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 .
Response to Amendment
Claims 1-20 are pending in this application.
Claim rejections 35 USC 101 are withdrawn.
Applicant’s arguments on claim rejections 35 USC 102 and 35 USC 103, filed 7/7/2026, have been fully considered and are persuasive. Therefore, the rejection has been withdrawn. However, upon further consideration, a new ground(s) of rejection is made in view of Griffith.
Response to Arguments
Applicant’s arguments with respect to claim rejections 35 USC 102 and 35 USC 103 have been considered but are moot because the new ground of rejection does not rely on any reference applied in the prior rejection of record for any teaching or matter specifically challenged in the argument.
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.
Claims 1, 3, 8, 10, 15 and 17 are rejected under 35 U.S.C. 103 as being unpatentable over Engelko et al. (US 2013/0159247, hereinafter “Engelko”) in view of Griffith et al. (US 2025/0315611, hereinafter “Griffith”).
Regarding claim 1, Engelko teaches A method comprising:
determining, based on the data model, the set of tables used for creation of the plurality of entity documents (Engelko, [0018]: As shown in FIG. 1, the original table 17 (e.g., the source table) can be related to, or can include, program data and/or user data. For example, the original table 17 can include data defined by an owner of the original system 12. For example, the original table 17 can include user-specific data such as business data, financial data, and/or so forth. In some embodiments, the data stored within the original table 17 can be referred to as customer data.);
generating, based on the set of tables, a change table for each table in the set of tables (Engelko, [0050]: A logging table corresponding with an original table targeted for an upgrade can be generated (block 210). [0067]: As shown in FIG. 4A, after an upgrade process related to an original system has been started (block 410), tables for change recording can be generated and a version identifier can be set (e.g., defined) (block 415).);
determining, based on the change tables, one or more changes to data in the set of tables (Engelko, [0052]: An indicator of a change to a record of the original table can be received during execution of at least a portion of the upgrade of the original table (block 230). [0053]: A primary key identifying the record of the original table and the version identifier stored in the control table can be stored in the logging table (block 240).);
generating, based on the one or more changes, a collected changes table for each table in the set of tables (Engelko, [0091]: In some embodiments, at least some portions of the target table 750 can be generated (e.g., updated during a change recording process) based on the original table 742, the logging table 744 and/or the control table 746.);
causing, based on the collected changes tables, an update to a semantic indexing table (Engelko, [0063]: In some embodiments, if the version identifier is updated within the control table 330, the version identifier can be replaced (e.g., replaced with a version identifier having a different value). [0072]: Also as shown in FIG. 4A, with each iteration of change recording and transferring of changes, the version identifier is updated (block 445) (if change recording has not been completed).).
Engelko does not explicitly teach receiving, by at least one server device from a client device, a first user question associated with a plurality of entity documents stored in a vector database, wherein the plurality of entity documents is generated based on a set of tables associated with a data model; generating, based on the plurality of entity documents, an answer to the first user question; wherein the update causes one or more updated entity documents to be stored in the vector database; receiving, by the at least one server device from the client device, a second user question associated with the one or more updated entity documents; and sending, to the client device, an answer to the second user question, wherein the answer to the second user question is based on the one or more updated entity documents.
Griffith teaches receiving, by at least one server device from a client device, a first user question associated with a plurality of entity documents stored in a vector database, wherein the plurality of entity documents is generated based on a set of tables associated with a data model (Griffith, [0014]: In addition to automatically identifying a specific machine learning models to perform tasks associated with a use case, training the models, and deploying the model for use in a live environment, the collaborative platform may also provide a knowledge management and question-answering service that allows users to create custom knowledge bases and interact with them using language models. At its core, this service leverages the retrieval-augmented generation (RAG) architecture, combining the generative capabilities of large language models (LLMs), or other types of natural language processing models, with the ability to retrieve and reason over external data. [0054]: At block 260, the system determines a first database comprising first stored data associated with a first request. At block 270, the system determines a second database comprising second stored data associated with the first request. For example, the first request may be a request for the collaborative platform to generate a machine learning model that may be used to perform a task or tasks associated with a desired use case. In some instances, the first request may be for at least one of: a numerical prediction, a binary output, a category prediction, a trend forecast, or a probability value (however, any other type of request may be provided as well).);
generating, based on the plurality of entity documents, an answer to the first user question (Griffith, [0054]: At block 280, the system automatically retrieves the first stored data and the second stored data, wherein at least one of the first database or the second database is an external database. That is, the collaborative platform may automatically retrieve initial training data that may be used to train one or more machine learning models for evaluation before a model is selected to be used in a live environment to perform the task or tasks associated with the use case.);
wherein the update causes one or more updated entity documents to be stored in the vector database (Griffith, [0063]: At block 316 of the process flow 300, computer-executable instructions stored on a memory of a device, such as a server, may be executed to update the first machine learning model using the first set of feedback signals.);
receiving, by the at least one server device from the client device, a second user question associated with the one or more updated entity documents (Griffith, [0064] At block 318 of the process flow 300, computer-executable instructions stored on a memory of a device, such as a server, may be executed to determine a second request for an artificial intelligence output via the graphical user interface. In some instances, the second request may include a request for at least one of: training data generation, text drafting, data extraction, or source code rewriting. However, any other type of request may also be made.); and
sending, to the client device, an answer to the second user question, wherein the answer to the second user question is based on the one or more updated entity documents (Griffith, [0068]: At block 326 of the process flow 300, computer-executable instructions stored on a memory of a device, such as a server, may be executed to cause presentation of the artificial intelligence output.).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to combine the change data capturing process of Engelko with the teaching about the machine learning models of Griffith because the RAG evaluation framework may identify areas for improvement and optimize the system's performance (Griffith, [0019]).
