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 .
DETAILED ACTION
This action is in reply to the amendment filed on 11/20/2025.
Claims 1, 8, 16 and 17 have been amended.
Claims 1-17 are pending and have been examined.
Response to Arguments
With regard to the Double Patenting rejection, the rejection is maintained since the claims of both the parent and grandparent case still cover the scope of the amended claims.
With regard to the 101 rejection, the arguments have been considered but they are not persuasive. The Applicant asserted that the amended claims of the instant case “. . . are not directed to an abstract idea under Step 2A, and (3) the claims include additional elements that amount to significantly more . . .” However, the claim recited concept of associating geolocation with credit risk, and thus, is directed to business relations – commercial interactions (Certain Methods of Organizing Human Activity).
In step 2A Prong Two, the applicant cited Enfish, LLC, and asserted that the recited judicial exception is integrated into a practical application. However, The Examiner does not see the parallel between the claims of the instant case and those of Enfish. In Enfish, the claims describe the steps of configuring a computer memory in accordance with a self-referential table, in both method and system claims. The focus of the claims in Enfish is on the specific asserted improvement in computer capabilities (i.e., the self-referential table for a computer database). Specifically, the claimed invention in Enfish achieves other benefits over conventional databases, such as increased flexibility, faster search times, and smaller memory requirements. Hence, the Enfish claims were not directed to an abstract idea. On the other hand, the Applicant’s claims do not involve any improvements to another technology, technical field, or improvements to the functioning of the computer itself. The invention in Enfish was a technological solution to a technological problem (using self-referential table for a computer database rather than using conventional table for a computer database), whereas the Applicants’ invention is a business solution to a problem rooted in an abstract idea.
Simply executing an abstract concept on a computer does not render a computer "specialized," nor does it transform a patent-ineligible claim into a patent-eligible one. See Bancorp Servs., LLC v. Sun Life Assurance Co. of Can., 687 F.3d 1266, 1280 (Fed. Cir. 2012).
In Bilski and in Alice, the specific features of the claimed method/system did not change the fact that the claims were drawn to an abstract idea. This interpretation of this abstract idea is based in light of the Alice decision and the updates in the MPEP. Hence the claims are drawn to an abstract idea.
Furthermore, the Applicant cited McRo, Inc., and asserted that Claim 1 is “directed to a specific means or method that improves the relevant technology’. . .” However, The Examiner does not see the parallel between the claims of the instant case and those of McRo (McRo, Inc. v. Bandai Namco Games Am., 2015-1080 (Fed. Cir. Sept. 13, 2016)). In McRo the patents relate to “automating part of a preexisting 3-D animation method”, which were to be done manually before the issuance of the patent. The claims were directed to an asserted improvement in computer animation technology such as directed to a patentable technological improvement over the existing, manual 3D animation techniques. In other words, “the claims are limited to rules with specific characteristics” which allow for the improvement realized by the invention. Specifically at McRo *22, “As the specification confirms, the claimed improvement here is allowing computers to produce “accurate and realistic lip synchronization and facial expressions in animated characters” that previously could only be produced by human animators. ’576 patent col. 2 ll. 49–50.” Hence the claims in McRo were patent eligible because they recited significantly more than an abstract idea. However, the Applicants’ invention is a business solution to a problem rooted in an abstract idea as stated multiple times above. The claimed limitations and the claimed computing functionality does not incorporate a complex set of rules which allow the computer to be improved. In contrast, the claimed functions such as “obtaining data generated . . .”, “creating . . . a set of data tables”, “creating and storing . . . cross-references between at least one location indicator . . .”, “generating and storing . . . geo-spatial area”, “identifying . . .at least one security”, “updating . . data table”, “generating an interactive GUI . . .” are conventional functions of a computer system. The computer is merely a platform on which the abstract idea is implemented. Hence, the limitations are not indicative of integration into a practical application. They are Adding the words “apply it” (or an equivalent) with the judicial exception, or mere instructions to implement an abstract idea on a computer, or merely uses a computer as a tool to perform an abstract idea - see MPEP 2106.05(f).
