DETAILED ACTION
Claims 1, 4-11, 14-19, and 21-23 are pending. Claims 1, 9, and 19 have been amended. Claims 1, 4-11, 14-19, and 21-23 are rejected.
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 Interpretation
Claims 9-11, 14-18, and 22 are directed to a computer program product comprising one or more computer readable storage medium. This claim does not use the term non-transitory. Looking to the specification, Paragraph [0063] states that “A computer readable storage medium, as that term is used in the present disclosure, is not to be construed as storage in the form of transitory signals per se”. This shows that the claims are not directed to signals per se.
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.
Claim(s) 1, 4-10 and 14-19 is/are rejected under 35 U.S.C. 103 as being unpatentable over Ushijima, Patent Application Publication No. 2015/0310129 (hereinafter Ushijima) in view of Zhou et al., Patent Application Publication No. 2019/0266134 (hereinafter Zhou) and Walters et al., United States Patent No. 11,474,978 (hereinafter Walters).
Regarding claim 1, Ushijima teaches:
A computer-implemented method comprising: establishing a serverless automated data migration feature in a database propagation system, the enabling comprising (Ushijima Paragraph [0008], second step of extracting, by the computer, the types of nodes having a reference frequency equal to or more than a threshold; a third step of converting, by the computer, the extracted nodes into a table structure and storing the table structure as an intermediate table, Paragraph [0006], extracting the data stored in the graph database and to migrate the data):
executing relative to the source database a first query configured for extracting (Ushijima Paragraph [0044], the front-end computer 100 sends a query result from the back-end computers 200 and 300 as a response to the computer (not shown) that sent the query), using a first command sent via the first data transfer connection from the first system to the source system (Ushijima Paragraph [0072], the front-end computer 100 associates a part of the graph database 220 having a high reference frequency with the relational database 320, and extracts the resultant as the intermediate table 140, Figs. 1 and 2 show the connections and commands), a source schema from the source database (Ushijima Paragraph [0072], the front-end computer 100 associates a part of the graph database 220 having a high reference frequency with the relational database 320, and extracts the resultant as the intermediate table 140);
executing relative to the target database a second query configured for extracting (Ushijima Paragraph [0058], The query request reception module 110 is configured to receive queries to the relational database 320 (in SQL etc.) and queries to the graph database 220), using a second command sent via the data transfer second connection from the first system to the target system (Ushijima Paragraph [0092], the elements included in the RDB schema 1 are generated by extracting a correspondence between the nodes of the graph database 220 and the fields (columns) of the relational database 320, Figs. 1 and 2 show the connections and commands), a target schema from the target database (Ushijima Paragraph [0092], the elements included in the RDB schema 1 are generated by extracting a correspondence between the nodes of the graph database 220 and the fields (columns) of the relational database 320);
adding, responsive to determining that a second source attribute specified by the source schema has above a threshold amount of similarity with a target attribute specified by the target schema (Ushijima Paragraph [0159], the intermediate table 140 is obtained by extracting the data in a high-frequency reference range having a reference frequency equal to or more than a threshold, the frequency of converting queries for the relational database 320 into queries for the graph database 220 is reduced), a first conversion to a database update list (Ushijima Paragraph [0159], the intermediate table 140 is obtained by extracting the data in a high-frequency reference range having a reference frequency equal to or more than a threshold, the frequency of converting queries for the relational database 320 into queries for the graph database 220 is reduced);
performing the serverless automated data migration by implementing at a time of the data propagation the plurality of conversions in the database update list in the target database (Ushijima Paragraph [0008], second step of extracting, by the computer, the types of nodes having a reference frequency equal to or more than a threshold; a third step of converting, by the computer, the extracted nodes into a table structure and storing the table structure as an intermediate table, Paragraph [0089], the schema information management module 112 acquires a list of the types of nodes included in the graph from the graph database 220 of the back-end computer 200 to be searched, Paragraph [0006], extracting the data stored in the graph database and to migrate the data).
Ushijima does not expressly disclose:
establishing over a data communication network, at a first system, using an authentication parameter for a source database hosted on a source system, a first data transfer connection between the source database and the first system, wherein the source system and the first system are different from each other;
establishing over the data communication network, at the first system, using an authentication parameter for a target database hosted on a target system, a second data transfer connection between the target database and the first system, wherein the target system and the first system are different from each other;
However, Zhou teaches:
establishing over a data communication network, at a first system, using an authentication parameter for a source database hosted on a source system, a first data transfer connection between the source database and the first system, wherein the source system and the first system are different from each other (Zhou Paragraph [0011], The processing circuitry connects to the source database after being authenticated by the source database. The processing circuitry further sends a target connection request to the target database and connects to the target database after being authenticated by the target database);
establishing over the data communication network, at the first system, using an authentication parameter for a target database hosted on a target system, a second data transfer connection between the target database and the first system, wherein the target system and the first system are different from each other (Zhou Paragraph [0011], The processing circuitry connects to the source database after being authenticated by the source database. The processing circuitry further sends a target connection request to the target database and connects to the target database after being authenticated by the target database);
The claimed invention and Zhou are from the analogous art of database systems. It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention having the teachings of Ushijima and Zhou to have combined Ushijima and Zhou. Zhou teachings the improvements of data migration when upgrading the server hardware of a database (Paragraphs 3 and 4).
