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 Status
Claims 1-14 are pending.
Double Patenting
The nonstatutory double patenting rejection is based on a judicially created doctrine grounded in public policy (a policy reflected in the statute) so as to prevent the unjustified or improper timewise extension of the “right to exclude” granted by a patent and to prevent possible harassment by multiple assignees. A nonstatutory double patenting rejection is appropriate where the conflicting claims are not identical, but at least one examined application claim is not patentably distinct from the reference claim(s) because the examined application claim is either anticipated by, or would have been obvious over, the reference claim(s). See, e.g., In re Berg, 140 F.3d 1428, 46 USPQ2d 1226 (Fed. Cir. 1998); In re Goodman, 11 F.3d 1046, 29 USPQ2d 2010 (Fed. Cir. 1993); In re Longi, 759 F.2d 887, 225 USPQ 645 (Fed. Cir. 1985); In re Van Ornum, 686 F.2d 937, 214 USPQ 761 (CCPA 1982); In re Vogel, 422 F.2d 438, 164 USPQ 619 (CCPA 1970); In re Thorington, 418 F.2d 528, 163 USPQ 644 (CCPA 1969).
A timely filed terminal disclaimer in compliance with 37 CFR 1.321(c) or 1.321(d) may be used to overcome an actual or provisional rejection based on nonstatutory double patenting provided the reference application or patent either is shown to be commonly owned with the examined application, or claims an invention made as a result of activities undertaken within the scope of a joint research agreement. See MPEP § 717.02 for applications subject to examination under the first inventor to file provisions of the AIA as explained in MPEP § 2159. See MPEP § 2146 et seq. for applications not subject to examination under the first inventor to file provisions of the AIA . A terminal disclaimer must be signed in compliance with 37 CFR 1.321(b).
The filing of a terminal disclaimer by itself is not a complete reply to a nonstatutory double patenting (NSDP) rejection. A complete reply requires that the terminal disclaimer be accompanied by a reply requesting reconsideration of the prior Office action. Even where the NSDP rejection is provisional the reply must be complete. See MPEP § 804, subsection I.B.1. For a reply to a non-final Office action, see 37 CFR 1.111(a). For a reply to final Office action, see 37 CFR 1.113(c). A request for reconsideration while not provided for in 37 CFR 1.113(c) may be filed after final for consideration. See MPEP §§ 706.07(e) and 714.13.
The USPTO Internet website contains terminal disclaimer forms which may be used. Please visit www.uspto.gov/patent/patents-forms. The actual filing date of the application in which the form is filed determines what form (e.g., PTO/SB/25, PTO/SB/26, PTO/AIA /25, or PTO/AIA /26) should be used. A web-based eTerminal Disclaimer may be filled out completely online using web-screens. An eTerminal Disclaimer that meets all requirements is auto-processed and approved immediately upon submission. For more information about eTerminal Disclaimers, refer to www.uspto.gov/patents/apply/applying-online/eterminal-disclaimer.
Claims 1-14 are rejected on the ground of nonstatutory double patenting as being unpatentable over claims 1-14 of U.S. Patent No. 12,242,518 application 18/493,295 in view of Moncivais-Pinedo.
19/066,765
1. A method for analyzing data stored in a relational database, the method comprising:
18/493,295
1. A method for analyzing data stored in a relational database, the method comprising:
19/066,765
installing a structured query language (SQL) server application on a host server;
18/493,295
installing a structured query language (SQL) server application on a host server;
19/066,765
installing statistical analysis modules on the host server;
18/493,295
installing statistical analysis modules on the host server;
19/066,765
executing the statistical analysis modules within a relational database of the SQL server
application to analyze data stored in the relational database; and
18/493,295
executing the statistical analysis modules within a relational database of the SQL server
application to analyze data stored in the relational database; and
19/066,765
generating outputs based on the execution of the statistical analysis modules within the
relational database.
18/493,295
generating outputs based on the execution of the statistical analysis modules within the
relational database;
generating a data mart in the SQL server application, the data mart comprising financial data, wherein the data comprises the financial data;
generating a conceptual data model comprising independent specifications of the financial data;
generating based on the conceptual data model, a logical data model indicative of structures of the financial data to be implemented in the relational database; and
generating based on the logical model, a physical data model in which the financial data are organized into tables, wherein generating the data mart is based on the tables.