Under Step 2B Prong Two, the Applicant asserted that the “pending claims recite significantly more than any abstract idea. The Applicant then cited BASCOM, and alleged that the claim recited an “inventive concept”. The Examiner, however, does not see the parallel between the claims of the instant case and those of Bascom. In Bascom, the claims describe a filtering system by providing customized filters at a remote server. Specifically, in Bascom an ISP server receives a request to access a website, associates the request with a particular user, and identifies the requested website. The filtering tool then applies the filtering mechanism associated with the particular user to the requested website to determine whether the user associated with that request is allowed access to the website. The filtering tool returns either the content of the website to the user, or a message to the user indicating that the request was denied. In Bascom another group of claims describe a hybrid filtering scheme implemented on the ISP server comprised of a master-inclusive list, an individual-customizable set of exclusive lists, and an individual-customizable set of inclusive lists. The focus of the claims in Bascom is on the specific asserted improvement in filtering technology by providing individually customizable filtering at the remote ISP server by taking advantage of the technical capability of certain communication networks. Specifically, the claimed invention in Bascom achieves other benefits over conventional filtering by providing Internet-content filtering in a manner that can be customized for a person attempting to access such content while avoiding the need for (potentially millions of) local servers or computers to perform such filtering and while being less susceptible to circumvention by the user, and structuring a filtering scheme not just to be effective, but also to make user-level customization administrable as users are added instead of becoming intractably complex. Hence the Bascom claims are not directed to an abstract idea. On the other hand the Applicant’s claims do not involve any improvements to another technology, technical field, or improvements to the functioning of the computer itself. The invention in Bascom was a technological solution to a technological problem (using an improved filtering technology rather than using conventional filtering technology). Whereas the Applicants’ invention is a business solution to a problem rooted in an abstract idea. The arrangement of obtaining data from one or more data source systems, creating a set of data tables, creating and storing in a set of data tables, identifying at least one security of the security data, creating one or more links among the identified at least one security, storing the instrument-level data, updating the set of data table, generating a displaying does not involve any improvements to another technology, technical field, or improvements to the functioning of the computer itself.
The limitations are not indicative of an inventive concept (aka “significantly more”): Adding the words “apply it” (or an equivalent) with the judicial exception, or mere instructions to implement an abstract idea on a computer, or merely uses a computer as a tool to perform an abstract idea - see MPEP 2106.05(f).
Therefore, the claim is not patent eligible under both Step 2A and 2B analysis. The 101 rejection is maintained.
With regard to the 103 rejection, the arguments have been considered but they are not persuasive. The applicant has sufficiently amended the claim, and thus, the argument(s) are moot over new ground of rejections. The examiner cited the reference Kamalski (US 2009/0165120 A1) to teach the added limitation. It would be obvious to one of ordinary skill in the art before the effective filing date to combine the features of converting data into a tabular data format as taught by Kamalski with the elements such as creating credit risk indicators disclosed by Heath in view of Diriye in further view of Coogan-Pushner to help encoding location data (abstract). Therefore, the combination is obvious.
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 1-17 are rejected on the ground of nonstatutory double patenting as being unpatentable over claims 1-17 of U.S. Patent No. 12,175, 530 (parent case). Although the claims at issue are not identical, they are not patentably distinct from each other because the claims in the parent case anticipated the claims in the instant application.
Claims 1-17 are rejected on the ground of nonstatutory double patenting as being unpatentable over claims 1-16 of U.S. Patent No. 11,961,139 (grandparent case). Although the claims at issue are not identical, they are not patentably distinct from each other because the claims in the grandparent case anticipated the claims in the instant application.
