DETAILED ACTION
Claims 1, 3-9, 11-16 and 18-20 are pending in this 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 .
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.
Claims 1, 13, 14 and 20 are rejected under 35 U.S.C. 103 as being unpatentable over Abrams et al. (US PGPUB No. 2013/0339385) [hereinafter “Abrams”] in view of Kraus et al. (US PGPUB No. 2017/0154108) [hereinafter “Kraus”] in further view of Fuller et al. (US PGPUB No. 2012/0290559) [hereinafter “Fuller”].
As per claim 1, Abrams teaches a method, comprising: receiving, at a data platform, information associated with activities within a network environment ([0016], network data stored at data sources across a federated system); generating a logical graph based on the information (Abstract, data source may a be graph database); storing data representative of the logical graph in a database ([0024], data stored at data source that includes graph databases); receiving, in response to a user interaction with an interface of the data platform, a request to filter the information ([0024], receiving a query to a data source on a federated system); in response to receiving the request, generating a query using a graph-based schema ([0024], generating an appropriate subquery for the data source including graph databases see Abstract); and performing the generated query against the database ([0024], returning the subquery results to the client system).
Abrams does not explicitly teach generating a logical graph based on the information, wherein the logical graph links login activity to at least one user and at least one process. Kraus teaches generating a logical graph based on the information, wherein the logical graph links login activity to at least one user and at least one process ([0058], a database schema with a graph representing a database structure populated with data linking and mapping network events to user login history and other relevant activity see [0070]).
At the time of filing, it would have been obvious to one of ordinary skill in the art to combine Abrams with the teachings of Kraus, generating a logical graph based on the information, wherein the logical graph links login activity to at least one user and at least one process, to populate the graph and database with various data as intended to take advantage of organizational and search functionality present in the logical graph and database.
The combination of Abrams and Kraus does not explicitly teach wherein generating the query comprises constructing a join graph that represents relationships of filter keys among entities; and traversing the edges of the join graph to create a final data filter set wherein the join graph includes a list of relationships among all possible implicit join groups. Fuller teaches wherein generating the query comprises constructing a join graph that represents relationships of filter keys among entities ([0055], generating a join graph that contains relationships between entity data see [0002] including classifications of the data, i.e. keys see [0003]); and traversing the edges of the join graph to create a final data filter set wherein the join graph includes a list of relationships among all possible implicit join groups ([0053], join graph lists all joined tables as implicit joins between groups of entity data see [0002]).
At the time of filing, it would have been obvious to one of ordinary skill in the art to combine Abrams and Kraus with the teachings of Fuller, wherein generating the query comprises constructing a join graph that represents relationships of filter keys among entities; and traversing the edges of the join graph to create a final data filter set wherein the join graph includes a list of relationships among all possible implicit join groups, to link entities in manner that improves query efficiency.
As per claim 13, the combination of Abrams, Kraus and Fuller teaches the method of claim 1, wherein the user interaction is with a query field of the interface (Abrams; Abstract, user interacts with database using his computer by querying the database which inherently has input fields).
As per claim 14, the substance of the claimed invention is identical or substantially similar to that of claim 1. Accordingly, this claim is rejected under the same rationale.
As per claim 20, the substance of the claimed invention is identical or substantially similar to that of claim 1. Accordingly, this claim is rejected under the same rationale.
Claims 3-9, 11-12 and 16, 18-19 are rejected under 35 U.S.C. 103 as being unpatentable over Abrams, Kraus and Fuller in view of Trappen et al. (US PGPUB No. 2004/0019599) [hereinafter “Trappen”].
As per claim 3, the combination of Abrams, Kraus and Fuller teaches the method of claim 1.
The combination of Abrams, Kraus and Fuller does not explicitly teach wherein generating the query is based on a join defining a group of filter keys of a same key type. Trappen teaches wherein generating the query is based on a join defining a group of filter keys of a same key type ([0147], entities with a labeled class and joined with the same class type).
At the time of filing, it would have been obvious to one of ordinary skill in the art to combine Abrams and Kraus with the teachings of Trappen, wherein generating the query is based on a join defining a group of filter keys of a same key type, to link entities in manner that improves query efficiency.