19/066,765
2. The method of claim 1, wherein generating the outputs occurs without exporting the data
stored in the relational database.
18/493,295
2. The method of claim 1, wherein generating the outputs occurs without exporting the data
stored in the relational database.
19/066,765
3. The method of claim 1, wherein the host server comprises 32 processing cores and 64
gigabytes of random access memory.
18/493,295
3. The method of claim 1, wherein the host server comprises 32 processing cores and 64
gigabytes of random access memory.
19/066,765
4. The method of claim 1, wherein the outputs comprise a spending trend and a forecast
budget run rate.
18/493,295
4. The method of claim 1, wherein the outputs comprise a spending trend and a forecast
budget run rate.
19/066,765
5. The method of claim 1, wherein the statistical analysis modules use an R statistical
model.
18/493,295
5. The method of claim 1, wherein the statistical analysis modules use an R statistical
model.
19/066,765
6. A system for analyzing data stored in a relational database, the system comprising
memory coupled to at least one processor of a host server, the at least one processor configured
to:
install a structured query language (SQL) server application on the host server;
install statistical analysis modules on the host server;
execute the statistical analysis modules within a relational database of the SQL server
application to analyze data stored in the relational database; and
generate outputs based on the execution of the statistical analysis modules within the
relational database.
18/493,295
6. A system for analyzing data stored in a relational database, the system comprising
memory coupled to at least one processor of a host server, the at least one processor configured
to:
install a structured query language (SQL) server application on the host server;
install statistical analysis modules on the host server;
execute the statistical analysis modules within a relational database of the SQL server
application to analyze data stored in the relational database; and
generate outputs based on the execution of the statistical analysis modules within the
relational database;
generate a data mart in the SQL server application, the data mart comprising financial data, wherein the data comprises the financial data;
generate a conceptual data model comprising independent specifications of the financial data;
generate based on the conceptual data model, a logical data model indicative of structures of the financial data to be implemented in the relational database, and
generate based on the logical data model, physical data model in which the financial data are organized into tables, wherein the data mart is based on the tables.
19/066,765
7. The system of claim 6, wherein to generate the outputs occurs without exporting the data
stored in the relational database.
18/493,295
7. The system of claim 6, wherein to generate the outputs occurs without exporting the data
stored in the relational database.
19/066,765
8. The system of claim 6, wherein the host server comprises 32 processing cores and 64
gigabytes of random access memory.
18/493,295
8. The system of claim 6, wherein the host server comprises 32 processing cores and 64
gigabytes of random access memory.
19/066,765
9. The system of claim 6, wherein the outputs comprise a spending trend and a forecast
budget run rate.
18/493,295
9. The system of claim 6, wherein the outputs comprise a spending trend and a forecast
budget run rate.
19/066,765
10. The system of claim 6, wherein the statistical analysis modules use an R statistical model.
18/493,295
10. The system of claim 6, wherein the statistical analysis modules use an R statistical model.
19/066,765
11. A non-transitory computer-readable storage medium comprising instructions to cause at
least one processor of a device for analyzing data stored in a relational database, upon execution
of the instructions by the at least one processor, to:
install a structured query language (SQL) server application on a host server;
install statistical analysis modules on the host server;
execute the statistical analysis modules within a relational database of the SQL server
application to analyze data stored in the relational database; and
generate outputs based on the execution of the statistical analysis modules within the
relational database.
18/493,295
11. A non-transitory computer-readable storage medium comprising instructions to cause at
least one processor of a device for analyzing data stored in a relational database, upon execution
of the instructions by the at least one processor, to:
install a structured query language (SQL) server application on a host server;
install statistical analysis modules on the host server;
execute the statistical analysis modules within a relational database of the SQL server
application to analyze data stored in the relational database; and
generate outputs based on the execution of the statistical analysis modules within the
relational database.
19/066,765
12. The non-transitory computer-readable storage medium of claim 11, wherein to generate
the outputs occurs without exporting the data stored in the relational database.
18/493,295
12. The non-transitory computer-readable storage medium of claim 11, wherein to generate
the outputs occurs without exporting the data stored in the relational database.
