DETAILED ACTION
Notice of Pre-AIA or AIA Status
The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
The following action is in response to the amendment and remarks of 12/08/2025.
Claims 1, 4, 8 and 11 have been amended. Claim 15 has been newly added.
Claims 1-15 are pending and have been considered below.
Response to Arguments
Regarding the drawing objection (Non-Final Rejection 10/01/2025 page 2), the drawing objection has been withdrawn in light of the drawing amendment and corresponding remarks.
Regarding the 35 USC 103 rejection of claims 1-6 and 8-13 over WILLIAMS in view of JETHWA (Non-Final Rejection pages 4-7) and 35 USC 103 rejection of claims 7 and over WILLIAMS in view of JETHWA and in further view of BODIN (Non-Final Rejection pages 7-8), Applicant argues that none of WILLIAMS, JETHWA or BODIN disclose or render obvious the amended features of claim 1 including: “generate clusters of knowledge graph nodes according to the identified functionality such that the knowledge graph nodes are delineated into the clusters differing according to the identified functionality; and a graphical user interface configured to display an AI-based assistant feature that receives user queries related to classification of components according to functionality, the knowledge graph nodes being altered to indicate which of the clusters that the knowledge graph nodes belong to”. The Examiner respectfully disagrees.
Applicant argues (Remarks page 9-10) that JETHWA, relied on to teach the clustering of the knowledge graph nodes according to identified functionality, fails to disclose or render the amended feature of claim 1 when combined with WILLIAMS and/or BODIN because any alleged clustering does not result in the knowledge graph nodes being delineated into clusters differing according to the identified functionality. The Examiner notes that JETHWA does disclose utilizing clustering algorithms for making recommendations (¶63: “In some embodiments, the recommendations can be determined using similarity-based algorithms, such as minimal distance algorithms, clustering algorithms, and/or nearest neighbor algorithms. The determined recommendations can be tasks, suggestions, executable or callable functionality, and/or domain-specific assets that are most semantically or contextually relevant to the domain-specific entities included in graph 245 and/or the query input 240. ”). JETHWA discloses that the UI displaying the knowledge graph can be generated and re-generated based on interactions by the user such that nodes of similar functionality are displayed in a related cluster (¶73: “In some embodiments, the rendering algorithms can include algorithms associated with the domain-specific entities 205 corresponding to the nodes and edges displayed in graph 245. For example, algorithms that can display a plurality of oil and gas wells in a cluster related to an operation performed by the well, or algorithms to display network traffic between organization data centers, or algorithms to display API calls and invocations to a server configured with hosted, license-authenticated modeling and simulation software used in energy production modeling.”). This clearly anticipates the amended features of claim 1 including delineating the nodes of the knowledge graph into clusters differing by functionality and displaying the nodes as altered to indicate the cluster. The argument is not persuasive.
Applicant further argues (Remarks page 10-11) that the GUI of WILLIAMS does not display the knowledge graph nodes being altered to indicate which of the clusters that the knowledge graph belongs to. The Examiner agrees that WILLIAMS does not explicitly disclose this feature, however this feature is taught by JETHWA. JETHWA meets the deficiencies of WILLIAMS and combines reasonably as stated in the 35 USC 103 rejection below which has been updated to reflect the amendment.
Claim Rejections - 35 USC § 103
In the event the determination of the status of the application as subject to AIA 35 U.S.C. 102 and 103 (or as subject to pre-AIA 35 U.S.C. 102 and 103) is incorrect, any correction of the statutory basis (i.e., changing from AIA to pre-AIA ) for the rejection will not be considered a new ground of rejection if the prior art relied upon, and the rationale supporting the rejection, would be the same under either status.
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.
This application currently names joint inventors. In considering patentability of the claims the examiner presumes that the subject matter of the various claims was commonly owned as of the effective filing date of the claimed invention(s) absent any evidence to the contrary. Applicant is advised of the obligation under 37 CFR 1.56 to point out the inventor and effective filing dates of each claim that was not commonly owned as of the effective filing date of the later invention in order for the examiner to consider the applicability of 35 U.S.C. 102(b)(2)(C) for any potential 35 U.S.C. 102(a)(2) prior art against the later invention.