Ushijima in view of Zhou does not expressly disclose:
outputting from a synonym model a similarity measurement indicative of a below threshold similarity between a vector representation of a first source attribute specified by the source schema and vector representation of any target attribute specified by the target schema;
adding, responsive to the similarity measurement, the first source attribute to the target schema, wherein a named attribute comprises a column in a corresponding named schema;
holding, in the database update list, a plurality of conversions including the first conversion until a data propagation is limited from the source database to the target database; and
However, Walters teaches:
outputting from a synonym model a similarity measurement indicative of a below threshold similarity between a vector representation of a first source attribute specified by the source schema and vector representation of any target attribute specified by the target schema (Walters Column 3 Lines 5-01, receiving a search request comprising a sample dataset and a vector similarity threshold of similarity between vectors, Claim 1, receiving a search request comprising a sample dataset and a vector similarity threshold of similarity between vectors);
adding, responsive to the similarity measurement (Walters Column 3 Lines 5-01, receiving a search request comprising a sample dataset and a vector similarity threshold of similarity between vectors, Claim 1, receiving a search request comprising a sample dataset and a vector similarity threshold of similarity between vectors), the first source attribute to the target schema, wherein a named attribute comprises a column in a corresponding named schema (Walters Column 11 Lines 15-20, data-profiling module 237 may generate a tag, a label, a unique identifier, a title, a data class name (e.g., “health data”, “financial data”, “environmental data”, etc.), a data format, or other metadata, Column 11 Lines 1-6, A data vector may include one or more statistical metrics of a corresponding reference datasets or of a variable (e.g., a data column) of the reference dataset);
holding, in the database update list, a plurality of conversions including the first conversion until a data propagation is limited from the source database to the target database (Walters Column 14 Lines 33-40, migration module 339 may receive a log from a component of system 100 and update an aggregated log file. Updating a log file or aggregated log file may include identifying and removing duplicate records); and
The claimed invention and Walters are from the analogous art of schema systems. It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention having the teachings of Ushijima in view of Zhou and Walters to have combined Ushijima in view of Zhou and Walters. Walters teaches a searching module may be configured to generate search parameters using a machine learning model trained to use learned features of data to improve search accuracy (Column 12 Lines 25-30).
Regarding claim 4, Ushijima in view of Zhou and Walters further teaches:
The computer-implemented method of claim 1, further comprising: constructing, responsive to determining that a source format specified by the second source attribute is not identical to a target format specified by the target attribute (Ushijima Paragraph [0008], a second step of extracting, by the computer, the types of nodes having a reference frequency equal to or more than a threshold; a third step of converting, by the computer, the extracted nodes into a table structure and storing the table structure as an intermediate table), a format conversion, the format conversion specifying a conversion from the source format to the target format (Ushijima Paragraph [0008], a second step of extracting, by the computer, the types of nodes having a reference frequency equal to or more than a threshold; a third step of converting, by the computer, the extracted nodes into a table structure and storing the table structure as an intermediate table);
adding, to the database update list, the format conversion (Ushijima Paragraph [0008], a second step of extracting, by the computer, the types of nodes having a reference frequency equal to or more than a threshold; a third step of converting, by the computer, the extracted nodes into a table structure and storing the table structure as an intermediate table); and
storing, in the target database in a format specified by the format conversion and labelled with the target attribute, data of the second source attribute (Ushijima Paragraph [0008], a second step of extracting, by the computer, the types of nodes having a reference frequency equal to or more than a threshold; a third step of converting, by the computer, the extracted nodes into a table structure and storing the table structure as an intermediate table).
Regarding claim 5, Ushijima in view of Zhou and Walters further teaches:
The computer-implemented method of claim 1, further comprising: constructing, responsive to determining that a source format specified by the second source attribute is identical to a target format specified by the target attribute and determining that the source attribute and the target attribute are not identical to each other (Ushijima Paragraph [0008], a second step of extracting, by the computer, the types of nodes having a reference frequency equal to or more than a threshold; a third step of converting, by the computer, the extracted nodes into a table structure and storing the table structure as an intermediate table), an attribute conversion, the attribute conversion specifying a conversion from the second source attribute to the target attribute (Ushijima Paragraph [0008], a second step of extracting, by the computer, the types of nodes having a reference frequency equal to or more than a threshold; a third step of converting, by the computer, the extracted nodes into a table structure and storing the table structure as an intermediate table);
adding, to the database update list, the attribute conversion (Ushijima Paragraph [0008], a second step of extracting, by the computer, the types of nodes having a reference frequency equal to or more than a threshold; a third step of converting, by the computer, the extracted nodes into a table structure and storing the table structure as an intermediate table); and
storing, in the target database and labelled with the target attribute, data of the second source attribute (Ushijima Paragraph [0008], a second step of extracting, by the computer, the types of nodes having a reference frequency equal to or more than a threshold; a third step of converting, by the computer, the extracted nodes into a table structure and storing the table structure as an intermediate table).
