analysis for claim 10 is applicable here since claim 18 carries out the computer-readable medium of claim 10 but for the recitation of additional element(s) of wherein the one or more machine learning techniques are Ensemble Deep Learning modelling approach and End-to-End Deep Learning modelling approach.
Step 2A Prong Two Analysis: With respect to the abstract idea, the judicial exception is not integrated into a practical application.
The claim recites wherein the machine learning techniques are Ensemble Deep Learning modelling approach and End-to-End Deep Learning modelling approach which is simply additional information regarding the machine learning techniques, and the element(s) do(es) not apply the exception in a meaningful way (MPEP 2106.05(e)).
The claim recites additional element(s) – Ensemble Deep Learning, End-to-End Deep Learning. The additional element(s) is/are recited at a high-level of generality such that it amounts to no more than indicating a field of use or technological environment in which to apply the judicial exception (MPEP 2106.05(h)).
Accordingly, the additional element(s) do(es) not integrate the abstract idea into a practical application because the additional element(s) do(es) not impose any meaningful limits on practicing the abstract idea, and, therefore, the claim is directed to an abstract idea.
Step 2B Analysis: The claim does not include additional elements that are sufficient to amount to significantly more than the judicial exception. As discussed above with respect to the integration of the abstract idea into a practical application, the additional element(s) of:
Ensemble Deep Learning, End-to-End Deep Learning amount(s) to no more than indicating a field of use or technological environment in which to apply the judicial exception (MPEP 2106.05(h))
additional information regarding the machine learning techniques do(es) not apply the exception in a meaningful way (MPEP 2106.05(e))
The additional element(s) do(es) not provide an inventive concept, and, therefore, the claim is not patent eligible.
Regarding claim 19, the claim is rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more.
Step 1 Analysis: Claim 19 is directed to a system with a processor, which is directed to a machine, one of the statutory categories.
Step 2A Prong One Analysis: The claim recites a(n) system for large scale categorization of cookies.
The limitation of ... gather information about a plurality of cookies from a first source and a second source wherein the plurality of cookies comprises a plurality of features wherein the plurality of features comprise a combination of complex features and discrete features, as drafted, is a process that, under its broadest reasonable interpretation, covers a mental process. The limitation is directed to observation, evaluation, judgment and opinion and is a process capable of being performed by a human mentally or using pen and paper.
The limitation of ... populate the plurality of cookies into a first table and a second table corresponding to the first source and the second source respectively wherein the first source comprises of a plurality of lists and the second source comprises of a plurality of websites, as drafted, is a process that, under its broadest reasonable interpretation, covers a mental process. The limitation is directed to observation, evaluation, judgment and opinion and is a process capable of being performed by a human mentally or using pen and paper.
The limitation of ... recognize and determine the plurality of features ..., as drafted, is a process that, under its broadest reasonable interpretation, covers a mental process. The limitation is directed to observation, evaluation, judgment and opinion and is a process capable of being performed by a human mentally or using pen and paper.
The limitation of ... convert the complex features of the plurality of cookies into corresponding discrete features, wherein the discrete features are set by using at least one of external datasets and embedding the complex features, as drafted, is a process that, under its broadest reasonable interpretation, covers a mental process. The limitation is directed to observation, evaluation, judgment and opinion and is a process capable of being performed by a human mentally or using pen and paper.
The limitation of ... embed the plurality of cookies, upon converting the complex features into corresponding discrete features, wherein a classifier is built as an output of an embedding of the plurality of cookies, wherein the classifier is defined as a feature, as drafted, is a process that, under its broadest reasonable interpretation, covers a mental process. The limitation is directed to observation, evaluation, judgment and opinion and is a process capable of being performed by a human mentally or using pen and paper.
The limitation of ... create a model by using ensembling learning with inputs comprising the reduced-dimensionality output and the actual values of the discrete features, as drafted, is a process that, under its broadest reasonable interpretation, covers a mental process. The limitation is directed to observation, evaluation, judgment and opinion and is a process capable of being performed by a human mentally or using pen and paper.
The limitation of ... predict the categorization of the plurality of cookies ... into a plurality of classes based on a threshold wherein the plurality of cookies is populated into a third table and a fourth table corresponding to the first source and second source respectively, as drafted, is a process that, under its broadest reasonable interpretation, covers a mental process. The limitation is directed to observation, evaluation, judgment and opinion and is a process capable of being performed by a human mentally or using pen and paper.