Claims 1-6, 8-13 and 15 are rejected under 35 U.S.C. 103 as being unpatentable over WILLIAMS, WO 2019103775 A1 [previously presented] in view of JETHWA, US 2019/0121801 A1 [previously presented].
Regarding claim 1, WILLIAMS discloses a system for computer aided design (¶5), comprising:
a computing device comprising a processor; and
a memory having modules stored thereon for execution by the processor (¶10), comprising:
an engineering software tool configured to construct a graphical design of an industrial system for a design project (¶21);
an artificial intelligence (AI) module integrated with the engineering tool during a current project (¶25), configured to communicate with a remote server-based Al module (¶39) having a trained machine learning-based model that classifies components for a current project with contextualization according to functionality (¶25), the remote Al module configured to:
receive a knowledge graph for the current project based on data associated with the graphical design (¶24), the knowledge graph comprising nodes and edges includes the plurality of components (¶25);
identify a functionality for each knowledge graph node based on the classifier model (¶25); and
a graphical user interface configured to display an AI-based assistant feature that receives user queries related to classification of components according to functionality (¶30-31); and
wherein the remote Al module generates functionality-based recommendations based on the clusters in response to the queries (¶29-30).
WILLIAMS fails to disclose explicitly disclose wherein the nodes and edges of the knowledge graph represent an ontology for a set of elements and relationships, wherein clusters of knowledge graph nodes are generated according to the identified functionality such that the knowledge graph nodes are delineated into clusters differing according to the identified functionality and the GUI displays the nodes as altered to indicate the different clusters.
JETHWA discloses methods for generating recommendations based on semantic knowledge graphs (¶2). In particular JETHWA discloses knowledge graphs representing ontological data comprising elements and relationship between elements (¶44) and further wherein recommendations can be made by applying clustering algorithms (¶63) such that the nodes of the displayed knowledge graph are delineated to different clusters based on functionality and a recommendation GUI displays the nodes as altered to indicate such (¶73). Accordingly it would have been obvious to one having ordinary skill in the art and the teachings of WILLIAMS and JETHWA before them before the effective filing of the claimed invention to combine the known teachings of knowledge graphs comprising ontological relationships and knowledge graph recommendations based on clustering techniques such that a recommendation GUI displays nodes as delineated clusters, as suggested by JETHWA, with the knowledge graph recommendations GUI of WILLIAMS. One would have been motivated to make this combination in order to utilize well known concepts in a predictable manner to achieve predictable results such as when making recommendations based on knowledge graphs through a user interface, as suggested by JETHWA (¶63).
Regarding claim 2, WILLIAMS and JETHWA disclose the system of claim 1, and JETHWA discloses wherein the remote Al module is further configured to generate a cluster diagram having distinct functionality clusters (¶73), the system further comprising:
a graphical user interface configured to display the cluster diagram as another AI-based assistant feature to provide a visual aid to the user with functionality classifications in the graphical design (Fig. 5B).
Regarding claim 3, WILLIAMS and JETHWA disclose the system of claim 1, and WILLIAMS further discloses wherein the remote Al module is further configured to:
identify missing information in the design based on the clustering (¶25-28); and
generate recommendations for the design on the AI-based assistant feature responsive to identifying missing information related to the design (¶29).
Regarding claim 4, WILLIAMS and JETHWA disclose the system of claim 1, and JETHWA further discloses further comprising:
an inference engine (¶39-42) configured to:
classify functionality of project components by extracting structure features from the knowledge graph and applying a rule based inference analysis to the extracted structure using rules stored in a rules database (¶44); and
send a message to the AI-based assistant feature with a textual description of the functional classification of the target component (¶82).