19/066,765
13. The non-transitory computer-readable storage medium of claim 11, wherein the host
server comprises 32 processing cores and 64 gigabytes of random access memory.
18/493,295
13. The non-transitory computer-readable storage medium of claim 11, wherein the host
server comprises 32 processing cores and 64 gigabytes of random access memory.
19/066,765
14. The non-transitory computer-readable storage medium of claim 11, wherein the outputs
comprise a spending trend and a forecast budget run rate.
18/493,295
14. The non-transitory computer-readable storage medium of claim 11, wherein the outputs
comprise a spending trend and a forecast budget run rate.
Specification
The specification is objected to as failing to provide proper antecedent basis for the claimed subject matter. See 37 CFR 1.75(d)(1) and MPEP § 608.01(o). Correction of the following is required: Claims 5 and 10 recite wherein the statistical analysis modules use an R statistical model.
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.
Claim(s) 1 is/are rejected under 35 U.S.C. 103 as being unpatentable over Brezis (US 11,853,911) in view of Rosner (US 2016/0035019) in view of Chroscielewski (US 2009/0222552)
Examiner Note: Hereafter above references will be entered as reference combination A.
Regarding claim 1, Brezis discloses:
installing a structured query language (SQL) server application on a host server;
Brezis col 4 lines 5-7, For example, where the user has specified the data source to be an SQL server, the connection information can include a host/server identifier (e.g., via IP address or fully-qualified domain name),
installing statistical analysis modules on the host server;
Brezis discloses elements of the claimed invention as noted but does not disclose above limitation. However, Rosner discloses:
Rosner [0031] In addition, the back-end portion of the host server 100 can perform statistics gathering and data analytics functionalities in order to, for example, calculate the fair market price, or provide hotel merchants relevant sales data so as to enable the merchants to make educated decisions whether or not to accept, refuse, or counter a bid offer from the customer. This also provides educational value to the hotel merchants so that their asking price/price range for their rooms in the future may be more reflective of the market's demand. Among others, these functionalities promotes the electronic marketplace platform introduced here.
It would have been obvious to one of ordinary skill in the art before the filing date of the claimed invention to modify Brezis to obtain above limitation based on the teachings of Rosner for the purpose of providing educational value to hotel merchants so that their asking price/price range for their rooms in the future may be more reflective of the market's demand.
Furthermore, one of ordinary skill in the art would be motivated to look to the teachings of Rosner. Rosner is analogous art from the same field of invention, i.e., analyzing data stored in a relational database, see below:
[0023] In some variations, the repository 124 can be implemented via object-oriented technology and/or via text files, and can be managed by a distributed database management system, an object-oriented database management system (OODBMS), an object-relational database management system (ORDBMS), a file system, and/or any other suitable database management package.
The above indicates there is a reasonable expectation of success in combining Brezis and Rosner to achieve the claimed invention.
executing the statistical analysis modules within a relational database of the SQL server
application to analyze data stored in the relational database;
Brezis discloses elements of the claimed invention as noted but does not disclose above limitation. However, Chroscielewski discloses:
Chroscielewski [0021] The invention is a human-computer productivity management system with both processes and data systems designed to monitor the interactions between humans and computer systems, log the interactions, securely transmit the data to a centralized server, archive the data, process the data into highly efficient relational database, analyze the data to calculate productivity metrics, distill the data into key business intelligence reports and control the use of the computer systems.
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify Brezis to obtain above limitation based on the teachings of Chroscielewski for the purpose of monitoring and logging interactions between humans and computer systems.
Furthermore, one of ordinary skill in the art would be motivated to look to the teachings of Chroscielewski . Chroscielewski is analogous art from the same field of invention, i.e., analyzing data stored in a relational database, see below:
The invention is a human-computer productivity management system with both processes and data systems designed to monitor the interactions between humans and computer systems, log the interactions, securely transmit the data to a centralized server, archive the data, process the data into highly efficient database, analyze the data to calculate productivity metrics, distill the data into key business intelligence reports and control the use of the computer systems, see abstract.
The above indicates there is a reasonable expectation of success in combining Brezis and Chroscielewski to achieve the claimed invention.
generating outputs based on the execution of the statistical analysis modules within the
relational database.