Regarding claim 6, Ushijima in view of Zhou and Walters further teaches:
The computer-implemented method of claim 1, wherein determining that the second source attribute has above the threshold amount of similarity with the target attribute is performed using a trained synonym model (Walters Column 3 Lines 5-01, receiving a search request comprising a sample dataset and a vector similarity threshold of similarity between vectors, Claim 1, receiving a search request comprising a sample dataset and a vector similarity threshold of similarity between vectors, Column 9 Lines 5-15, Model-training module 236 may be configured to train one or more models and/or perform hyperparameter tuning of one or more models, including machine learning models. For example, model-training module 236 may be configured to receive input of one or more thresholds).
Regarding claim 7, Ushijima in view of Zhou and Walters further teaches:
The computer-implemented method of claim 6, wherein the trained synonym model determines a cosine similarity between a source numerical representation of the second source attribute and a target numerical representation of the target attribute (Ushijima Paragraph [0099], One entry includes a number (#) 2201 storing the node number, a type 2202 storing the type of node, a source 2203 storing the database name of an extraction source, a projection 2204 setting whether or not projection is required, and a connection 2205 setting whether or not to join the node with another database (Walters teaches the trained models)).
Regarding claim 8, Ushijima in view of Zhou and Walters further teaches:
The computer-implemented method of claim 6, further comprising: updating, responsive to a user confirmation of similarity between the second source attribute and the target attribute (Walters Column 3 Lines 5-01, receiving a search request comprising a sample dataset and a vector similarity threshold of similarity between vectors, Claim 1, receiving a search request comprising a sample dataset and a vector similarity threshold of similarity between vectors), the trained synonym model, the updating training the synonym model to include a synonym relationship between the second source attribute and the target attribute (Walters Column 3 Lines 5-01, receiving a search request comprising a sample dataset and a vector similarity threshold of similarity between vectors, Claim 1, receiving a search request comprising a sample dataset and a vector similarity threshold of similarity between vectors, Column 9 Lines 5-15, Model-training module 236 may be configured to train one or more models and/or perform hyperparameter tuning of one or more models, including machine learning models. For example, model-training module 236 may be configured to receive input of one or more thresholds).
Claims 9 and 14-19 are rejected in the same manner as claims 1 and 4-8 but are merely directed to a different embodiment of the same invention (method/computer program product/system). Ushijima further teaches a processor and memory in paragraph 8.
Regarding claim 10, Ushijima in view of Zhou and Walters further teaches:
The computer program product of claim 9, wherein the stored program instructions are stored in a computer readable storage device in a data processing system, and wherein the stored program instructions are transferred over a network from a remote data processing system (Ushijima Paragraph [0044], a front-end computer 100 is coupled via a network 400 to a back-end computer 200 configured to manage a graph database and a back-end computer 300 configured to manage a relational database, Paragraph [0008], A database management method for managing a graph database and a relational database in a computer comprising a processor and a memory).
Claim(s) 11 is/are rejected under 35 U.S.C. 103 as being unpatentable over Ushijima in view of Zhou, Walters, and McCoskey et al., Patent Application Publication No. 2003/0028889 (hereinafter McCoskey).
Regarding claim 11, Ushijima in view of Zhou and Walters teaches parent claim 9.
Ushijima in view of Zhou and Walters does not expressly disclose:
wherein the stored program instructions are stored in a computer readable storage device in a server data processing system, and wherein the stored program instructions are downloaded in response to a request over a network to a remote data processing system for use in a computer readable storage device associated with the remote data processing system, further comprising:
program instructions to meter use of the program instructions associated with the request; and
program instructions to generate an invoice based on the metered use.
However, McCoskey teaches:
wherein the stored program instructions are stored in a computer readable storage device in a server data processing system, and wherein the stored program instructions are downloaded in response to a request over a network to a remote data processing system for use in a computer readable storage device associated with the remote data processing system, further comprising (McCoskey Paragraph [0107], content is authorized and available, then routine 763 returns what is now an authorized remote download request form 768 through the network gateway 251 to the content delivery server 450 for fulfillment of the download request):
program instructions to meter use of the program instructions associated with the request (McCoskey Paragraph [0045], bill the user's account as appropriate and provide any license and usage fees to the content provider); and
program instructions to generate an invoice based on the metered use (McCoskey Paragraph [0045], bill the user's account as appropriate and provide any license and usage fees to the content provider).
