DETAILED ACTION
1. This office action is in response to applicant’s communication filed on 04/15/2026 in response to PTO Office Action mailed 01/15/2026. The Applicant’s remarks and amendments to the claims and/or the specification were considered with the results as follows.
2. In response to the last Office Action, claims 2, 10 and 17 are amended. No claims are added or canceled. As a result, claims 1-23 are pending in this office action.
Response to Arguments
3. Applicant's arguments with respect to 35 USC 103 have been fully considered but are not persuasive and the details are as follow:
Applicant’s argument stated as “Brenda fails to disclose, teach or suggest converting, by the metadata query processor in the content management system, the natural language query into a metadata query in a metadata query language…Brende discloses the generation of a query that is based on metadata and is executed a data store…”
In response to applicant's arguments against the references individually, one cannot show nonobviousness by attacking references individually where the rejections are based on combinations of references. See In re Keller, 642 F.2d 413, 208 USPQ 871 (CCPA 1981); In re Merck & Co., 800 F.2d 1091, 231 USPQ 375 (Fed. Cir. 1986). As mentioned in the non-final action which mailed on 01/15/2026, the Brende reference does not explicitly disclose maintaining content in a content store and metadata in a metadata store separate from a content store, and the Coven reference has incorporated to teach this feature. The Brende reference discloses maintaining both content and metadata in a content store (See para. [0056]-para. [0058], maintaining embeddings of specific data linked to an entity’s operational ecosystem managed by the enterprise system, the set of metadata can be data patterns that enhance efficiency and relevance of query results, the set of metadata can be supporting sophisticated data analysis and decision-making process, predictive analytics and contextual data responses, which are integral to dynamic business environments). The Brende reference discloses receiving a natural language query to search within the content managed by the content management (See Brende, para. [0204] and Figure 4, step 404, receives a natural language query or question “show me the sales data for the last quarter”); converting the natural language query into a metadata query in a metadata query language (See Brende, para. [0205]- para. [0207] and Figure 4, step 406, generates an abstracted query representation into a standardized expression language based on a data model from the obtained natural language query or question); and executing the metadata query in the metadata query language against the metadata store to generate a metadata query result based on at least the metadata extracted from the content managed by the content management system (See para. [0056]-para. [0058], para. [0208]-para. [0211] and Figure 4, the enterprise system comprises a data store 103 and a query wise agent 105 to execute and support real-time data queries, the enterprise system communicates with the query wise agent 105 to access the stored metadata [e.g., data patterns] and executes the abstract query using the standardized expression language against a plurality of data stores to identify query fragments or predefined query pattern). Therefore, the Brende reference still read on the argued feature. In addition, the Examiner wants to point out that the Coven reference also discloses receiving a natural language query; and converting the natural query into a metadata query in a metadata query language. The Coven reference explicitly disclose in response to a natural language query, for example, in response to the natural language query “which people were present when dogs were present in the scene? the query engine communicates with a metadata database to retrieve data corresponding to the submitted query. The Metadata database is accessible through query engine, which comprises a query interface that receives and processes queries that are formulated in a query language (See Coven, para. [0063] and para. [0163], para. [0169] and 11E). Therefore, the combination of the cited references Coven and Brende still read on the argued feature in light of specification.
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, 5, 6, 8, 9, 13, 15, 16, 20, 21 and 23 are rejected under 35 U.S.C. 103 as being unpatentable by Brende (US 2024/0394251 A1) and in view of Coven (US 2019/0108419 A1).