Chroscielewsk claim 1, A computerized method for managing productivity in a human-computer environment, the method comprising: monitoring human-computer interactions on a plurality of computing devices; logging human-computer interactions on the plurality of computing devices; transmitting logged data, from the plurality of computing devices, to a data management server; indexing and archiving human-computer interaction data in a database; and calculating and displaying statistical information from the archived data.
Claim(s) 2 is/are rejected under 35 U.S.C. 103 as being unpatentable over reference combination A in view of Mozes (US 2017/0308809)
Regarding claim 2, reference combination A discloses elements of the claimed invention as noted but does not disclose wherein generating the outputs occurs without exporting the data
stored in the relational database. However, Mozes discloses:
Mozes [0067] At block 230, the data partitions are analyzed within the relational database system to generate partition metrics data. The partition metrics data include a number of partitions in the training data, a size of each partition in the training data, and a respective value for the partition key associated with each partition in the training data. Other partition metrics data may be possible as well, in accordance with other embodiments. In accordance with one embodiment, metrics logic 125 of analytics logic 110 of FIG. 1 is configured to generate the partition metrics data.
Interpreted per specification [0020]
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify reference combination A to obtain above limitation based on the teachings of Mozes for the purpose of providing a relational database system, having a computing device configured with analytics logic, for generating a composite model object of partitioned data mining models built on partitioned training data, and scoring records of scoring data using the composite model object, see [0006] FIG. 1.
Claim(s) 3 is/are rejected under 35 U.S.C. 103 as being unpatentable over reference combination A in view of Ward (US 2020/0304384).
Regarding claim 3, reference combination A discloses elements of the claimed invention as noted but does not disclose wherein the host server comprises 32 processing cores and 64
gigabytes of random access memory. However, Ward discloses:
Ward [0040] For example, in the illustrated embodiment, the various instance types (small, medium, large and extra large) of the standard instance family 210 may be implementable using a single server type “S1” with 32 processing cores, 64 gigabytes of available main memory and 1600 gigabytes of available disk storage.
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify reference combination A to obtain above limitation based on the teachings of Ward for the purpose of managing flexible capacity pool reservations for network-accessible resources, see [0016]
Claim(s) 4 is/are rejected under 35 U.S.C. 103 as being unpatentable over reference combination A in view of Sihavong (US 2022/0277383) in view of Clode (US 2013/0054440)
Regarding claim 4, reference combination A discloses elements of the claimed invention as noted but does not disclose wherein the outputs comprise a spending trend. However, Sihavong discloses:
Sihavong [0023] Account data 1271 includes financial data from the user's financial accounts. User financial accounts may include user savings accounts, checking accounts, credit card accounts, and any other types of payment accounts. Account data 1271 may include, but is not limited to, a plurality of data features, such as a user identifier (ID), an account number, cash flow, account balances, payment due dates of financial cards accounts, interest charges of the financial card accounts, savings goals, budgets, credit scores, spending trend data, etc. Account data 1271 is associated with transaction data 1272 of corresponding user accounts and corresponding historical user behavior data 1273.
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify reference combination A to obtain above limitation based on the teachings of Sihavong for the purpose of recommending personalized digital nudges designed to influence the user in a manner that furthers a savings goal, see abstract.
Regarding claim 4, reference combination A discloses elements of the claimed invention as noted but does not disclose wherein the outputs comprise a forecast budget run rate. However, Clode discloses:
Clode [0047] Established budget values may be run through the budget rates or the transactional rates. While assembling a budget vs. transaction report, the actual values may be run through the transactional rates to track finances or through the budget rates to determine budget accuracy. If there is a significant discrepancy in the budget with respect to the actual values, the actual values may be run through the budget rate to identify specific transactions or financial activities that may have caused the discrepancy. If the rate projections are substantially accurate, information may be provided regarding the accuracy of the budget. If the result is near the target budget but differs greatly when using the actual rates, a determination can be made regarding how much of the discrepancy is due to exchange rate variance.
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify reference combination A to obtain above limitation based on the teachings of Clode for the purpose of running through the transactional rates to track finances or through the budget rates to determine budget accuracy.