The claimed invention and McCoskey are from the analogous art of systems looking at usage. It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention having the teachings of Ushijima in view of Zhou, Walters, and McCoskey to have combined Ushijima in view of Zhou, Walters, and McCoskey. One of ordinary skill in the art would recognize that a user of a system could be billed for how much they use a system (McCoskey Paragraph 45).
Claim(s) 21-23 is/are rejected under 35 U.S.C. 103 as being unpatentable over Ushijima in view of Zhou, Walters, and Periwal, United States Patent No. 11,347,732 (hereinafter Periwal).
Regarding claim 21, Ushijima in view of Zhou and Walters teaches parent claim 1.
Ushijima in view of Zhou and Walters does not expressly disclose:
determining, based on information pertaining to the source schema and received via the first connection, any attributes to be exempted, irrespective of the threshold amount of similarity, from the first conversion.
However, Periwal teaches:
determining, based on information pertaining to the source schema and received via the first connection, any attributes to be exempted, irrespective of the threshold amount of similarity, from the first conversion (Periwal Column 11 Lines 35-40, For example, attributes “id”, “name”, and “exempt” each map to table column names “ID”, “NAME”, and “EXEMPT” respectively, Column 9 Lines 60-65, configure database schema objects, such as tables, views, or complex data types).
The claimed invention and Periwal are from the analogous art of schema systems. It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention having the teachings of Ushijima in view of Zhou, Walters, and Periwal to have combined Ushijima in view of Zhou, Walters, and Periwal. Periwal teaches improvements directed to a framework to efficiently store, retrieve, and search for property values within data objects of an object-oriented system (Column 4 Lines 9-15).
Regarding claim 22, Ushijima in view of Zhou and Walters teaches parent claim 9.
Ushijima in view of Zhou and Walters does not expressly disclose:
determining, determining, based on information pertaining to the source schema and received via the first connection, any attributes to be exempted, irrespective of the threshold amount of similarity, from the first conversion.
However, Periwal teaches:
determining, determining, based on information pertaining to the source schema and received via the first connection, any attributes to be exempted, irrespective of the threshold amount of similarity, from the first conversion (Periwal Column 11 Lines 35-40, For example, attributes “id”, “name”, and “exempt” each map to table column names “ID”, “NAME”, and “EXEMPT” respectively, Column 9 Lines 60-65, configure database schema objects, such as tables, views, or complex data types).
The claimed invention and Periwal are from the analogous art of schema systems. It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention having the teachings of Ushijima in view of Zhou, Walters, and Periwal to have combined Ushijima in view of Zhou, Walters, and Periwal. Periwal teaches improvements directed to a framework to efficiently store, retrieve, and search for property values within data objects of an object-oriented system (Column 4 Lines 9-15).
Regarding claim 23, Ushijima in view of Zhou and Walters teaches parent claim 19.
Ushijima in view of Zhou and Walters does not expressly disclose:
determining, based on information pertaining to the source schema and received via the first connection, any attributes to be exempted, irrespective of the threshold amount of similarity, from the first conversion.
However, Periwal teaches:
determining, based on information pertaining to the source schema and received via the first connection, any attributes to be exempted, irrespective of the threshold amount of similarity, from the first conversion (Periwal Column 11 Lines 35-40, For example, attributes “id”, “name”, and “exempt” each map to table column names “ID”, “NAME”, and “EXEMPT” respectively, Column 9 Lines 60-65, configure database schema objects, such as tables, views, or complex data types).
The claimed invention and Periwal are from the analogous art of schema systems. It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention having the teachings of Ushijima in view of Zhou, Walters, and Periwal to have combined Ushijima in view of Zhou, Walters, and Periwal. Periwal teaches improvements directed to a framework to efficiently store, retrieve, and search for property values within data objects of an object-oriented system (Column 4 Lines 9-15).
Response to Arguments
Applicant’s arguments, see pages 11-19, filed 08/20/2025, with respect to the rejection under 35 U.S.C. 101 have been fully considered and are persuasive. The rejection under 35 U.S.C. 101 has been withdrawn.
Applicant’s arguments, see pages 19-21, filed 08/20/2025, with respect to the rejection(s) of claim(s) 1, 4-11, 14-19, and 21-23 under 35 U.S.C. 103 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 the amendment and the newly cited Walters reference.
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure. KEMENTSIETSIDIS et al., Patent Application Publication No. 2022/0374399.
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.
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/DUSTIN D EYERS/ Examiner, Art Unit 2164
/AMY NG/ Supervisory Patent Examiner, Art Unit 2164