If a claim limitation, under its broadest reasonable interpretation, covers performance of the limitation in the mind, then it falls within the "Mental Processes" grouping. Accordingly, the claim recites an abstract idea.
Step 2A Prong Two Analysis: With respect to the abstract idea, the judicial exception is not integrated into a practical application.
The claim recites additional element(s) – system, processing subsystem, server, network, modules, collecting module, database, populating module, machine learning module, complex feature reduction module, cookie reduction module, ensembling module, predicting module. The additional element(s) is/are recited at a high-level of generality (i.e., as generic computer components performing generic computer functions of executing instructions on the computers) such that it amounts to no more than mere instructions to apply the exception using generic computer components (MPEP 2106.05(b)).
The claim recites additional element(s) – one or more machine learning techniques, classifier, model, ensembling learning. The additional element(s) is/are recited at a high-level of generality such that it amounts to no more than indicating a field of use or technological environment in which to apply the judicial exception (MPEP 2106.05(h)).
The claim recites ... with one or more machine learning techniques ...; ... through the machine learning technique ... which is simply applying the model recited at a high level of generality and amounts to the recitation of the words “apply it” (or an equivalent) or amounts to no more than mere instructions to implement an abstract idea or other exception on a computer (MPEP 2106.05(f)).
The claim recites processing subsystem ... configured to execute on a network to control bidirectional communications among a plurality of modules, which is simply transmitting data recited at a high level of generality. This is nothing more than insignificant extra-solution activity (MPEP 2106.05(g)).
Accordingly, the additional element(s) do(es) not integrate the abstract idea into a practical application because the additional element(s) do(es) not impose any meaningful limits on practicing the abstract idea, and, therefore, the claim is directed to an abstract idea.
Step 2B Analysis: The claim does not include additional elements that are sufficient to amount to significantly more than the judicial exception. As discussed above with respect to the integration of the abstract idea into a practical application, the additional element(s) of:
system, processing subsystem, server, network, modules, collecting module, database, populating module, machine learning module, complex feature reduction module, cookie reduction module, ensembling module, predicting module amount(s) to no more than mere instructions to apply the exception using generic computer components (MPEP 2106.05(b))
applying the model amount(s) to no more than mere instructions to apply the exception (MPEP 2106.05(f))
transmitting data amount(s) to no more than insignificant extra-solution activity (MPEP 2106.05(g)), wherein the insignificant extra-solution activity is the well-understood routine and conventional activit(y/ies) of receiving or transmitting data over a network (MPEP 2016.05(d))
one or more machine learning techniques, classifier, model, ensembling learning amount(s) to no more than indicating a field of use or technological environment in which to apply the judicial exception (MPEP 2106.05(h))
The additional element(s) do(es) not provide an inventive concept, and, therefore, the claim is not patent eligible.
Regarding claim 20, the claim is rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more.
Step 1 Analysis: Claim 20 is directed to a system with a processor, which is directed to a machine, one of the statutory categories.
Step 2A Prong One Analysis: The claim recites a(n) system for large scale categorization of cookies.
The limitation of ... merge the plurality of classes from the third table and the fourth table, upon prediction, with precedence to manually categorized cookies, as drafted, is a process that, under its broadest reasonable interpretation, covers a mental process. The limitation is directed to observation, evaluation, judgment and opinion and is a process capable of being performed by a human mentally or using pen and paper.
If a claim limitation, under its broadest reasonable interpretation, covers performance of the limitation in the mind, then it falls within the "Mental Processes" grouping. Accordingly, the claim recites an abstract idea.
Step 2A Prong Two Analysis: With respect to the abstract idea, the judicial exception is not integrated into a practical application.
The claim recites additional element(s) – merging module. The additional element(s) is/are recited at a high-level of generality (i.e., as generic computer components performing generic computer functions of executing instructions on the computers) such that it amounts to no more than mere instructions to apply the exception using generic computer components (MPEP 2106.05(b)).
The claim recites subsequently storing the third table and the fourth table, upon merging, into a fifth table, which is simply storing data recited at a high level of generality. This is nothing more than insignificant extra-solution activity (MPEP 2106.05(g)).
Accordingly, the additional element(s) do(es) not integrate the abstract idea into a practical application because the additional element(s) do(es) not impose any meaningful limits on practicing the abstract idea, and, therefore, the claim is directed to an abstract idea.