Current Application – 18/937,905
U.S. Patent No. – 12,175,530
Claim 1: A system for geographical mapping and linking of disparate data structures for interaction, the system comprising: at least one server in communication with one or more data source systems, the at least one server configured to: obtain data generated from among the one or more data source systems, the data comprising geo-spatial data comprising a plurality of geo-spatial areas having disparate formats, security data, and additional data comprising one or more of economic data and demographic data; create, in at least one storage structure, a set of data tables; identify a relationship between a location identifier and one or more geo-spatial areas of the plurality of geo-spatial areas outside of an area defined by the location identifier based on at least one statistical algorithm configured to determine a best fit; create, using a geo-spatial join process, a cross-reference between the location identifier and the one or more geo-spatial areas, the geo-spatial join process comprising: converting the geo-spatial data associated with the location identifier into first data having a tabular format, converting the geo-spatial data associated with the one or more geo-spatial areas into second data having the tabular format, and merging the first data and the second data via a tabular operation; store, in a first data table among the set of data tables, the cross-reference indexed by the location identifier create and store, in a second data table among the set of data tables, for each of the one or more geo-spatial areas, an indicator based on the additional data; identify a security within the security data, the security associated with the location identifier; query the first data table for the location identifier to identify the cross-reference; create one or more links between the security, the one or more geo-spatial areas, and the indicator, based on the cross-reference;form instrument-level data for the security including the indicator; store, in a third data table among the set of data tables, the instrument-level data for the security; update the set of data tables in response to any changes in the data obtained from the one or more data source systems, by at least one of: updating one or more existing data entries stored among the set of data tables and adding one or more new data entries among the set of data tables; and generate an interactive graphical user interface (GUI) configured for display on one or more of an interactive webpage and a mobile application, the interactive GUI comprising one or more user tools configured to query the set of data tables including any updated data entries and any added data entries, wherein the at least one server is configured to disseminate at least one of the instrument-level data and the indicator data to at least one dissemination entity.
2. (Previously Presented) The system of claim 1, wherein the at least one server is configured to disseminate at least one of the instrument-level data and the indicator to at least one dissemination entity.
3. (Original) The system of claim 2, wherein the at least one dissemination entity comprises at least one of a client device, an external distribution system, a delivery platform and an external database.
4. (Original) The system of claim 1, wherein the geo-spatial data comprises one or more of demographic data, economic data, social data and healthcare data.
5. (Original) The system of claim 1, wherein the additional data is associated with at least one of the one or more geo-spatial areas, the additional data comprising one or more of population data, income data, migration data, labor data, housing data, education data and healthcare data.
6. (Original) The system of claim 1, wherein the one or more geo-spatial areas comprise one or more of at least one city, at least one subdivision, at least one county, at least one state, a multi-state area, a metropolitan statistical area, a micropolitan statistical area and a core base statistical area.
7. (Currently Amended) The system of claim 1, wherein the location identifier comprises one or more zip codes.
8. (Original) The system of claim 1, wherein the at least one predetermined criteria includes one or more of a coverage area and a population density.
9. (Original) The system of claim 1, wherein the at least one server is configured to continually monitor the data among the one or more data source systems in at least one of real- time or near real-time and obtain the data responsive to the monitoring.
10. (Original) The system of claim 1, wherein the at least one server is configured to determine at least one of a score and a ranking of the indicator based on at least one predetermined attribute of the additional data.
11. (Original) The system of claim 1, wherein the at least one server is configured to store the geo-spatial data, the security data and the additional data in one or more data tables associated with the at least one storage structure.
12. (Original) The system of claim 11, wherein the at least one server is configured to one or more of filter, normalize and format, using a data integrator tool associated with the at least one server, at least a portion of the data among the geo-spatial data, the security data, and the additional data, prior to entry within the one or more data tables.
13. (Original) The system of claim 1, wherein the at least one storage structure comprises one or more of at least one database and at least one in-memory cache.
14. (Original) The system of claim 1, wherein the identified at least one security comprises at least one municipal security.
15. (Original) The system of claim 1, wherein the at least one server is configured to receive user input via the one or more user tools, the user input associated with at least one of querying the third data table and creating user-customized instrument-level data.
16. (Original) The system of claim 1, wherein: the one or more links comprise a first link and a second link, the first link being created between the security and at least one among the one or more geo-spatial areas based on the one or more cross-references in the first data table, and the second link being created between the indicator in the second data table and the identified at least one security based on the first link, to form the instrument-level data for the identified at least one security.