Referring to claims 1, 9 and 16, Brende discloses a method, comprising:
maintaining, by a content management system, content in a content store (See para. [0052] and para. [0053], managing content such as account data in a data store) and metadata in a metadata store […], the content in the metadata data store corresponding to the content stored in the content store (See para. [0057], an enterprise system 101 manages a vector database which stores embeddings of specific data), both the content and the metadata being managed by a content management system, and wherein the set of metadata is […] managed by the content management system (See para. [0056]-para. [0058], maintaining embeddings of specific data linked to an entity’s operational ecosystem managed by the enterprise system, the set of metadata can be data patterns that enhance efficiency and relevance of query results, the set of metadata can be supporting sophisticated data analysis and decision-making process, predictive analytics and contextual data responses, which are integral to dynamic business environments);
receiving, at a metadata query processor of the content management system, a natural language query to search within the content managed by the content management system (See para. [0204] and Figure 4, step 404, receives a natural language query or question “show me the sales data for the last quarter”);
converting, by the metadata query processor in the content management system, the natural language query into a metadata query in a metadata query language (See para. [0205]- para. [0207] and Figure 4, step 406, generates an abstracted query representation into a standardized expression language based on a data model from the obtained natural language query or question); and
executing, by the content management system, the metadata query in the metadata query language against the metadata store to generate a metadata query result based on at least the metadata extracted from the content managed by the content management system […] (See para. [0056]-para. [0058], para. [0208]-para. [0211] and Figure 4, the enterprise system comprises a data store 103 and a query wise agent 105 to execute and support real-time data queries, the enterprise system communicates with the query wise agent 105 to access the stored metadata [e.g., data patterns] and executes the abstract query using the standardized expression language against a plurality of data stores to identify query fragments or predefined query pattern).
Brende does not explicitly disclose maintaining content in a content store and metadata in a metadata store separate from the content store and the set of metadata is generated by a metadata extractor that extracts metadata from the content managed by the content management system.
Coven discloses maintaining content in a content store and metadata in a metadata store separate from the content store (See para. [0090], the metadata can be stored in a separate metadata file or even in separate metadata repository and linked to the content item in some way) and the set of metadata is generated by a metadata extractor that extracts metadata from the content managed by the content management system (See para. [0062] and para. [0066] and Figure 4, generating a set of metadata including extracting faces, topics, objects from the content); receiving a natural language query and converting the natural language query into a metadata query in a metadata query language in response to a natural language query (See para. [0063] and para. [0163], para. [0169] and 11E, in response to natural language query “which people were present when dogs were present in the scene?”, the query engine communicates with a metadata database to retrieve data corresponding to the submitted query, the metadata database is accessible through query engine, which comprises a query interface that receives and processes queries that are formulated in a query language); and executing the query in the metadata query language against the metadata store to generate a metadata query result based on the metadata extracted from the content managed by the content management system, wherein the metadata query result identifies a portion of the contents in the content store (See para. [0063] and para. [0064], the query engine interfaces with the metadata database 440 to retrieve data corresponding to the submitted query, the metadata database 440 may be stored at and be accessible from any location. For example, the metadata database 440 may be stored and managed from within the cloud-based collaboration platform 414 or, the metadata database may be stored and managed from within the framework 410 or, the metadata database may be stored and managed from any other location. In example embodiments, contents of the metadata database 440 are accessible through query engine 460, which many comprise a query interface that receives and processes queries that are formulated in a query language. Such a query language can codify aspects of search terms, search predicates, and query results output specifications, etc. The returned query results are further processed by a representation selector 492 that combines query results from one or more queries to form widgets or other entries that can be displayed on any one or more UI areas of the user interface 104. In example embodiments, combining query results from multiple queries operates by correlating a first query result with a second query result. Such a correlation operates by determining a common metric for correlation (e.g., a common set of timecodes). When two or more sets of query results correspond to the same metric, aspects of the two or more sets of query results can be aligned with respect to the common metric).
Therefore, it would have been obvious to a person of ordinary skill in the computer art before the effective filing date of the claimed invention to modify the content management system of Brende’s system to generate metadata based on the metadata extracted from the content managed by the content management system, as taught by Coven. Skilled artisan would have been motivated to generate a schema tailored from the metadata (See Coven, para. [0092]). In addition, both of the references (Coven and Brende) teach features that are directed to analogous art and they are directed to the same field of endeavor, such as facilitating database queries. This close relation between both of the references highly suggests an expectation of success.
As to claims 3, 11 and 18, Brende discloses wherein the output representation for the metadata query that is presented to the user corresponds to at least one of a graph output, a JSON output, or a text output (See para. [0231], the user is presented with the abstracted query representation, and potential inconsistencies or conflicts with the data model are highlighted. Suggestions or recommendations for correcting the query based on predefined rules or heuristics are provided, and the user is allowed to modify the query or provide additional information to resolve the issues).
As to claims 4, 12 and 19, Brende discloses wherein a LLM is used by the output representation processor to select or configure the output representation for the metadata query (See para. [0209] and Figure 4, step 412, a large language model (LLM) trained on a corpus of query patterns and system performance metrics may be utilized to translate the predefined query pattern into an executable query).