Step 2B Analysis: The claim does not include additional elements that are sufficient to amount to significantly more than the judicial exception. As discussed above with respect to the integration of the abstract idea into a practical application, the additional element(s) of:
merging module amount(s) to no more than mere instructions to apply the exception using generic computer components (MPEP 2106.05(b))
storing data amount(s) to no more than insignificant extra-solution activity (MPEP 2106.05(g)), wherein the insignificant extra-solution activity is the well-understood routine and conventional activit(y/ies) of storing and retrieving information in memory (MPEP 2016.05(d))
The additional element(s) do(es) not provide an inventive concept, and, therefore, the claim is not patent eligible.
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.
The factual inquiries for establishing a background for determining obviousness under 35 U.S.C. 103 are summarized as follows:
1. Determining the scope and contents of the prior art.
2. Ascertaining the differences between the prior art and the claims at issue.
3. Resolving the level of ordinary skill in the pertinent art.
4. Considering objective evidence present in the application indicating obviousness or nonobviousness.
Claim(s) 1, 4-5, 7-8, 10, 13-14, 16-17, 19 is/are rejected under 35 U.S.C. 103 as being unpatentable over Hu et al. (CCCC: Corralling Cookies into Categories with CookieMonster, hereinafter referred to as “Hu”) in view of Modarresi et al. (US 2019/0286747 A1 – Categorical Data Transformation and Clustering for Machine Learning Using Data Repository Systems, hereinafter referred to as “Modarresi”).
Regarding claim 1 (Currently Amended), Hu teaches a computer-implemented (Hu, section 3 – teaches collecting browser cookies from websites [This necessarily requires the use of a computer]) method for large scale categorization of cookies (Hu, section 3.2 – teaches method of cookie categorization) comprising:
gathering information about a plurality of cookies from a first source and a second source (Hu, section 1 – teaches gathering cookies from Cookiepedia [first source] and cookies from Alexa websites [second source]) wherein the plurality of cookies comprises a plurality of features wherein the plurality of features comprise a combination of complex features and discrete features (Hu, section 3.2.1 – teaches extracted features from the cookie names using tokenization);
populating the plurality of cookies into a first table and a second table corresponding to the first source and the second source respectively wherein the first source comprises of a plurality of lists and the second source comprises of a plurality of websites (Hu, section 1 – teaches Cookiepedia [first source] is a populated list [table] of cookies and collecting a list of cookies from Alexa websites [second source] [It would be obvious that collection would also be a populated list (i.e., table)]);
subjecting the first table and the second table to one or more machine learning techniques to recognize and determine the plurality of features wherein the one or more machine learning techniques (Hu, sections 3.2-3.3 – teaches subjecting both datasets to machine learning techniques (e.g., feature extraction and classification) in order to determine features of the cookies) is operable to:
convert the complex features of the plurality of cookies into corresponding discrete features (Hu, section 3.2 – teaches tokenizing the complex features [names] into discreate features [tokens]), wherein the discrete features are set by using at least one of external datasets and embedding the complex features (Hu, section 3.2 – teaches tokenizing based on at least the enchant dictionary [external dataset]);
embed the plurality of cookies, upon converting the complex features into corresponding discrete features, wherein a classifier is built as an output of embedding of the plurality of cookies, wherein the classifier is defined as a feature (Hu, section 3.2.2 – teaches clustering the tokens into four categories);
create a model by using ensembling learning with inputs comprising the reduced-dimensionality output and the actual values of the discrete features (Hu, section 3.3 – teaches using the tokens to create the CookieMonster cookie classifier using a plurality of models [ensembling]); and
predicting the categorization of the plurality of cookies, through the one or more machine learning techniques, into a plurality of classes based on a threshold wherein the plurality of cookies is populated into a third table and a fourth table corresponding to the first source and second source respectively (Hu, section 3.3.5 – teaches using the CookieMonster model to predict unknown cookies in both the Alexa dataset [first source] and the Cookiepedia dataset [second source] using multinomial naïve bayes [based on a threshold]; [It would be obvious that the first and second tables could be considered third and fourth tables to include the new classified data]).
While Hu teaches converting cookie names [complex features] into token [discrete features], Hu does not explicitly teach that any given cookie name is originally a token.
