CTFR 18/093,342 CTFR 100280 DETAILED ACTION Notice of Pre-AIA or AIA Status 07-03-aia AIA 15-10-aia The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA. This action is made final. Claims 1-6 are pending. Claims 1, 5 and 6 are independent claims. Response to Arguments Applicant’s arguments, dated 2/25/26, regarding the 35 USC 101 rejections of the previous office action have been fully considered but are unpersuasive. Due to the amendments, new grounds of rejection have been applied – see the updated 101 rejections below. Applicant argues that the claimed invention is directed to statutory subject matter. Examiner argues that any potential improvements are a direct result of applying mental determination steps, or a mentally measurable constraint to the generally recited machine learning process. Examiner notes that the judicial exception alone cannot provide the improvement (See MPEP 2106.05(a), ¶6). Applicant’s arguments, dated 2/25/26, regarding the 35 USC 103 rejections of the previous office action have been fully considered but are unpersuasive. Due to the amendments, new grounds of rejection have been applied – see the updated 103 rejections below. Claim Rejections - 35 USC § 112 07-30-02 AIA 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. 07-34-01 Claims 1, 5 and 6 are rejected under 35 U.S.C. 112(b) or 35 U.S.C. 112 (pre-AIA), second paragraph, as being indefinite for failing to particularly point out and distinctly claim the subject matter which the inventor or a joint inventor (or for applications subject to pre-AIA 35 U.S.C. 112, the applicant), regards as the invention. 07-34-05 AIA Claim 1 recites the limitation " determining, as the specific class, a class that entails a relation of another class ." in lines 22-23 . There is insufficient antecedent basis for this limitation in the claim. 07-34-05 AIA Claim 5 recites the limitation " determining, as the specific class, a class that entails a relation of another class ." in lines 22-23 . There is insufficient antecedent basis for this limitation in the claim. 07-34-05 AIA Claim 6 recites the limitation " determining, as the specific class, a class that entails a relation of another class ." in line 25 . There is insufficient antecedent basis for this limitation in the claim. Claim Rejections - 35 USC § 101 07-04-01 AIA 07-04 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 1-6 are rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more. Regarding claim 1: Step 1: This part of the eligibility analysis evaluates whether the claim falls within any statutory category. See MPEP 2106.03. Claim 1 recites: A non-transitory computer-readable recording medium having stored therein a program that causes a computer to execute a process comprising… Claim 1 is directed to an apparatus (Step 1: YES). Step 2A prong 1: Does the claim recite a judicial exception? Claim 1 recites: specifying a first triple and a second triple included in a knowledge graph (specifying two triples in a knowledge graph is a mental process) ; determining which of the first triple and the second triple is associated with more specific information on the basis of at least one of a first comparison and a second comparison, the first comparison being a comparison between a first relation between first two entities included in the first triple and a second relation between second two entities included in the second triple in a specific set of classes included in the knowledge graph, (determining which triple is more specific based on a comparison between relations is a mental process) , the second comparison being a comparison between a first entity connected to any one of the first two entities and a second entity connected to any one of the second two entities (comparing two entities connected to the triples’ entities to determine specificity is a mental process) ; and when it is determined by the determining that the first triple is associated with the more specific information… a constraint that a difference in the vectors representing the elements of the first triple is smaller than a difference in the vectors representing the elements of the second triple (evaluating or satisfying a constraint that a difference in vectors of more specific information is smaller than a difference in vectors of less specific information is a mental process) , wherein the determining includes: determining entailment of the relation between entities that belong to each of a plurality of classes included in the knowledge graph (determining entailment of relations is mental process) : and comparing between the first relation and the second relation by determining, as the specific class, a class that entails a relation of another class (comparing between relations by evaluating a class entailment relation is a mental process) … These steps can be performed mentally or are mathematical calculations (Step 2A prong 1: YES). Step 2A prong 2: Does the claim recite additional elements? Do those additional elements, considered individually and in combination, integrate the judicial exception into a practical application? Claim 1 recites: performing machine learning of a machine learning model using the knowledge graph and… Performing machine learning of a model with a knowledge graph and a constraint that is capable of being evaluated mentally is recited at a high level of generality, i.e., as a generic computer performing generic computer functions. Further, the claim omits any details as to how the neural network model solves a technical problem and instead recites only the idea of a solution or outcome (see MPEP 2106.05(f)). Thus, the limitation represents no more than mere instructions to implement the abstract idea which is equivalent to adding the words “apply it” to the recited judicial exception (Step 2A prong 2: NO). Step 2B: These elements are recited at such a high level of generality that they fail to integrate the