As per claim 4, the combination of Abrams, Kraus, Fuller and Trappen teaches the method of claim 3, wherein instances of the same type of filter key are formed as an implicit join group (Trappen; [0147], join is made as an implicit join since it read from the class table mapping).
As per claim 5, the combination of Abrams, Kraus, Fuller and Trappen teaches the method of claim 3, wherein a same instance of a filter key can participate in different implicit join groups (Trappen; [0143], a filter key can be combined and used in more than one join).
As per claim 6, the combination of Abrams, Kraus and Fuller teaches the method of claim 1
The combination of Abrams, Kraus and Fuller does not explicitly teach wherein generating the query comprises discovering join relations via a filter key specification. Trappen teaches wherein generating the query comprises discovering join relations via a filter key specification (Trappen; class table mapping).
At the time of filing, it would have been obvious to one of ordinary skill in the art to combine Abrams, Kraus and Fuller with the teachings of Trappen, wherein generating the query comprises discovering join relations via a filter key specification, to link entities in manner that improves query efficiency.
As per claim 7, the combination of Abrams, Kraus and Fuller teaches the method of claim 1
The combination of Abrams, Kraus and Fuller does not explicitly teach wherein generating the query is based on a join performed across at least one of event queries, network queries, or configuration queries. Trappen wherein generating the query is based on a join performed across at least one of event queries ([0061], context of join function involves tasks performed on abstract data types see also Abstract), network queries (Examiner Note: this is an optional feature but to expedite prosecution a potential citation is provided) ([0061], tasks are performed across network see also Abstract), or configuration queries (Examiner Note: this is an optional feature but could overcome the current rejection if included as a required feature along with the other options).
At the time of filing, it would have been obvious to one of ordinary skill in the art to combine Abrams, Kraus and Fuller with the teachings of Trappen, wherein generating the query is based on a join performed across at least one of event queries, network queries, or configuration queries, to link entities in manner that improves query efficiency.
As per claim 8, the combination of Abrams, Kraus and Fuller teaches the method of claim 1
The combination of Abrams, Kraus and Fuller does not explicitly teach wherein the join graph comprises a list of join links. Trappen teaches wherein the join graph comprises a list of join links ([0147], class table mapping).
At the time of filing, it would have been obvious to one of ordinary skill in the art to combine Abrams, Kraus and Fuller with the teachings of Trappen, wherein the join graph comprises a list of join links, to link entities in manner that improves query efficiency.
As per claim 9, the combination of Abrams, Kraus and Trappen teaches the method of claim 8, wherein a join link represents an implicit join group by a same filter key type (Trappen; [0149], classes in mapping represent groups with same filter key and represent an implicit join).
As per claim 11, the combination of Abrams, Kraus and Fuller teaches the method of claim 1
The combination of Abrams, Kraus and Fuller does not explicitly teach wherein the request is associated with target information useable to generate or update a visualization of at least a portion of the logical graph in the interface, the logical graph comprising a plurality of nodes interconnected by a plurality of edges, the plurality of nodes and the plurality of edges representative of the activities within the network environment. Trappen teaches wherein the request is associated with target information useable to generate or update a visualization of at least a portion of the logical graph in the interface ([0067], user uses display to interface with system), the logical graph comprising a plurality of nodes interconnected by a plurality of edges ([0126], constructing a DAG with nodes and edges), the plurality of nodes and the plurality of edges representative of the activities within the network environment ([0126], edges represents relationship between nodes operating network transactions see [0274]).
At the time of filing, it would have been obvious to one of ordinary skill in the art to combine Abrams, Kraus and Fuller with the teachings of Trappen, wherein the request is associated with target information useable to generate or update a visualization of at least a portion of the logical graph in the interface, the logical graph comprising a plurality of nodes interconnected by a plurality of edges, the plurality of nodes and the plurality of edges representative of the activities within the network environment, to link entities in manner that improves query efficiency.