Modarresi teaches
… wherein the plurality of cookies comprises a plurality of features wherein the plurality of features comprise a combination of complex features and discrete features (Modarresi, [0015] – teaches machine learning data can be both categorical [complex] and numerical [discrete]; [In light of the Hu reference, the data is interpreted to be cookies]);
subjecting … to one or more machine learning techniques to recognize and determine the plurality of features wherein the one or more machine learning techniques (Modarresi, [0016]-[0021] – teaches machine learning techniques to determine features) is operable to:
convert the complex features of the plurality of cookies into corresponding discrete features (Modarresi, [0016] – teaches converting categorical [complex] data into numerical [discrete] data) …;
embed the plurality of cookies … wherein a classifier is built as an output of embedding of the plurality of cookies, wherein the classifier is defined as a feature (Modarresi, [0017]-[0021] – teaches embedding the categorical data into classifications [creating a classifier]);
create a model … with inputs comprising the reduced-dimensionality output and the actual values of the discrete features (Modarresi, [0022] – teaches inputting numerical data [original numerical data (discrete) and converted categorical data (reduced-dimensionality data)] into a machine learning model for training); and
predicting the categorization of the plurality of cookies, through the one or more machine learning techniques, into a plurality of classes based on a threshold (Modarresi, [0022] – teaches using the machine learning model for predictions, some model types being based on a threshold) ...
It would have been obvious to one of ordinary skill in the art before the filing date of the claimed invention to modify Hu with the teachings of Modarresi in order to make efficient and accurate use of categorical data in the field of website cookie categorization (Modarresi, Abstract – “Categorical data transformation and clustering techniques and systems are described for machine learning. These techniques and systems are configured to improve operation of a computing device to support efficient and accurate use of categorical data, which is not possible using conventional techniques. In an example, categorical data is received by a computing device that includes a categorical variable having a non-numerical data type for a number of classes. The categorical data is then converted into numerical data based on clustering used to generate a plurality of latent classes.”).
Regarding claim 4 (Original), Hu in view of Modarresi teaches all of the limitations of the method of claim 1 as noted above. Hu further teaches wherein a part of the first table and the second table comprises manually categorized cookies (Hu, section 3.2.2 – teaches manually classifying cookies; see also Hu, section 1).
It would have been obvious to one of ordinary skill in the art before the filing data of the claimed invention to combine the teachings of Hu and Modarresi for the same reasons as disclosed in claim 1 above.
Regarding claim 5 (Currently Amended), Hu in view of Modarresi teaches all of the limitations of the method of claim 1 as noted above. Hu further teaches wherein the one or more machine learning techniques learns the relationship between the plurality of features of the plurality of cookies and corresponding categories (Hu, section 3.3 – teaches training a model [learning relationships] to learn categories from tokens [features]).
It would have been obvious to one of ordinary skill in the art before the filing data of the claimed invention to combine the teachings of Hu and Modarresi for the same reasons as disclosed in claim 1 above.
Regarding claim 7 (Original), Hu in view of Modarresi teaches all of the limitations of the method of claim 1 as noted above. However, Hu in view of Modarresi does not explicitly teach wherein the plurality of cookies is categorized online and offline. Hu further teaches wherein the plurality of cookies is categorized online and offline (Hu, section 4 – teaches offline and online cookie categorization).
It would have been obvious to one of ordinary skill in the art before the filing data of the claimed invention to combine the teachings of Hu and Modarresi for the same reasons as disclosed in claim 1 above.
Regarding claim 8 (Currently Amended), Hu in view of Modarresi teaches all of the limitations of the method of claim 1 as noted above. Hu further teaches wherein the plurality of cookies are website cookies (Hu, section 1 – teaches the cookies are website cookies).
It would have been obvious to one of ordinary skill in the art before the filing data of the claimed invention to combine the teachings of Hu and Modarresi for the same reasons as disclosed in claim 1 above.
Regarding claim 10 (Currently Amended), it is the computer-readable medium embodiment of claim 1 with similar limitations to claim 1 and is rejected using the same reasoning found in claim 1. Hu further teaches non-transitory computer-readable medium storing a computer program that, when executed by a processor (Hu, section 3 – teaches collecting browser cookies from websites [This necessarily requires the use of a computer]), causes the processor to perform a method for large scale categorization of cookies (Hu, section 3.2 – teaches method of cookie categorization) …
It would have been obvious to one of ordinary skill in the art before the filing data of the claimed invention to combine the teachings of Hu and Modarresi for the same reasons as disclosed in claim 1 above.
