DETAILED ACTION
This Office action is in response to a non-provisional utility patent application filed by Applicant on 9/16/2024.
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 .
Information Disclosure Statement PTO-1449
The Information Disclosure Statement submitted by applicant on 9/16/2024 has been considered. The submission is in compliance with the provisions of 37 CFR § 1.97. Form PTO-1449 signed and attached hereto.
Double Patenting
No conflicting application or issued patent was identified that would require a rejection under double patenting.
Claim Rejections - 35 USC § 101
35 U.S.C. 101 reads as follows:
Whoever invents or discovers any new and useful process, machine, manufacture, or composition of matter, or any new and useful improvement thereof, may obtain a patent therefor, subject to the conditions and requirements of this title.
Claims 1–5, 8–12, 14–16, 18–20 rejected under 35 U.S.C. 101 because the claimed invention is directed to non-statutory subject matter. The claims do not fall within at least one of the four categories of patent eligible subject matter because the claimed invention is directed to a judicial exception (i.e., a law of nature, a natural phenomenon, or an abstract idea) without significantly more.
The analysis is guided by the Supreme Court’s two-step framework, described in Mayo and Alice (Alice Corp. Pty Ltd. v. CLS Bank Int’l, 134 S. Ct. 2347, 2354 (2014) and Mayo Collaborative Servs. v. Prometheus Labs., Inc., 132 S. Ct. 1289, 1296-97 (2012)). Please see the Interim Guidance on Patent Subject Matter Eligibility (December 2014).
STEP 1: Are the claims directed to a process, machine, manufacture, or composition of matter? Yes. Independent claims 1, 14, and 18 recite a series of acts for detecting data leakage. Thus, the claim is directed to a process, which is one of the statutory categories of invention.
STEP 2A: Are the claims directed to a law of nature, a natural phenomenon, or an abstract idea, i.e., judicially recognized exceptions (both individually and as an ordered combination)? Yes. The steps of identifying statements, determining whether the identified statement is public or private, and determining whether the identified statement is true or false amounts to abstract ideas beyond the scope of 101.
The Eligibility Guidance for Identifying Abstract Ideas provides a standard for analyzing claims in view of the Alice/Mayo framework and informed by concepts held to be abstract ideas in Supreme Court and Federal Circuit eligibility decisions based upon common characteristics. Under this analysis the claimed invention is analogous to a mental process using pen and paper.
STEP 2B: Do the claims recite additional elements that amount to significantly more than the judicial exception(s)? No. The additional limitations do not integrate the abstract idea into a practical application. The receiving and extracting are merely insignificant pre-solution activity (data gathering steps).
The recited “knowledge graph is not defined as a particular computer data structure, nor does the claim define how it is generated.
The additional limitations are merely insignificant pre-solution activity and moreover, the extracting data from at least one service is well-understood, routine, and conventional. The Examiner asserts official notice that web scraping is well-understood, routine, and conventional. Hence, the additional limitations do not amount to significantly more than the exception.
The dependent claims 2–5, 8–12, 15–16, and 19–20 inherit the deficiencies of the claims upon which they ultimate claim and provide only limited additional functionality, which does not rise above the threshold of this step’s analysis. The analysis provided above applies to each of the claims and are rejected as well.
Claims 2, 4–5 and 8–12 are recitations of mental steps that can be performed with pen and paper.
Claim 3 relates to well-understood, routine, and conventional web scraping.
Claims 14 and 18 are CRM and system claims, respectively, that correspond to claim 1. They merely implement the abstract idea on a conventional computing medium and computing device. These additional limitation merely use a medium storing software and a computing device as a tool to perform the abstract idea.
Finally, claims 15–16 and 19–20 are further recitations of mental steps.
Claim Rejections - 35 USC § 103
The following is a quotation of 35 U.S.C. 103 which forms the basis for all obviousness rejections set forth in this Office action:
A patent for a claimed invention may not be obtained, notwithstanding that the claimed invention is not identically disclosed as set forth in section 102, if the differences between the claimed invention and the prior art are such that the claimed invention as a whole would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to which the claimed invention pertains. Patentability shall not be negated by the manner in which the invention was made.