As per claim 12, the combination of Abrams, Kraus and Fuller teaches the method of claim 1
The combination of Abrams, Kraus and Fuller does not explicitly teach wherein the user interaction is with a representation of at least a portion of the logical graph in the interface, the logical graph comprising a plurality of nodes interconnected by a plurality of edges, the plurality of nodes and the plurality of edges representative of the activities within the network environment. Trappen teaches wherein the user interaction is with a representation of at least a portion of the logical graph in the interface ([0067], user uses display to interface with system), the logical graph comprising a plurality of nodes interconnected by a plurality of edges ([0126], constructing a DAG with nodes and edges), the plurality of nodes and the plurality of edges representative of the activities within the network environment ([0126], edges represents relationship between nodes operating network transactions see [0274]).
At the time of filing, it would have been obvious to one of ordinary skill in the art to combine Abrams, Kraus and Fuller with the teachings of Trappen, wherein the user interaction is with a representation of at least a portion of the logical graph in the interface, the logical graph comprising a plurality of nodes interconnected by a plurality of edges, the plurality of nodes and the plurality of edges representative of the activities within the network environment, to link entities in manner that improves query efficiency.
As per claim 16, the combination of Abrams, Kraus and Fuller teaches the computer program product of claim 14.
The combination of Abrams, Kraus and Fuller does not explicitly teach wherein the join graph comprises a list of join links, each join link representative of an implicit join group by a same filter key type. Trappen teaches wherein the join graph comprises a list of join links, each join link representative of an implicit join group by a same filter key type ([0149], classes in mapping represent groups with same filter key and represent an implicit join).
At the time of filing, it would have been obvious to one of ordinary skill in the art to combine Abrams, Kraus and Fuller with the teachings of Trappen, wherein the join graph comprises a list of join links, each join link representative of an implicit join group by a same filter key type, to link entities in manner that improves query efficiency.
As per claim 18, the substance of the claimed invention is identical or substantially similar to that of claim 6. Accordingly, this claim is rejected under the same rationale.
As per claim 19, the substance of the claimed invention is identical or substantially similar to that of claim 12. Accordingly, this claim is rejected under the same rationale.
Claim 15 is rejected under 35 U.S.C. 103 as being unpatentable over Abrams, Kraus and Fuller in view of Ramsey et al. (US PGPUB No. 2009/0119640) [hereinafter “Ramsey”].
As per claim 15, the combination of Abrams, Kraus and Fuller teaches the computer program product of claim 14.
The combination of Abrams, Kraus and Fuller does not explicitly teach wherein generating the query comprises generating an SQL query string using a query building library. Ramsey teaches wherein generating the query comprises generating an SQL query string using a query building library ([0023], SQL query using a library directed to graph).
At the time of filing, it would have been obvious to one of ordinary skill in the art to combine Abrams, Kraus and Fuller with the teachings of Ramsey, wherein generating the query comprises generating an SQL query string using a query building library, to link entities in manner that improves query efficiency.
Response to Arguments
Applicant’s arguments with respect to the rejection of claims 1-20 under 35 U.S.C. 103 have been fully considered by the Examiner. In light of the new amendments, a new prior art reference, Fuller, has been introduced and cited to.
To expedite prosecution, Examiner is open to conducting an interview to discuss claim amendments to overcome the current rejection and/or place the application in condition for allowance.
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure. Leida et al. (US PGPUB No. 2013/0262443), Li et al. (US PGPUB No. 2015/0302058), You et al. (US PGPUB No. 2017/0243277), Pang et al. ("A Unified Narrative for Query Processing in Graph Databases," 2025 IEEE 41st International Conference on Data Engineering (ICDE), Hong Kong, Hong Kong, 2025, pp. 4492-4496, doi: 10.1109/ICDE65448.2025.00338) and Li et al. ("Variable-Length Path Query Evaluation Based on Worst-Case Optimal Joins," 2024 IEEE 40th International Conference on Data Engineering (ICDE), Utrecht, Netherlands, 2024, pp. 3311-3323, doi: 10.1109/ICDE60146.2024.00256) all disclose various aspects of the claimed invention including translating relational databases into graph representations and vice versus.
Any inquiry concerning this communication or earlier communications from the examiner should be directed to PETER C SHAW whose telephone number is (571)270-7179. The examiner can normally be reached Max Flex.
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/PETER C SHAW/Primary Examiner, Art Unit 2493 January 1, 2026