Claim(s) 5 is/are rejected under 35 U.S.C. 103 as being unpatentable over reference combination A in view of Gilbert (US 2011/0167115).
Regarding claim 5, reference combination A discloses elements of the claimed invention as noted but does not disclose wherein the statistical analysis modules use an R statistical
Model. However, Gilbert discloses:
Gilbert [0152] The core We Meddle tie strength engine is written in Perl, appropriating the output of an R statistical model, although the engine is not limited by the software language used to implement it. When a user first signs in to We Meddle, the system needs to build a database of tie strengths for each account the user follows. The sign-in forks off hundreds and sometimes thousands of API requests against Twitter. This was the main technical hurdle: overlapping the relational data requests in precisely the right way to support hundreds of simultaneous users.
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify reference combination A to obtain above limitation based on the teachings of Gilbert for the purpose of building a database of tie strengths for each account the user follows.
Claim(s) 6 is/are rejected under 35 U.S.C. 103 as being unpatentable over Brezis (US 11,853,911) in view of Rosner (US 2016/0035019) in view of Chroscielewski (US 2009/0222552)
Regarding claim 6, Brezis discloses:
install a structured query language (SQL) server application on a host server;
Brezis col 4 lines 5-7, For example, where the user has specified the data source to be an SQL server, the connection information can include a host/server identifier (e.g., via IP address or fully-qualified domain name),
install statistical analysis modules on the host server;
Brezis discloses elements of the claimed invention as noted but does not disclose above limitation. However, Rosner discloses:
Rosner [0031] In addition, the back-end portion of the host server 100 can perform statistics gathering and data analytics functionalities in order to, for example, calculate the fair market price, or provide hotel merchants relevant sales data so as to enable the merchants to make educated decisions whether or not to accept, refuse, or counter a bid offer from the customer. This also provides educational value to the hotel merchants so that their asking price/price range for their rooms in the future may be more reflective of the market's demand. Among others, these functionalities promotes the electronic marketplace platform introduced here.
It would have been obvious to one of ordinary skill in the art before the filing date of the claimed invention to modify Brezis to obtain above limitation based on the teachings of Rosner for the purpose of providing educational value to hotel merchants so that their asking price/price range for their rooms in the future may be more reflective of the market's demand.
Furthermore, one of ordinary skill in the art would be motivated to look to the teachings of Rosner. Rosner is analogous art from the same field of invention, i.e., analyzing data stored in a relational database, see below:
[0023] In some variations, the repository 124 can be implemented via object-oriented technology and/or via text files, and can be managed by a distributed database management system, an object-oriented database management system (OODBMS), an object-relational database management system (ORDBMS), a file system, and/or any other suitable database management package.
The above indicates there is a reasonable expectation of success in combining Brezis and Rosner to achieve the claimed invention.
execute the statistical analysis modules within a relational database of the SQL server
application to analyze data stored in the relational database;
Brezis discloses elements of the claimed invention as noted but does not disclose above limitation. However, Chroscielewski discloses:
Chroscielewski [0021] The invention is a human-computer productivity management system with both processes and data systems designed to monitor the interactions between humans and computer systems, log the interactions, securely transmit the data to a centralized server, archive the data, process the data into highly efficient relational database, analyze the data to calculate productivity metrics, distill the data into key business intelligence reports and control the use of the computer systems.
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify Brezis to obtain above limitation based on the teachings of Chroscielewski for the purpose of monitoring and logging interactions between humans and computer systems.
Furthermore, one of ordinary skill in the art would be motivated to look to the teachings of Chroscielewski . Chroscielewski is analogous art from the same field of invention, i.e., analyzing data stored in a relational database, see below:
The invention is a human-computer productivity management system with both processes and data systems designed to monitor the interactions between humans and computer systems, log the interactions, securely transmit the data to a centralized server, archive the data, process the data into highly efficient database, analyze the data to calculate productivity metrics, distill the data into key business intelligence reports and control the use of the computer systems, see abstract.
The above indicates there is a reasonable expectation of success in combining Brezis and Chroscielewski to achieve the claimed invention.
generate outputs based on the execution of the statistical analysis modules within the
relational database.