Regarding claim 13 (Original), the rejection of claim 10 is incorporated herein. Further, the limitations in this claim are taught by Hu in view of Modarresi for the reasons set forth in the rejection of claim 4.
Regarding claim 14 (Currently Amended), the rejection of claim 10 is incorporated herein. Further, the limitations in this claim are taught by Hu in view of Modarresi for the reasons set forth in the rejection of claim 5.
Regarding claim 16 (Original), the rejection of claim 10 is incorporated herein. Further, the limitations in this claim are taught by Hu in view of Modarresi for the reasons set forth in the rejection of claim 7.
Regarding claim 17 (Currently Amended), the rejection of claim 10 is incorporated herein. Further, the limitations in this claim are taught by Hu in view of Modarresi for the reasons set forth in the rejection of claim 8.
Regarding claim 19 (Currently Amended), it is the system of claim 1 with similar limitations to claim 1 and is rejected using the same reasoning found in claim 1. Hu further teaches a system for large scale categorization of cookies (Hu, section 3.2 – teaches method of cookie categorization) comprising:
a processing subsystem hosted on a server and configured to execute on a network to control bidirectional communications among a plurality of modules (Hu, section 3 – teaches collecting browser cookies from websites [This necessarily requires the use of a computer]) …
It would have been obvious to one of ordinary skill in the art before the filing data of the claimed invention to combine the teachings of Hu and Modarresi for the same reasons as disclosed in claim 1 above.
Claim(s) 2, 6, 11, 15, 20 is/are rejected under 35 U.S.C. 103 as being unpatentable over Hu in view of Modarresi and further in view of Shinde et al. (US 2020/0110904 A1 – Method and System for Providing Data Privacy Based on Customized Cookie Consent, hereinafter referred to as “Shinde”).
Regarding claim 2 (Original), Hu in view of Modarresi teaches all of the limitations of the method of claim 1 as noted above. However, Hu in view of Modarresi does not explicitly teach wherein the plurality of classes from the third table and the fourth table, upon prediction, are merged together with precedence to manually categorized cookies and subsequently storing the third table and the fourth table, upon merging, into a fifth table.
Shinde teaches wherein the plurality of classes from the third table and the fourth table, upon prediction, are merged together with precedence to manually categorized cookies and subsequently storing the third table and the fourth table, upon merging, into a fifth table (Shinde, [0039] – teaches storing classified entity cookies [fourth table] in the historical database of classified cookies [third table] creating a combined database of all cookies [fifth table]).
It would have been obvious to one of ordinary skill in the art before the filing date of the claimed invention to modify Hu in view of Modarresi with the teachings of Shinde in order to improve existing services for customers in the field of website cookie categorization (Shinde, [0003] – “Digital and internet world comprises of exhaustive types of data that also includes personal information. In today's competitive digital world, to enable innovative solutions and improvement in existing services for customers, the exhaustive personal data is collected, stored and coupled with emerging techniques of big data and analytics to performing analytics, market decisions, and research. The personal data can be collected from the digital internet by several ways, of which cookies are most popular.”).
Regarding claim 6 (Currently Amended), Hu in view of Modarresi and further in view of Shinde teaches all of the limitations of the method of claim 2 as noted above. Shine further teaches wherein the fifth table comprises the categorization of the plurality of cookies and metadata used for subsequent training of the one or more machine learning techniques (Shinde, [0039] – teaches using the combined database [fifth table] for future actions regarding entities [including updating models]; see also Shinde, [0037] – teaches using the historic database [fifth table after combination] for machine learning techniques).
It would have been obvious to one of ordinary skill in the art before the filing date of the claimed invention to combine the teachings of Hu, Modarresi and Shinde in order to use the combined datasets to improve existing services (Shinde, [0003]).
Regarding claim 11 (Original), the rejection of claim 10 is incorporated herein. Further, the limitations in this claim are taught by Hu in view of Modarresi and further in view of Shinde for the reasons set forth in the rejection of claim 2.
Regarding claim 15 (Currently Amended), the rejection of claim 11 is incorporated herein. Further, the limitations in this claim are taught by Hu in view of Modarresi and further in view of Shinde for the reasons set forth in the rejection of claim 6.
Regarding claim 20 (Original), the rejection of claim 19 is incorporated herein. Further, the limitations in this claim are taught by Hu in view of Modarresi and further in view of Shinde for the reasons set forth in the rejection of claim 2.
