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 .
DETAILED ACTION
This Office Action is sent in response to Application’s Communication received on 06/05/2023 for application number 18/328977. The Office hereby acknowledges receipt of the following and placed of record in file: Specification, Drawing, Abstract, Oath/Declaration, and Claims.
Claims (1-10), (11-15) and (16-20) are presented for examination.
Information Disclosure Statement
The information disclosure statements (IDS) submitted on 06/05/2023 was filed prior to current Office Action. The submission is in compliance with the provisions of 37 CFR 1.97. Accordingly, the information disclosure statement is being considered by the examiner.
Allowable Subject Matter
Claims (1-10), (11-15) and (16-20) are directed to allowable subject matter if 101 rejection is addressed.
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 therefore, subject to the conditions and requirements of this title.
Claims (1-10), (11-15) and (16-20) are rejected under 35 U.S.C. 101 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.
Step 1: Claims (1-10), (11-15) and (16-20) are drawn to a method each of which is within the four statutory categories (e.g., a process, a machine).
Step 2A - Prong One: In prong one of step 2A, the claims are analyzed to evaluate whether they recite a judicial exception.
Claim 1.
obtaining an initial knowledge graph comprising nodes representing a plurality of entities and edges representing relationships between related entities of the plurality of entities;
building a dataset based on the initial knowledge graph, the dataset indicating, for each related entity pair, of a collection of related entity pairs, between which a relationship exists as represented in the initial knowledge graph:
at least one attribute and at least one attribute value of a first entity of the related entity pair;
at least one attribute and at least one attribute value of a second entity of the related entity pair;
a relationship type of the relationship between the related entity pair; and
a weight of the relationship type;
using the dataset to build a collection of machine learning models for identifying missing relationship information, the collection of machine learning models comprising at least one clustering model and at least one classification model;
receiving a partial specification of a new relationship triple to include in the initial knowledge graph, the new relationship triple comprising a new source entity, a target entity, and a relationship type of a relationship between the new source entity and the target entity, wherein the partial specification of the new relationship triple comprises a specification of the new source entity and is missing at least some relationship information of the new relationship triple;
applying one or more machine learning models of the collection of machine learning models and identifying the missing at least some relationship information of the new relationship triple to provide a complete specification of the new relationship triple; and
augmenting the initial knowledge graph using the complete specification of the new relationship triple, the augmenting providing an augmented knowledge graph that includes the new relationship triple, including the new source entity, the target entity, and the relationship type of the relationship between the new source entity and the target entity.
Claim 1 recites a judicial exception because it includes limitations directed to obtaining relationship information, organizing the information into dataset, identifying missing relationship information from partial relationship triple, and augmenting a knowledge graph, which are mental processes that can practically be performed in the human mind. The claim also recites mathematical concepts through building and applying machine learning models, including clustering and classification models, which involve mathematical calculations such grouping, scoring and classifying data based on numerical attributes or relationships.
The steps of “obtaining relationship information”, “organizing it into dataset”, “evaluating incomplete relationship information”, “identifying missing relationship information, and updating a knowledge graph” are defined are mental process.
The steps of “building machine learning models”, “classification model” and “applying machine learning modes” are defined a mathematical concept.
Similarly, the same rational applies to claims 11 and 16.
MPEP 2106.04(a)(2).I.C states:
. . . A mathematical calculation is a mathematical operation (such as multiplication) or an act of calculating using mathematical methods to determine a variable or number, e.g., performing an arithmetic operation such as exponentiation. There is no particular word or set of words that indicates a claim recites a mathematical calculation. That is, a claim does not have to recite the word "calculating" in order to be considered a mathematical calculation.
Step 2A Prong 2:
Claim 1 recites additional elements such as “memory” and “processor” which are recited at a high level, the elements are merely reciting the words that pertain to a generic computer (or an equivalent) with the judicial exception, or merely including instructions to implement an abstract idea on a computer, or merely using a computer as a tool to perform an abstract idea, as discussed in MPEP § 2106.05(f). The additional element(s) amount to merely the words “apply it” (or an equivalent) or are mere instructions to implement an abstract idea or other exception on a computer. The limitation does not integrate the judicial exception into a practical application.
Dependent claims (2-10), (12-15) and (17-20) fail to include any additional elements. In other words, each of the limitations/elements recited in respective dependent claims (2-13), (15-20), (22-25) and (29-30) are further part of the abstract idea as identified by the Examiner for each respective dependent claim (i.e. they are part of the abstract idea recited in each respective claim).
The Examiner has therefore determined that the elements, or combination of additional elements, do not integrate the abstract idea into a practical application. Accordingly, the claims are directed to an abstract idea.
Step 2B: The claim does not provide an inventive concept (significantly more than the abstract idea). The claim is ineligible.
The “memory” and “processor” which are recited at a high level and are steps considered insignificant extra solution activity. The limitations are mere data gathering and output input data that is recited at a high level of generality and amount to processing input data using devices that are recited at high level of generality using a generic computer. Even when considered in combination, the additional elements represent mere instructions to apply an exception and insignificant extra-solution activity, which cannot provide an inventive concept.
Dependent claims (2-10), (12-15) and (17-20) fail to include any additional elements. In other words, each of the limitations/elements recited in respective dependent claims (2-13), (15-20), (22-25) and (29-30) are further part of the abstract idea as identified by the Examiner for each respective dependent claim (i.e. they are part of the abstract idea recited in each respective claim).
The Examiner has therefore determined that the elements, or combination of additional elements, do not integrate the abstract idea into a practical application. Accordingly, the claims are directed to an abstract idea.
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure.
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/HASSAN MRABI/Examiner, Art Unit 2144
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