17. (Currently Amended) The system of claim 1, wherein the at least one server is configured to map the location identifier to the one or more geo-spatial areas based on a maximum area of intersection between theidentifier in accordance with the at least one predetermined criteria.
1. A method for geographical mapping and linking of disparate data structures for interaction, the method comprising: obtaining, via at least one server in communication with one or more data source systems, data generated from among the one or more data source systems, the data comprising geo-spatial data, security data, and additional data,
creating, in at least one storage structure, a set of data tables,
creating and storing, by the at least one server, in a first data table among the set of data tables, one or more cross-references between one or more location indicators and one or more geo- spatial areas based on at least one statistical algorithm, in accordance with the geo-spatial data, wherein the at least one statistical algorithm is configured to query the geo-spatial data and map the one or more location indicators to the one or more geo-spatial areas in accordance with at least one predetermined criteria;
generating and storing, by the at least one server, for each of the one or more geo-spatial areas, at least one credit risk indicator based on the additional data, to form credit risk indicator data stored in a second data table among the set of data tables;
identifying, by the at least one server, at least one security of the security data, the identified at least one security associated with at least one among the one or more location indicators;
creating, by the at least one server, one or more Hinks among the identified at least one security, the one or more geo-spatial areas and the at least one credit risk indicator among the credit risk indicator data, based on the one or more cross-references in the first data table, to form instrument-level data for the identified at least one security including the at least one credit risk indicator; storing the instrument-level data for the identified at least one security in a third data table among the set of data tables; updating the set of data tables in response to any changes in the data obtained from the one or more data source systems, by at least one of updating one or more existing data entries stored among the set of data tables and adding one or more new data entries among the set of data tables: and generating an interactive graphical user interface (GUD vie at least one interactive webpage, the interactive GUI comprising one or more user tools configured to query the set of data tables including any updated data entries and any added data entries.
2. The method of claim 1, the method further comprising:
disseminating, by the at least one server, at least one of the instrument-level date and the credit risk indicator data to at least one dissemination entity.
3. The method of claim 2, wherein the at least one dissemination entity comprises at least one of a client device, an external distribution system, a delivery platform and an external database.
4. The method of claim 1, wherein the geo-spatial data comprises one or more of demographic data, economic data, social data and healthcare data.
5, The method of claim 1, wherein the additional data is associated with at least one of the one or more geo-spatial areas, the additional data comprising one or more of population data, income data, migration data, labor data, housing data, education data and healthcare data.
6. The method of claim 1, wherein the one or more geo-spatial areas comprise one or more of at least one city, at least one subdivision, at least one county, at least one state, a multi-state arca, a metropolitan statistical area, a micropolitan statistical area and a core base statistical area.
7. The method of claim 1, wherein the one or more location indicators comprise ate or more zip codes.
8. The method of claim 1, wherein the at least one predetermined criteria includes one or more of 4 coverage area and a population density.
9. The method of claim 1, the method further comprising: continually monitoring, vie the at least one server, the data among the one or more data source systems in at least one of real-time or near real-time; and obtaining the data responsive to the monitoring.
10. The method of claim 1, the method further comprising: determining, by the at least one server, at least one of a score and a ranking of the at least one credit risk indicator based on at least one predetermined attribute of the additional data.
11. The method of claim 1, the method further comprising: storing the goo-spatial data, the security data and the additional data in one or more data tables associated with the at least one storage structure.
12. The method of claim 11, the method further comprising:
one or more of filtering, normalizing and formatting, using a data integrator tool associated with the at least one server, at least a portion of the data among the geo-spatial data, the security data, and the additional data, prior to entry within the one or more data tables.
13. The method of claim 1, wherein the at least one storage structure comprises one or more of at least one database and at least one in-memory cache.