Chroscielewsk claim 1, A computerized method for managing productivity in a human-computer environment, the method comprising: monitoring human-computer interactions on a plurality of computing devices; logging human-computer interactions on the plurality of computing devices; transmitting logged data, from the plurality of computing devices, to a data management server; indexing and archiving human-computer interaction data in a database; and calculating and displaying statistical information from the archived data.
Claim(s) 7 is/are rejected under 35 U.S.C. 103 as being unpatentable over reference combination A in view of Mozes (US 2017/0308809)
Regarding claim 7, reference combination A discloses elements of the claimed invention as noted but does not disclose wherein to generate the outputs occurs without exporting the data
stored in the relational database.
Mozes [0067] At block 230, the data partitions are analyzed within the relational database system to generate partition metrics data. The partition metrics data include a number of partitions in the training data, a size of each partition in the training data, and a respective value for the partition key associated with each partition in the training data. Other partition metrics data may be possible as well, in accordance with other embodiments. In accordance with one embodiment, metrics logic 125 of analytics logic 110 of FIG. 1 is configured to generate the partition metrics data.
Interpreted per specification [0020]
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify reference combination A to obtain above limitation based on the teachings of Mozes for the purpose of providing a relational database system, having a computing device configured with analytics logic, for generating a composite model object of partitioned data mining models built on partitioned training data, and scoring records of scoring data using the composite model object, see [0006] FIG. 1.
Claim(s) 8 is/are rejected under 35 U.S.C. 103 as being unpatentable over reference combination A in view of Ward (US 2020/0304384).
Regarding claim 8, reference combination A discloses elements of the claimed invention as noted but does not disclose wherein the host server comprises 32 processing cores and 64
gigabytes of random access memory. However, Ward discloses:
Ward [0040] For example, in the illustrated embodiment, the various instance types (small, medium, large and extra large) of the standard instance family 210 may be implementable using a single server type “S1” with 32 processing cores, 64 gigabytes of available main memory and 1600 gigabytes of available disk storage.
Ward [0040] For example, in the illustrated embodiment, the various instance types (small, medium, large and extra large) of the standard instance family 210 may be implementable using a single server type “S1” with 32 processing cores, 64 gigabytes of available main memory and 1600 gigabytes of available disk storage.
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify reference combination A to obtain above limitation based on the teachings of Ward for the purpose of managing flexible capacity pool reservations for network-accessible resources, see [0016]
Claim(s) 9 is/are rejected under 35 U.S.C. 103 as being unpatentable over reference combination A in view of Sihavong (US 2022/0277383) in view of Clode (US 2013/0054440)
Regarding claim 9, reference combination A discloses elements of the claimed invention as noted but does not disclose wherein the outputs comprise a spending trend
Sihavong [0023] Account data 1271 includes financial data from the user's financial accounts. User financial accounts may include user savings accounts, checking accounts, credit card accounts, and any other types of payment accounts. Account data 1271 may include, but is not limited to, a plurality of data features, such as a user identifier (ID), an account number, cash flow, account balances, payment due dates of financial cards accounts, interest charges of the financial card accounts, savings goals, budgets, credit scores, spending trend data, etc. Account data 1271 is associated with transaction data 1272 of corresponding user accounts and corresponding historical user behavior data 1273.
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify reference combination A to obtain above limitation based on the teachings of Sihavong for the purpose of recommending personalized digital nudges designed to influence the user in a manner that furthers a savings goal, see abstract.
Regarding claim 9, reference combination A discloses elements of the claimed invention as noted but does not disclose wherein the outputs comprise a forecast budget run rate.
However, Clode discloses:
Clode [0047] Established budget values may be run through the budget rates or the transactional rates. While assembling a budget vs. transaction report, the actual values may be run through the transactional rates to track finances or through the budget rates to determine budget accuracy. If there is a significant discrepancy in the budget with respect to the actual values, the actual values may be run through the budget rate to identify specific transactions or financial activities that may have caused the discrepancy. If the rate projections are substantially accurate, information may be provided regarding the accuracy of the budget. If the result is near the target budget but differs greatly when using the actual rates, a determination can be made regarding how much of the discrepancy is due to exchange rate variance.
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify reference combination A to obtain above limitation based on the teachings of Clode for the purpose of running through the transactional rates to track finances or through the budget rates to determine budget accuracy.