Regarding claim 5, WILLIAMS and JETHWA disclose the system of claim 1, and JETHWA further discloses wherein the Al module is further configured to:
receive a user query pertaining to functionality of a target component (¶81);
determine the functionality of the component based on the clustering in response to the query (¶81); and
send a message to the AI-based assistant feature with a textual description of the functional classification of the target component (¶82).
Regarding claim 6, WILLIAMS and JETHWA disclose the system of claim 1, and WILLIAMS further discloses wherein the remote Al module is further configured to:
detect gaps in the design project (¶26); and
send a message to the AI-based assistant feature notifying the user that one or more elements for a functionality cluster are missing (¶26).
Regarding claims 8-13, claims 8-13 recite limitations similar to claims 1-6, respectively, and are similarly rejected.
Regarding claim 15, WILLIAMS and JETHWA disclose the system of claim 1, and JETHWA further discloses wherein the remote Al module is configured to:
determine that a node of the knowledge graph nodes has a functionality that does not map to any of the clusters (¶50, ¶86, ¶88); and
in response to determining the node has the functionality that does not map to any of the clusters, recommend replacing the node with another node or removing the node from the current project (¶50, ¶86, ¶88: exclude nodes that are no longer required).
Claims 7 and 14 are rejected under 35 U.S.C. 103 as being unpatentable over WILLIAMS in view of JETHWA and in further view of BODIN, US 2020/0159950 A1 [previously presented].
Regarding claim 7, WILLIAMS and JETHWA disclose the system of claim 1, and JETHWA further discloses:
a mapping engine configured to map to the knowledge graph in the form of data metrics for compliance of components (¶42, ¶44); and
an inference engine configured to:
determine discrepancies between engineering data in the knowledge graph and the data metrics in the knowledge graph for a target component (¶42, ¶44); and
send a message to the AI-based assistant feature notifying the user that a potential non-compliance is detected for the target component (¶42, ¶44, ¶51).
Neither WILLIAMS or JETHWA explicitly disclose wherein the data metrics are in the form of regulation data, rules pertaining to policies, regulations, standards or a combination thereof.
BODIN discloses methods for AI assisted project design including recommendations (¶49-50, ¶62) . In particular, BODIN discloses analyzing data metrics, including compliance data representing policy standards, to determine non-compliance of a target project object and present the a recommended compliance action (¶336, ¶178). Therefore it would have been obvious to one having ordinary skill in the art and the teachings of WILLIAMS, JETHWA and BODIN before them before the effective filing of the claimed invention to combine the data metrics compliance determination of a project object, as suggested by BODIN, with the data metrics compliance determination of WILLIAMS and JETHWA. One would have been motivated to make this combination in order to expand functionality of an autonomous recommendations agent, as suggested by BODIN (¶292).
Regarding claim 14, claim 14 recites limitations similar to claim 7 and is similarly rejected.
Conclusion
Applicant's amendment necessitated the new ground(s) of rejection presented in this Office action. Accordingly, THIS ACTION IS MADE FINAL. See MPEP § 706.07(a). Applicant is reminded of the extension of time policy as set forth in 37 CFR 1.136(a).
A shortened statutory period for reply to this final action is set to expire THREE MONTHS from the mailing date of this action. In the event a first reply is filed within TWO MONTHS of the mailing date of this final action and the advisory action is not mailed until after the end of the THREE-MONTH shortened statutory period, then the shortened statutory period will expire on the date the advisory action is mailed, and any nonprovisional extension fee (37 CFR 1.17(a)) pursuant to 37 CFR 1.136(a) will be calculated from the mailing date of the advisory action. In no event, however, will the statutory period for reply expire later than SIX MONTHS from the mailing date of this final action.
Any inquiry concerning this communication or earlier communications from the examiner should be directed to ANDREW L TANK whose telephone number is (571)270-1692. The examiner can normally be reached Monday-Thursday 9a-6p.
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If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Matthew Ell can be reached at 571-270-3264. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
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/ANDREW L TANK/Primary Examiner, Art Unit 2141