14. The method of claim 1, wherein the identified at least one security comprises at least one municipal security.
15. The method of claim 1, the method further comprising:
receiving, try the at least one server, user input via the one or more user tools, the user input associated with at least one of querying the third data table and creating user-customized instrument-level data.
16. The method of claim 1, wherein the one or more links comprise a first link and a second link, the method further comprising:
creating the first link between the identified at least one security and at least one among the one or more geo-spatial areas based on the one or more cross-references in the first data table, and creating the second link between the at least one credit risk indicator among the credit risk indicator data in the second data table and the identified at least one security based on the first link, to form the instrument-level data for the identified at least one security.
17. The method of claim 1, further comprising: mapping the one or more location indicators to the one or more geo-spatial areas based on a maximum area of intersection between the one or more location indicators in accordance with the at least one predetermined criteria.
Current Application – 18/937,905
U.S. Patent No. – 11,961,139
Claim 1: A system for geographical mapping and linking of disparate data structures for interaction, the system comprising: at least one server in communication with one or more data source systems, the at least one server configured to: obtain data generated from among the one or more data source systems, the data comprising geo-spatial data comprising a plurality of geo-spatial areas having disparate formats, security data, and additional data comprising one or more of economic data and demographic data; create, in at least one storage structure, a set of data tables; identify a relationship between a location identifier and one or more geo-spatial areas of the plurality of geo-spatial areas outside of an area defined by the location identifier based on at least one statistical algorithm configured to determine a best fit; create, using a geo-spatial join process, a cross-reference between the location identifier and the one or more geo-spatial areas, the geo-spatial join process comprising: converting the geo-spatial data associated with the location identifier into first data having a tabular format, converting the geo-spatial data associated with the one or more geo-spatial areas into second data having the tabular format, and merging the first data and the second data via a tabular operation; store, in a first data table among the set of data tables, the cross-reference indexed by the location identifier create and store, in a second data table among the set of data tables, for each of the one or more geo-spatial areas, an indicator based on the additional data; identify a security within the security data, the security associated with the location identifier; query the first data table for the location identifier to identify the cross-reference; create one or more links between the security, the one or more geo-spatial areas, and the indicator, based on the cross-reference;form instrument-level data for the security including the indicator; store, in a third data table among the set of data tables, the instrument-level data for the security; update the set of data tables in response to any changes in the data obtained from the one or more data source systems, by at least one of: updating one or more existing data entries stored among the set of data tables and adding one or more new data entries among the set of data tables; and generate an interactive graphical user interface (GUI) configured for display on one or more of an interactive webpage and a mobile application, the interactive GUI comprising one or more user tools configured to query the set of data tables including any updated data entries and any added data entries, wherein the at least one server is configured to disseminate at least one of the instrument-level data and the indicator data to at least one dissemination entity.
2. (Previously Presented) The system of claim 1, wherein the at least one server is configured to disseminate at least one of the instrument-level data and the indicator to at least one dissemination entity.
3. (Original) The system of claim 2, wherein the at least one dissemination entity comprises at least one of a client device, an external distribution system, a delivery platform and an external database.
4. (Original) The system of claim 1, wherein the geo-spatial data comprises one or more of demographic data, economic data, social data and healthcare data.
5. (Original) The system of claim 1, wherein the additional data is associated with at least one of the one or more geo-spatial areas, the additional data comprising one or more of population data, income data, migration data, labor data, housing data, education data and healthcare data.
6. (Original) The system of claim 1, wherein the one or more geo-spatial areas comprise one or more of at least one city, at least one subdivision, at least one county, at least one state, a multi-state area, a metropolitan statistical area, a micropolitan statistical area and a core base statistical area.
7. (Currently Amended) The system of claim 1, wherein the location identifier comprises one or more zip codes.
8. (Original) The system of claim 1, wherein the at least one predetermined criteria includes one or more of a coverage area and a population density.
9. (Original) The system of claim 1, wherein the at least one server is configured to continually monitor the data among the one or more data source systems in at least one of real- time or near real-time and obtain the data responsive to the monitoring.