Claim(s) 10 is/are rejected under 35 U.S.C. 103 as being unpatentable over reference combination A in view of Gilbert (US 2011/0167115).
Regarding claim 10, reference combination A discloses elements of the claimed invention as noted but does not disclose wherein the statistical analysis modules use an R statistical model. However, Gilbert discloses:
Gilbert [0152] The core We Meddle tie strength engine is written in Perl, appropriating the output of an R statistical model, although the engine is not limited by the software language used to implement it. When a user first signs in to We Meddle, the system needs to build a database of tie strengths for each account the user follows. The sign-in forks off hundreds and sometimes thousands of API requests against Twitter. This was the main technical hurdle: overlapping the relational data requests in precisely the right way to support hundreds of simultaneous users.
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify reference combination A to obtain above limitation based on the teachings of Gilbert for the purpose of building a database of tie strengths for each account the user follows.
Claim(s) 11 is/are rejected under 35 U.S.C. 103 as being unpatentable over Brezis (US 11,853,911) in view of Rosner (US 2016/0035019) in view of Chroscielewski (US 2009/0222552)
Regarding claim 11, Brezis discloses:
install a structured query language (SQL) server application on a host server;
Brezis col 4 lines 5-7, For example, where the user has specified the data source to be an SQL server, the connection information can include a host/server identifier (e.g., via IP address or fully-qualified domain name),
install statistical analysis modules on the host server;
Brezis discloses the elements of the claimed invention as noted but does not disclose above limitation. However, Rosner discloses:
Rosner [0031] In addition, the back-end portion of the host server 100 can perform statistics gathering and data analytics functionalities in order to, for example, calculate the fair market price, or provide hotel merchants relevant sales data so as to enable the merchants to make educated decisions whether or not to accept, refuse, or counter a bid offer from the customer. This also provides educational value to the hotel merchants so that their asking price/price range for their rooms in the future may be more reflective of the market's demand. Among others, these functionalities promotes the electronic marketplace platform introduced here.
It would have been obvious to one of ordinary skill in the art before the filing date of the claimed invention to modify Brezis to obtain above limitation based on the teachings of Rosner for the purpose of providing educational value to hotel merchants so that their asking price/price range for their rooms in the future may be more reflective of the market's demand.
Furthermore, one of ordinary skill in the art would be motivated to look to the teachings of Rosner. Rosner is analogous art from the same field of invention, i.e., analyzing data stored in a relational database, see below:
[0023] In some variations, the repository 124 can be implemented via object-oriented technology and/or via text files, and can be managed by a distributed database management system, an object-oriented database management system (OODBMS), an object-relational database management system (ORDBMS), a file system, and/or any other suitable database management package.
The above indicates there is a reasonable expectation of success in combining Brezis and Rosner to achieve the claimed invention.
execute the statistical analysis modules within a relational database of the SQL server
application to analyze data stored in the relational database;
Brezis discloses elements of the claimed invention as noted but does not disclose above limitation. However, Chroscielewski discloses:
Chroscielewski [0021] The invention is a human-computer productivity management system with both processes and data systems designed to monitor the interactions between humans and computer systems, log the interactions, securely transmit the data to a centralized server, archive the data, process the data into highly efficient relational database, analyze the data to calculate productivity metrics, distill the data into key business intelligence reports and control the use of the computer systems.
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify Brezis to obtain above limitation based on the teachings of Chroscielewski for the purpose of monitoring and logging interactions between humans and computer systems.
Furthermore, one of ordinary skill in the art would be motivated to look to the teachings of Chroscielewski . Chroscielewski is analogous art from the same field of invention, i.e., analyzing data stored in a relational database, see below:
The invention is a human-computer productivity management system with both processes and data systems designed to monitor the interactions between humans and computer systems, log the interactions, securely transmit the data to a centralized server, archive the data, process the data into highly efficient database, analyze the data to calculate productivity metrics, distill the data into key business intelligence reports and control the use of the computer systems, see abstract.
The above indicates there is a reasonable expectation of success in combining Brezis and Chroscielewski to achieve the claimed invention.
generate outputs based on the execution of the statistical analysis modules within the
relational database.