Claim(s) 3, 12 is/are rejected under 35 U.S.C. 103 as being unpatentable over Hu in view of Modarresi and further in view of Kaizer et al. (Towards Automatic Identification of JavaScript-Oriented Machine-Based Tracking, hereinafter referred to as “Kaiser”).
Regarding claim 3 (Currently Amended), Hu in view of Modarresi teaches all of the limitations of the method of claim 1 as noted above. However, Hu in view of Modarresi does not explicitly teach wherein the information about the plurality of cookies is automatically retrieved from the second source by crawling the plurality of websites with a special plugin and subsequently storing the information in the second table.
Kaizer teaches wherein the information about the plurality of cookies is automatically retrieved from the second source by crawling the plurality of websites with a special plugin and subsequently storing the information in the second table (Kaizer, section 2 – teaches using a web crawler browser plug-in to acquire cookie data).
It would have been obvious to one of ordinary skill in the art before the filing date of the claimed invention to modify Hu in view of Modarresi with the teachings of Kaiser in order to improve website tracking in the field of website cookie categorization (Kaizer – “Machine-based tracking is a type of behavior that extracts information on a user's machine, which can then be used for fingerprinting, tracking, or profiling purposes. In this paper, we focus on JavaScript-oriented machine-based tracking as JavaScript is widely accessible in all browsers. We find that coarse features related to JavaScript access, cookie access, and URL length/subdomain information can perform well in a supervised machine learning classifier that can identify machine-based trackers with 97.7% accuracy. We then use the classifier on real-world datasets based on 30-minute website crawls of different types of websites - including websites that target children and websites that target a popular audience - and find 85%+ of all websites utilize machine-based tracking, even when they target a regulated group (children) as their primary audience.”).
Regarding claim 12 (Currently Amended), the rejection of claim 10 is incorporated herein. Further, the limitations in this claim are taught by Hu in view of Modarresi and further in view of Kaizer for the reasons set forth in the rejection of claim 3.
Claim(s) 9, 18 is/are rejected under 35 U.S.C. 103 as being unpatentable over Hu in view of Modarresi and further in view of Kim et al. (Connecting Devices to Cookies via Filtering, Feature Engineering, and Boosting, hereinafter referred to as “Kim”).
Regarding claim 9 (Currently Amended), Hu in view of Modarresi teaches all of the limitations of the method of claim 1 as noted above. However, Hu in view of Modarresi does not explicitly teach wherein the one or more machine learning techniques are Ensemble Deep Learning modelling approach and End-to-End Deep Learning modelling approach.
Kim teaches wherein the one or more machine learning techniques are Ensemble Deep Learning modelling approach and End-to-End Deep Learning modelling approach (Kim, section IV – teaches using an ensemble model to classify cookies).
It would have been obvious to one of ordinary skill in the art before the filing date of the claimed invention to modify Hu in view of Modarresi with the teachings of Kim in order to match devices to improve targeted markets and recommendations in the field of website cookie categorization (Kim, section I – “Record linkage, also known as entity resolution, is the task of connecting the different representations of the same object. The task in ICDM 2015: Drawbridge Cross-Device Connections challenge is similar to the entity resolution problem. The objective of this contest is to link devices and cookies such that the F0.5 score is maximized. This allows the client organization to determine the probability that two digital devices are used by the same person. A machine learning system that can identify users across devices could be useful in targeted marketing and recommendation engines. This paper explores the development and testing of a machine learning system in R/Python to address the ICDM 2015: Drawbridge Cross-Device Connections competition. The ideas presented in this paper obtained a private F0.5 score of 0.849562 for a final rank of 12th/340. The Kaggle competition platform computes this final rank on private data where the ground truth is withheld from the competitors. We believe these results are robust given our local ten-fold cross validation showed a mean area under the receiver operating characteristic curve (AUC) of 0.982.”).
Regarding claim 18 (Currently Amended), the rejection of claim 10 is incorporated herein. Further, the limitations in this claim are taught by Hu in view of Modarresi and further in view of Kim for the reasons set forth in the rejection of claim 9.
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 communication from the examiner should be directed to MARSHALL WERNER whose telephone number is (469) 295-9143. The examiner can normally be reached on Monday – Thursday 7:30 AM – 4:30 PM ET.
If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Kamran Afshar, can be reached at (571) 272-7796. The fax number for the organization where this application or proceeding is assigned is (571) 273-8300.
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/MARSHALL L WERNER/ Primary Examiner, Art Unit 2125
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