Regarding claim 3, Engelko in view of Griffith teaches wherein the first user question comprises at least one natural language query (Griffith, [0016]: Once a knowledge base is populated, the core functionality of searching and interacting with the knowledge can be accessed through either the UI or APIs. The search capability allows users to enter natural language queries, which are then mapped to the semantic vector space.).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to combine the change data capturing process of Engelko with the teaching about the machine learning models of Griffith because the RAG evaluation framework may identify areas for improvement and optimize the system's performance (Griffith, [0019]).
Claim 8 is rejected under the same rationale as claim 1. Engelko also teaches A system comprising: a vector database and a first computing device (Engelko, [0092]: As shown in FIG. 8, a system upgrade module 870 operating within shadow server environment 820 is configured to access a database environment 830.).
Claim 10 is rejected under the same rationale as claim 3.
Claim 15 is rejected under the same rationale as claim 1. Engelko also teaches A non-transitory computer-readable medium storing instructions that, when executed by one or more processors, cause the one or more processors to… (Engelko, [0101]: In some implementations, a tangible computer-readable storage medium can be configured to store instructions that when executed cause a processor to perform a process.).
Claim 17 is rejected under the same rationale as claim 3.
Claims 2, 9 and 16 are rejected under 35 U.S.C. 103 as being unpatentable over Engelko in view of Griffith and further in view of Smith et al. (US 12,505,089, hereinafter “Smith”).
Regarding claim 2, Engelko in view of Griffith teaches the method of claim 1 as discussed above. Engelko in view of Griffith does not explicitly teach wherein determining the one or more changes to data in the set of tables comprises at least one of: incrementally scanning each table using a change-time column, or parsing a transaction log of a source database.
Smith teaches wherein determining the one or more changes to data in the set of tables comprises at least one of: incrementally scanning each table using a change-time column (Smith, column 11 lines 36-56: For example, the change detection system 112 can add system-time columns to database tables, which can be used to determine the period for which each record of the database is valid, and the change detection system 112 can query temporal tables (e.g., query dataset 124) for records altered within a specific timeframe. The change detection system 112 can execute a trigger-based CDC function (e.g., via a data replication function, a data transformation and loading function (ETL and/or UTL), an audit logging function, etc.) by creating database triggers within a database (e.g., database 120 or data sources 150) and/or being configured to respond to the database triggers of the database. The database triggers can be set to automatically record changes into a shadow (or monitored) table (e.g., database utilized for logging insertions, updates, and deletions) when a data manipulation language (DML) operation occurs on the monitored table. The change detection system 112 can periodically (or repeatedly, or according to a prespecified time) scan the monitored/shadow table for new entries (e.g., entries representing the latest data modifications).), or parsing a transaction log of a source database (Smith, column 11 lines 30-36: For example, the change detection system 112 can monitor a database transaction log for changes and parse the database transaction logs to identify and extract modifications without querying the database directly. In some embodiments, the change detection system 112 can implement a time-based (e.g., timestamp-based) CDC method (e.g., utilizing system-versioned temporal tables, etc.).).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to combine the change data capturing process of Engelko and Griffith with the teaching about the change detection system of Smith because it can avoid computational costs of scanning the entire data source/dataset to determine changes and increase the efficiency and performance of computing devices implementing the change detection system (Smith, column 11 lines 20-24).
Claim 9 is rejected under the same rationale as claim 2.
Claim 16 is rejected under the same rationale as claim 2.
Claims 4-6, 11-13 and 18-19 are rejected under 35 U.S.C. 103 as being unpatentable over Engelko in view of Griffith and further in view of Bourbonnais et al. (US 2018/0046551, hereinafter “Bourbonnais”).
Regarding claim 4, Engelko in view of Griffith teaches the method of claim 1 as discussed above. Engelko in view of Griffith does not explicitly teach wherein generating the collected changes table for each table in the set of tables comprises truncating an existing collected changes table for each table in the set of tables.