Chroscielewsk claim 1, A computerized method for managing productivity in a human-computer environment, the method comprising: monitoring human-computer interactions on a plurality of computing devices; logging human-computer interactions on the plurality of computing devices; transmitting logged data, from the plurality of computing devices, to a data management server; indexing and archiving human-computer interaction data in a database; and calculating and displaying statistical information from the archived data
Claim(s) 12 is/are rejected under 35 U.S.C. 103 as being unpatentable over reference combination A in view of Mozes (US 2017/0308809)
Regarding claim 12, reference combination A discloses elements of the claimed invention as noted but does not disclose wherein to generate the outputs occurs without exporting the data
stored in the relational database. However, Mozes discloses:
Mozes [0067] At block 230, the data partitions are analyzed within the relational database system to generate partition metrics data. The partition metrics data include a number of partitions in the training data, a size of each partition in the training data, and a respective value for the partition key associated with each partition in the training data. Other partition metrics data may be possible as well, in accordance with other embodiments. In accordance with one embodiment, metrics logic 125 of analytics logic 110 of FIG. 1 is configured to generate the partition metrics data.
Interpreted per specification [0020]
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify reference combination A to obtain above limitation based on the teachings of Mozes for the purpose of providing a relational database system, having a computing device configured with analytics logic, for generating a composite model object of partitioned data mining models built on partitioned training data, and scoring records of scoring data using the composite model object, see [0006] FIG. 1.
Claim(s) 13 is/are rejected under 35 U.S.C. 103 as being unpatentable over reference combination A in view of Ward (US 2020/0304384).
Regarding claim 13, reference combination A discloses elements of the claimed invention as noted but does not disclose wherein the host server comprises 32 processing cores and 64
gigabytes of random access memory. However, Ward discloses:
Ward [0040] For example, in the illustrated embodiment, the various instance types (small, medium, large and extra large) of the standard instance family 210 may be implementable using a single server type “S1” with 32 processing cores, 64 gigabytes of available main memory and 1600 gigabytes of available disk storage.
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify reference combination A to obtain above limitation based on the teachings of Ward for the purpose of managing flexible capacity pool reservations for network-accessible resources, see [0016]
Claim(s) 14 is/are rejected under 35 U.S.C. 103 as being unpatentable over reference combination A in view of Sihavong (US 2022/0277383) in view of Clode (US 2013/0054440)
Regarding claim 14, reference combination A discloses elements of the claimed invention as noted but does not disclose wherein the outputs comprise a spending trend. However, Sihavong discloses:
Sihavong [0023] Account data 1271 includes financial data from the user's financial accounts. User financial accounts may include user savings accounts, checking accounts, credit card accounts, and any other types of payment accounts. Account data 1271 may include, but is not limited to, a plurality of data features, such as a user identifier (ID), an account number, cash flow, account balances, payment due dates of financial cards accounts, interest charges of the financial card accounts, savings goals, budgets, credit scores, spending trend data, etc. Account data 1271 is associated with transaction data 1272 of corresponding user accounts and corresponding historical user behavior data 1273.
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify reference combination A to obtain above limitation based on the teachings of Sihavong for the purpose of recommending personalized digital nudges designed to influence the user in a manner that furthers a savings goal, see abstract.
Regarding claim 14, reference combination A discloses elements of the claimed invention as noted but does not disclose wherein the outputs comprise a forecast
budget run rate. However, Clode discloses:
Clode [0047] Established budget values may be run through the budget rates or the transactional rates. While assembling a budget vs. transaction report, the actual values may be run through the transactional rates to track finances or through the budget rates to determine budget accuracy. If there is a significant discrepancy in the budget with respect to the actual values, the actual values may be run through the budget rate to identify specific transactions or financial activities that may have caused the discrepancy. If the rate projections are substantially accurate, information may be provided regarding the accuracy of the budget. If the result is near the target budget but differs greatly when using the actual rates, a determination can be made regarding how much of the discrepancy is due to exchange rate variance.
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify reference combination A to obtain above limitation based on the teachings of Clode for the purpose of running through the transactional rates to track finances or through the budget rates to determine budget accuracy.
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/ETIENNE P LEROUX/Primary Examiner of Art Unit 2161