Claims 1, 3, 10, 14, 18 rejected under 35 U.S.C. 103 as being unpatentable over Pan (PAN, Jeff Z. et al., "Content Based Fake News Detection Using Knowledge Graphs", 18 September 2018, The Semantic Web - ISWC 2018, LNCS 11136, 2018, (pp. 669-683, 15 total pages), See IDS filed 9/16/2024) in view of Azadani (US 2020/0387836 A1, published Dec. 10, 2020).
Regarding claims 1, 14, and 18, Pan discloses: a computer-implemented method for detecting data leakage and/or detecting dangerous information, the method comprising: receiving a knowledge graph (generating a knowledge graph from a corpus of data. Pan § 4.1, p. 673.); extracting data from at least one network service (receiving a new article. Pan § 4.2, p. 675.); identifying statements in the extracted data (extracting triples from the news article. Pan § 4.2, p. 675 and § 5.2, pp. 678–9.); for each identified statement: determining whether the identified statement is true or false using the knowledge graph (fake news detection using various models. Pan § 5.3, p. 680.).
Pan does not disclose: determining whether the identified statement is public or private using the knowledge graph.
However, Azadani does disclose: determining whether the identified statement is public or private using the knowledge graph (monitoring and testing output from a language model for safety, which includes data privacy monitoring and testing. Azadani Figure 15, element 1530 and ¶ 35.).
Therefore, it would have been prima facie obvious to one of ordinary skill in the art prior to the effective filing date of the claimed invention to modify the monitoring of outputs from a knowledge graph for veracity of the data of Pan with monitoring the output for whether data is public or private based upon the teachings of Azadani. The motivation being to increase reliability and safety of the output information from a machine learning model. Azadani ¶ 22.
Regarding claim 3, Pan in view of Azadani discloses the limitations of claim 1, wherein the at least one network service includes one or more of the following: a web service, a social networking service, a service providing an interface to a language model; wherein extracting data from the at least one network service comprises accessing at least one application programming interface via the at least one network service; wherein extracting data from the at least one network service comprises web scraping using the Hypertext Transfer Protocol, wherein the web scraping may comprise web crawling (receiving a news article would be understood to be commonly sources from some type of web service and extracting triples would be known to be the work of an application. Pan § 4.2 p. 675, § 4.2 p. 675, and § 5.2 pp. 678–9. The reference discusses scraping data from web services for building knowledge graphs, but the same technique is well known and could be applied to the extracting data for verification. Pan § 5.1 p. 677.).
Regarding claim 10, Pan in view of Azadani discloses the limitations of claim 1, wherein determining whether the identified statement is true or false (fake news detection using various models. Pan § 5.3, p. 680.) and determining whether the identified statement is public or private comprises comparing the identified statement with statements in the knowledge graph (monitoring and testing output from a language model for safety, which includes data privacy monitoring and testing. Azadani Figure 15, element 1530 and ¶ 35.).
Claims 2, 13, 15, 17, 19 rejected under 35 U.S.C. 103 as being unpatentable over Pan in view of Azadani in view of Adir (US 2024/0121074 A1, published Apr. 11, 2024).
Regarding claims 2, 15 and 19, Pan in view of Azadani discloses the limitations of claim 1, 14, and 18, respectively. Pan in view of Azadani does not disclose: wherein determining whether the identified statement is true or false using the knowledge graph comprises determining whether a subject-predicate combination of the identified statement has a maximum cardinality; when the maximum cardinality of the subject-predicate combination of the identified statement is exceeded, determining that the identified statement is false.
However, Adir does disclose: wherein determining whether the identified statement is true or false using the knowledge graph comprises determining whether a subject-predicate combination of the identified statement has a maximum cardinality; when the maximum cardinality of the subject-predicate combination of the identified statement is exceeded, determining that the identified statement is false (the tuple is determined to be true if the relation distance is below a certain threshold within the knowledge graph. Adir ¶ 45.).