abstract idea into a practical application, since they provide nothing more than mere instructions to implement an abstract idea on a generic computer (MPEP 2106.05(f)). These limitations, taken either alone or in combination, fail to provide an inventive concept (Step 2B: NO). Thus, the claim is not patent eligible. Regarding claims 2-4, they recite limitations which further narrow the abstract idea by specifying more details of the mental and mathematical process that occurs (Claim 2, determining which triple is more specific using an entailment relation between the two relations is a mental process; Claim 3, determining sets of entities sharing the first relation and sets of entities sharing the second relation, and comparing the sets to see if the first set is encompassed by the other are mental processes; Claim 4, specifying a class that the first entity and second entity belong to on the basis of a hierarchical structure between classes of knowledge graph entities is a mental process, and determining that the first triple related to more specific information based on its class being on a lower layer of the hierarchical structure is also a mental process). Regarding claim 5, it is a method similar to the process implemented by the apparatus of claim 1 and is rejected on the same grounds – see above. Regarding claim 6, it is an apparatus that recites similar limitations to the apparatus of claim 1 and is rejected on the same grounds – see above. Claim Rejections - 35 USC § 103 07-20-aia AIA 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. 07-21-aia AIA Claim s 1, 2, 5 and 6 are rejected under 35 U.S.C. 103 as being unpatentable over Choudhury et al. (US 20180103052 A1), herein Choudhury, in view of Van Assel et al. (US 20210233658 A1), herein Van Assel, and Juric et al. (US 10846288 B2), herein Juric . Regarding claim 1, Choudhury teaches: A non-transitory computer-readable recording medium having stored therein a program that causes a computer to execute a process comprising: specifying a first triple and a second triple included in a knowledge graph (¶25, Given the a semantic graph representation of Wikipedia, we find the three following answers: Ford is a Car Manufacturer, Car Manufacturer make Cars, Cars contain Catalytic Convertors, Catalytic Convertors uses Palladium. Ford is a Manufacturer, Manufacturer makes Products, Products use Rare Earth Mineral, Palladium is a Rare Earth Mineral. Ford has headquarters USA, USA was involved in cold war with Russia, Russia is major supplier of Palladium ) ; determining which of the first triple and the second triple is associated with more specific information on the basis of at least one of a first comparison and a second comparison, the first comparison being a comparison between a first relation between first two entities included in the first triple and a second relation between second two entities included in the second triple in a specific set of classes included in the knowledge graph (¶28, Our ranking metrics indicate that the first answer has highest coherence and specificity. The second answer scores lower with specificity – and – ¶23, Another proposed metric is “Specificity”. Given a path composed of Cyber Knowledge Graph nodes, its specificity is measured in terms of the relative importance of the nodes, and the frequency (or rarity) of the relationships that connects them – i.e., specificity can be measured via a comparison involving the relations in two paths) , the second comparison being a comparison between a first entity connected to any one of the first two entities and a second entity connected to any one of the second two entities (¶24, While visiting a node during the walk, it involves exploring all the neighbors of the node to determine where to visit next. ) ; Choudhury fails to teach: and when it is determined by the determining that the first triple is associated with the more specific information, performing machine learning of a machine learning model using the knowledge graph and a constraint that a difference in the vectors representing the elements of the first triple is smaller than a difference in the vectors representing the elements of the second triple. However, in the same field of endeavor, Van Assel teaches: and when it is determined by the determining that the first triple (¶124, The Knowledge Base 150 may therefore be represented using triples, comprising subject, property and object, <Subject, Property, Object>, each of these mapping to a concept and an IRI. An example of one triple would be <Breast cancer, isA, Cancer> ) is associated with the more specific information, performing machine learning of a machine learning model using the knowledge graph and a constraint that a difference in the vectors representing the elements of the first triple is smaller than a difference in the vectors representing the elements of the second triple (¶115, The knowledge graph may keep track of the meaning behind medical terminology across different medical systems and different languages. The diagnostic engine 111 uses the medical knowledge encoded in the knowledge graph and calls the NLP module described above to turn the words input by the user into a form that can be understood by the model, i.e. concepts – and ¶325, An embedding for the target concept can then be generated from the existing embeddings of the similar concepts. Similar concepts in the knowledge base may be found in various ways. For example, concepts which are close in the ontology are more likely to have a close semantic meaning. The degree of information carried by a link depends also on its position, since the lower the concept is in the ontology hierarchy, the higher its specificity – i.e., vectors representing elements of the first triple will have a smaller height than vectors of elements of the second triple) . Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to perform machine learning using a knowledge graph and a constraint as disclosed by Van Assel in the apparatus disclosed by Choudhury to link concepts and update a knowledge store (¶292, The methods use statistics to create representations of the concepts taken from the text to build semantic models of context. The goal is to express a measure of how much information a concept can provide to a diagnosis, given the user input. This can then be used to rank the concepts for example – ¶331, the process may be performed in order to update existing embeddings ). Choudhury in view of Van Assel fails to teach: wherein the determining includes: determining entailment of the relation between entities that belong to each of a plurality of classes included in the knowledge graph: and comparing between the first relation and the second relation by determining, as the specific class, a class that entails a relation of another class . However, in the same field of endeavor, Juric, teaches: wherein the determining includes: determining entailment of the relation between entities that belong to each of a plurality of classes included in the knowledge graph: and comparing between the first relation and the second relation by determining, as the specific class, a class that entails a relation of another class (Col. 8, line 36, the further comparisons may comprise: a. Determining whether for each relation in the query concept, there is a relation in the candidate concept that subsumes it, and for each concept in the query concept there is a concept in the candidate concept that subsumes it – and – Col. 2, line 63, Simple concepts are also referred to as “Atomic Concepts” and in OWL jargon, concepts are also called “Classes” ). Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to utilize subsumption relations in knowledge structures as disclosed by Juric in the apparatus disclosed by Choudhury in view of Van Assel to increase information extraction (Col. 5, line 62, The above method compares (with reference to subsumption) concepts by exploiting “meaning” that is encoded in their text labels and axioms that are stated for the used entities in some background Knowledge Base ). Regarding claim 2, Choudhury in view of Van Assel fails to teach: The non-transitory computer-readable recording medium according to claim 1, wherein the determining includes, as the first comparison between the first relation and the second relation, determining which of the first triple and the second triple is associated with the more specific information by an entailment relation between the first relation and the second relation in the occurrence status in which, when the first relation exists between the entities in the specific set of classes, the second relation also exists. However, in the same field of endeavor, Juric teaches: wherein the determining includes, as the first comparison between the first relation and the second relation, determining which of the first triple and the second triple is associated with the more specific information by an entailment relation between the first relation and the second relation in the occurrence status in which, when the first relation exists between the entities in the specific set of classes, the second relation also exists (Col. 8, line 36, the further comparisons may comprise: a. Determining whether for each relation in the query concept, there is a relation in the candidate concept that subsumes it, and for each concept in the query concept there is a concept in the candidate concept that subsumes it – and – Col. 2, line 63, Simple concepts are also referred to as “Atomic Concepts” and in OWL jargon, concepts are also called “Classes” ) . Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to utilize subsumption relations in knowledge structures as disclosed by Juric in the apparatus disclosed by Choudhury in view of Van Assel to increase information extraction (Col. 5, line 62, The above method compares (with reference to subsumption) concepts by exploiting “meaning” that is encoded in their text labels and axioms that are stated for the used entities in some background Knowledge Base ). Regarding claim 5, it is a method that recites similar limitations to claim 1 and is rejected on the same grounds – see above. Regarding claim 6, it is an apparatus that recites similar limitations to claim 1 and is rejected on the same grounds – see above . 07-22-aia AIA Claim 3 is rejected under 35 U.S.C. 103 as being unpatentable over Choudhury in view of Van Assel and Juric as applied to claim 2 above, and further in view of Neumann (US 20210374828 A1) . Regarding claim 3, Choudhury in view of Van Assel and Juric fails to teach: The non-transitory computer-readable recording medium according to claim 2, wherein the determining includes specifying, as the first comparison between the first relation and the second relation, a plurality of sets the first two entities having the first relation and a plurality of sets of the second two entities having the second relation from a plurality of triples belonging to the specific set of classes, and determining that the first triple is associated with the more specific information when the plurality of sets of the first entities are included in the plurality of sets of the second two entities. However, in the same field of endeavor, Neumann teaches: a plurality of sets the first two entities having the first relation and a plurality of sets of the second two entities having the second relation from a plurality of triples belonging to the specific set of classes, and determining that the first triple is associated with the more specific information when the plurality of sets of the first entities are included in the plurality of sets of the second two entities (¶22, A clustering algorithm may include hierarchical clustering, where objects that belong to a child cluster also belong to a parent cluster – Neumann teaches clusters, which are groups of objects that are somehow related to each other, i.e., having a relation. The parent/child relationship between clusters implies different levels of specificity) . Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to utilize a hierarchical clustering style as disclosed by Neumann in the apparatus disclosed by Choudhury in view of Van Assel and Juric to highlight relations between data items (¶22, “clustering algorithm,” as used in this disclosure, is a machine-learning process that groups a set of objects that are more similar to each other to produce a cluster, than to those in other groups or clusters ) . 07-22-aia AIA Claim (s) 4 is/are rejected under 35 U.S.C. 103 as being unpatentable over Choudhury in view of Van Assel and Juric as applied to claim 1 above, and further in view of Jenson et al. (US 20210027175 A1), herein Jenson . Choudhury further teaches: The non-transitory computer-readable recording medium according to claim 1, wherein the determining includes specifying, as the second comparison between the first entity and the second entity, a first class to which the first entity belongs, and a second class to which the second entity belongs (¶25, Given the a semantic graph representation of Wikipedia, we find the three following answers: Ford is a Car Manufacturer , Car Manufacturer make Cars… Ford is a Manufacturer , Manufacturer makes Products – certain entities in the knowledge graph taught by Choudhury can be interpreted as classes to which other entities belong. In this case, the “Car Manufacturer” class appears to be a more specific example of the “Manufacturer” class, and the first example answer is said to rank highest on measures of coherence and specificity – ¶28, Our ranking metrics indicate that the first answer has highest coherence and specificity. The second answer scores lower with specificity, ) ... Choudhury in view of Van Assel and Juric fails to explicitly teach: on the basis of a hierarchical structure between classes to which entities included in the knowledge graph belong, and determining that the first triple is associated with the more specific information, when the first class is located in a lower layer than the second class. However, in the same field of endeavor, Jenson teaches: on the basis of a hierarchical structure between classes to which entities included in the knowledge graph belong (¶36, domain-specific instances 106 provide specific information relevant to a domain-specific class under which it is hierarchically organized ) , and determining that the first triple is associated with the more specific information, when the first class is located in a lower layer than the second class (¶36, In such embodiments, the particular depth of a subclass indicates the relative level of domain-specificity encoded by the contextual parameters and relationships defined within a given domain-specific ontology – and – Fig. 1, “Spatial” class in 102 above “Facility” class in 104). Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to utilize a hierarchical structure to organize classes as disclosed by Jenson in the apparatus disclosed by Choudhury in view of Van Assel and Juric to allow for automated processing and take advantage of existing relations (¶38, In embodiments, each specific context class in the general ontology shares common properties with the top level Context concept class, such as label, object type, name, and so on, allowing it to be easily automatically processed – and – ¶37, the relational schemas already defined in those ontologies are able to be leveraged ). Conclusion 07-40 AIA Applicant's amendment necessitated the new ground(s) of rejection presented in this Office action. Accordingly, THIS ACTION IS MADE FINAL . See MPEP § 706.07(a). Applicant is reminded of the extension of time policy as set forth in 37 CFR 1.136(a). A shortened statutory period for reply to this final action is set to expire THREE MONTHS from the mailing date of this action. In the event a first reply is filed within TWO MONTHS of the mailing date of this final action and the advisory action is not mailed until after the end of the THREE-MONTH shortened statutory period, then the shortened statutory period will expire on the date the advisory action is mailed, and any nonprovisional extension fee (37 CFR 1.17(a)) pursuant to 37 CFR 1.136(a) will be calculated from the mailing date of the advisory action. In no event, however, will the statutory period for reply expire later than SIX MONTHS from the mailing date of this final action. Any inquiry concerning this communication or earlier communications from the examiner should be directed to HARRISON CHAN YOUNG KIM whose telephone number is (571)272-0713. The examiner can normally be reached Monday - Thursday 10:00 am - 7:00 pm. 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If you would like assistance from a USPTO Customer Service Representative, call 800-786-9199 (IN USA OR CANADA) or 571-272-1000. /HARRISON C KIM/ Examiner, Art Unit 2145 /CESAR B PAULA/ Supervisory Patent Examiner, Art Unit 2145 Application/Control Number: 18/093,342 Page 2 Art Unit: 2145 Application/Control Number: 18/093,342 Page 3 Art Unit: 2145 Application/Control Number: 18/093,342 Page 4 Art Unit: 2145 Application/Control Number: 18/093,342 Page 5 Art Unit: 2145 Application/Control Number: 18/093,342 Page 6 Art Unit: 2145 Application/Control Number: 18/093,342 Page 7 Art Unit: 2145 Application/Control Number: 18/093,342 Page 8 Art Unit: 2145 Application/Control Number: 18/093,342 Page 9 Art Unit: 2145 Application/Control Number: 18/093,342 Page 10 Art Unit: 2145 Application/Control Number: 18/093,342 Page 11 Art Unit: 2145 Application/Control Number: 18/093,342 Page 12 Art Unit: 2145 Application/Control Number: 18/093,342 Page 13 Art Unit: 2145 Application/Control Number: 18/093,342 Page 14 Art Unit: 2145
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