As to claims 5, 13 and 20, Brende discloses a filter is applied to restrict display or querying of data that is not permitted to be accessed by a user that submits the natural language query (See para. [0068], a database that is accessible by the user but not directly accessible by the computing device that obtains the natural language query enhances data privacy and security).
As to claims 6 and 21, Brende discloses wherein a natural language query is converted into the query in the metadata query language using a LLM (See para. [0209] and Figure 4, step 412, a large language model (LLM) trained on a corpus of query patterns and system performance metrics may be utilized to translate the predefined query pattern into an executable query).
As to claims 8, 15 and 23, Brende discloses fetching a template that corresponds to a document (See para. [0121] and para. [0122], obtaining a template that corresponding to a database schema document with relevant entities); transforming the query using a meta template; and executing a transformed query against the metadata store (See para. [0121] and para. [0122] and para. [0126], para. [0220], converting the natural language to abstract query against the database scheme document and generate executable queries).
Claims 7, 14 and 22 are rejected under 35 U.S.C. 103 as being unpatentable by Brende (US 2024/0394251 A1) and in view of Coven (US 2019/0108419 A1) and further in view of Hsu (US 2019/0102413 A1).
As to claims 7 and 22, Brende does not explicitly disclose populating metadata for a document and creating a metadata instance for the document.
Hsu discloses creating a document; populating metadata for the document; creating a metadata instance for the document (See para. [0049], using the term rankings table 202, the metadata generation module illustrates an exemplary data structure that can be used to store information associated with documents for use in indexing/querying a set of documents. A documents table 208 is used by the computing device 102 to store various types of information associated with each document); and creating an index object in the metadata store for the document (See para. [0062] and Figure 4, the indexing module generates one or more indexes that are each used to store data associated with one or more documents).
Therefore, it would have been obvious to a person of ordinary skill in the computer art before the effective filing date of the claimed invention to modify the Brende’s system to populating metadata for a document, taught by Hsu. Skilled artisan would have been motivated to utizes metadata to identify documents that include the search terms and facilitate user locate a list of documents that are relevant to the search terms quickly and efficiently (See Hsu, para. [0003] and para. [0004]). In addition, all of the references (Coven, Hsu and Brende) teach features that are directed to analogous art and they are directed to the same field of endeavor, such as searching a set of documents which matched the search terms. This close relation between all of the references highly suggests an expectation of success.
As to claim 14, Brende discloses wherein the natural language query is converted into the query in the metadata query language using a LLM (See para. [0209] and Figure 4, step 412, a large language model (LLM) trained on a corpus of query patterns and system performance metrics may be utilized to translate the predefined query pattern into an executable query).
Brende does not explicitly disclose populating metadata for a document and creating a metadata instance for the document.
Hsu discloses creating a document; populating metadata for the document; creating a metadata instance for the document (See para. [0049], using the term rankings table 202, the metadata generation module illustrates an exemplary data structure that can be used to store information associated with documents for use in indexing/querying a set of documents. A documents table 208 is used by the computing device 102 to store various types of information associated with each document); and creating an index object in the metadata store for the document (See para. [0062] and Figure 4, the indexing module generates one or more indexes that are each used to store data associated with one or more documents).
Therefore, it would have been obvious to a person of ordinary skill in the computer art before the effective filing date of the claimed invention to modify the Brende’s system to populating metadata for a document, taught by Hsu. Skilled artisan would have been motivated to utizes metadata to identify documents that include the search terms and facilitate user locate a list of documents that are relevant to the search terms quickly and efficiently (See Hsu, para. [0003] and para. [0004]). In addition, all of the references (Hsu, Coven and Brende) teach features that are directed to analogous art and they are directed to the same field of endeavor, such as searching a set of documents which matched the search terms. This close relation between all of the references highly suggests an expectation of success.
Allowable Subject Matter
Claims 2-4, 10-12 and 17-19 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.
THIS ACTION IS MADE FINAL. 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 YUK TING CHOI whose telephone number is (571)270-1637. The examiner can normally be reached Monday-Friday 9am-6pm.
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If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, AMY NG can be reached at 5712701698. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
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/YUK TING CHOI/Primary Examiner, Art Unit 2164
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