Therefore, it would have been prima facie obvious to one of ordinary skill in the art prior to the effective filing date of the claimed invention to modify the monitoring of outputs from a knowledge graph for veracity of the data of Pan with determining truth or false based upon a knowledge graph distance threshold based upon the teachings of Adir. The motivation being to associate consistency and validity based upon measuring the distance between data on a formal language model structure.
Regarding claims 13 and 17, Pan in view of Azadani discloses the limitations of claims 1 and 14, respectively. Pan in view of Azadani does not disclose: wherein extracting data from the at least one network service comprises randomly selecting a statement from the knowledge graph; wherein the method further comprises: constructing a query string based on a subject and a predicate of the statement; calling, using a base uniform resource locator, at least one application programming interface via the at least one network service and using the query string.
However, Adir does disclose: wherein extracting data from the at least one network service comprises randomly selecting a statement from the knowledge graph (randomly selected samples of the tuples from the knowledge graph. Adir ¶ 78.); wherein the method further comprises: constructing a query string based on a subject and a predicate of the statement (a query is generated based upon the subject-predicate relationship. Adir ¶ 112.); calling, using a base uniform resource locator, at least one application programming interface via the at least one network service and using the query string (Adir ¶ 40.).
Therefore, it would have been prima facie obvious to one of ordinary skill in the art prior to the effective filing date of the claimed invention to modify the monitoring of outputs from a knowledge graph for veracity of the data of Pan with extracting randomly selected statements and constructing a query based upon a subject and predicate and using a URL to interface with the network service based upon the teachings of Adir. The motivation being to allow embedding tools into a machine learning knowledge graph.
Claims 12, 16, 20 rejected under 35 U.S.C. 103 as being unpatentable over Pan in view of Azadani in view of Srinivasan (US 2009/0012842 A1, published Jan. 8, 2009).
Regarding claims 12, 16, and 20, Pan in view of Azadani discloses the limitations of claims 1, 14, and 18, respectively. Pan in view of Azadani does not disclose: wherein each statement of the knowledge graph includes a subject-predicate-object triple, wherein each subject-predicate-object triple is composed of a subject, a predicate and an object, wherein the subject, the predicate and the object are each represented by a uniform resource identifier.
However, Srinivasan does disclose: wherein each statement of the knowledge graph includes a subject-predicate-object triple, wherein each subject-predicate-object triple is composed of a subject, a predicate and an object, wherein the subject, the predicate and the object are each represented by a uniform resource identifier (facts in the file are referenced using a URI and include a triple of subject, object, and predicate. Srinivasan ¶¶ 87–89 and 95.).
Therefore, it would have been prima facie obvious to one of ordinary skill in the art prior to the effective filing date of the claimed invention to modify the monitoring of outputs from a knowledge graph for veracity of the data of Pan with including subject, predicate, object triples in knowledge graphs that are referenced using uniform resource identifiers based upon the teachings of Srinivasan. The motivation being to access data blocks formally and quickly.
Allowable Subject Matter
The Examiner notes that claims 4–5, 8–9, and 11 are under the subject matter eligibility rejection of 35 U.S.C. 101 above. However, these claims would be objected to were the subject matter eligibility issues be overcome, meaning that from a prior art standpoint, they would be dependent upon a rejected base claim, but would be allowable if rewritten in independent form including all of the limitations of the base claim and any intervening claims.
Claims 6–7 are objected to as being dependent upon a rejected base claim, but would be allowable if rewritten in independent form including all of the limitations of the base claim and any intervening claims.
Conclusion
Any inquiry concerning this communication or earlier communications from the examiner should be directed to VANCE M LITTLE whose telephone number is (571) 270-0408. The examiner can normally be reached on Monday - Friday 9:30am - 5:30pm.
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/VANCE M LITTLE/Primary Examiner, Art Unit 2493