Bourbonnais teaches generating the collected changes table for each table in the set of tables comprises truncating an existing collected changes table for each table in the set of tables (Bourbonnais, [0059]: FIG. 5, illustrates, in a flow chart, more detailed operations for recovery log analytics in accordance with certain embodiments. Control begins at block 500 with the capture engine 160 pruning previous changed records in change data tables. [0062]: The monitoring thread updates the corresponding row to notify the capture engine 160 that it can prune all the rows whose SNAP_COMMITSEQ is less than the value of LAST_MAX_COMMITSEQ. the capture engine 160 has a single prune thread that monitors the progress of all the apply engines 110 and prunes the change data tables 142 and the UOW tables whose rows have been applied by all the apply engines.).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to combine the change data capturing process of Engelko and Griffith with the teaching about the pruning of the change data tables of Bourbonnais because it may avoid unnecessary/slow reading/parsing from the DBMS log (Bourbonnais, [0068]).
Regarding claim 5, Engelko in view of Griffith and Bourbonnais teaches collecting changes for each table in the set of tables from the corresponding change table into the corresponding collected changes table (Engelko, [0091]: In some embodiments, at least some portions of the target table 750 can be generated (e.g., updated during a change recording process) based on the original table 742, the logging table 744 and/or the control table 746. Bourbonnais, [0059]: In block 504, the capture engine 160 appends the consistent change records into the change data tables 142.), wherein only entity documents affected by the collected changes are regenerated in the vector database (Griffith, [0016]: The search capability allows users to enter natural language queries, which are then mapped to the semantic vector space. The service retrieves the most relevant documents from the knowledge base based on vector similarity and respects the metadata-based filtering, ensuring that users only receive responses from the relevant documents.).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to combine the change data capturing process of Engelko and Griffith with the teaching about the pruning of the change data tables of Bourbonnais because it may avoid unnecessary/slow reading/parsing from the DBMS log (Bourbonnais, [0068]).
Regarding claim 6, Engelko in view of Griffith and Bourbonnais teaches traversing the data model from leaf tables to a root entity table; and updating a parent table's collected changes table based on a child table's collected changes table (Engelko, [0091] In some embodiments, at least some portions of the target table 750 can be generated (e.g., updated during a change recording process) based on modification view 732 and/or the deletions view 734. In some embodiments, at least some portions of the target table 750 can be generated (e.g., updated during a change recording process) based on the original table 742, the logging table 744 and/or the control table 746.).
Claim 11 is rejected under the same rationale as claim 4.
Claim 12 is rejected under the same rationale as claim 5.
Claim 13 is rejected under the same rationale as claim 6.
Claim 18 is rejected under the same rationale as claim 4.
Claim 19 is rejected under the same rationale as claim 6.
Claims 7, 14 and 20 are rejected under 35 U.S.C. 103 as being unpatentable over Engelko in view of Griffith and further in view of Chaliparambil et al. (US 2013/0007069, hereinafter “Chaliparambil”).
Regarding claim 7, Engelko in view of Griffith teaches the method of claim 1 as discussed above. Engelko in view of Griffith does not explicitly teach wherein causing the update to the semantic indexing table comprises: calculating an identifier as a hash of concatenated root table primary key columns; deleting a row of the semantic indexing table where an identifier column equals the calculated identifier; and inserting, based on a deletion indicator being false or null, a new row into the semantic indexing table, wherein the new row comprises the identifier, an updated entity document, and an embeddings vector generated for the updated entity document.
Chaliparambil teaches wherein causing the update to the semantic indexing table comprises: calculating an identifier as a hash of concatenated root table primary key columns; deleting a row of the semantic indexing table where an identifier column equals the calculated identifier (Chaliparambil, [0187]: Next, rows can be deleted from the materialized view table at block 403. For example, for each altered row ID (e.g., a primary key for a record) in the materialized view table, the entire row can be deleted.); and inserting, based on a deletion indicator being false or null, a new row into the semantic indexing table, wherein the new row comprises the identifier, an updated entity document, and an embeddings vector generated for the updated entity document (Chaliparambil, [0189]: Next, the materialized view table is updated at block 405. For example, the records retrieved at block 404 can be inserted into the materialized view table for the deleted row ID's. Accordingly, the materialized view table is now up to date with respect to the altered records identified at block 402. [0205]: Next, at block 505, updated data relating to the personal health record is provided to the entity by sending the notification via an appropriate channel, provided the entity is authorized.).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to combine the change data capturing process of Engelko and Griffith with the teaching about the updating views in a database of Chaliparambil because it can reduce latency even further and can provide real-time levels of performance (Chaliparambil, [0191]).
Claim 14 is rejected under the same rationale as claim 7.
Claim 20 is rejected under the same rationale as claim 7.
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.
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure.
Prabhakaran (US 20190138619) discloses that each folder path present in a folder activity table (e.g., folder activity table 114) is scanned to verify a change in the modified time.
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Any inquiry concerning this communication or earlier communications from the examiner should be directed to PHONG H NGUYEN whose telephone number is (571)270-1766. The examiner can normally be reached Monday-Friday, 8:30am-5pm EST.
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/PHONG H NGUYEN/ Primary Examiner, Art Unit 2156
August 27, 2026
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