10. (Original) The system of claim 1, wherein the at least one server is configured to determine at least one of a score and a ranking of the indicator based on at least one predetermined attribute of the additional data.
11. (Original) The system of claim 1, wherein the at least one server is configured to store the geo-spatial data, the security data and the additional data in one or more data tables associated with the at least one storage structure.
12. (Original) The system of claim 11, wherein the at least one server is configured to one or more of filter, normalize and format, using a data integrator tool associated with the at least one server, at least a portion of the data among the geo-spatial data, the security data, and the additional data, prior to entry within the one or more data tables.
13. (Original) The system of claim 1, wherein the at least one storage structure comprises one or more of at least one database and at least one in-memory cache.
14. (Original) The system of claim 1, wherein the identified at least one security comprises at least one municipal security.
15. (Original) The system of claim 1, wherein the at least one server is configured to receive user input via the one or more user tools, the user input associated with at least one of querying the third data table and creating user-customized instrument-level data.
16. (Original) The system of claim 1, wherein: the one or more links comprise a first link and a second link, the first link being created between the security and at least one among the one or more geo-spatial areas based on the one or more cross-references in the first data table, and the second link being created between the indicator in the second data table and the identified at least one security based on the first link, to form the instrument-level data for the identified at least one security.
17. (Currently Amended) The system of claim 1, wherein the at least one server is configured to map the location identifier to the one or more geo-spatial areas based on a maximum area of intersection between theidentifier in accordance with the at least one predetermined criteria.
1. A method for geographical mapping and linking of disparate data structures for interaction, the method comprising: obtaining and storing, in at least one storage structure, via at least one server in communication with one or more data source systems, data generated from among the one or more data source systems, the data comprising geo-spatial data, security data, and additional data; creating, in the at least one storage structure, filtered data tables including at least one first data table, at least one second data table, and at least one third data table; creating, by the at least one server, one or more cross-references between one or more location indicators and one or more geo-spatial areas based on at least one statistical algorithm, in accordance with the geo-spatial data, wherein the at least one statistical algorithm is configured to query the geo-spatial data and map the one or more location indicators to the one or more geo-spatial areas based on a maximum area of intersection between the one or more location indicators in accordance with at least one predetermined criteria; storing the one or more cross-references in the at least one first data table; generating, by the at least one server, for each of the one or more geo-spatial areas, at least one credit risk indicator based on the additional data, to form credit risk indicator data; storing the credit risk indicator data in the at least one second data table; identifying, by the at least one server, at least one security of the security data, the identified at least one security associated with at least one among the one or more location indicators; creating, by the at least one server, one or more links among the identified at least one security, the one or more geo-spatial areas and the at least one credit risk indicator among the credit risk indicator data, based on the one or more cross-references in the at least one first data table, to form instrument-level data for the identified at least one security including the at least one credit risk indicator; storing the instrument-level data for the identified at least one security in the at least one third data table; at least one of: updating one or more existing data entries stored among the filtered data tables and adding one or more new data entries among the filtered data tables in response to any changes in the data obtained from the one or more data source systems; and generating an interactive graphical user interface (GUI) via at least one interactive webpage, the interactive GUI comprising one or more user tools, the one or more user tools configured to query the filtered data tables including any updated data entries and any added data entries.
2. The method of claim 1, the method further comprising: disseminating, by the at least one server, at least one of the instrument-level data and the credit risk indicator data to at least one dissemination entity.
3. The method of claim 2, wherein the at least one dissemination entity comprises at least one of a client device, an external distribution system, a delivery platform and an external database.
4. The method of claim 1, wherein the geo-spatial data comprises one or more of demographic data, economic data, social data and healthcare data.
5. The method of claim 1, wherein the additional data is associated with at least one of the one or more geo-spatial areas, the additional data comprising one or more of population data, income data, migration data, labor data, housing data, education data and healthcare data.
6. The method of claim 1, wherein the one or more geo-spatial areas comprise one or more of at least one city, at least one subdivision, at least one county, at least one state, a multi-state area, a metropolitan statistical area, a micropolitan statistical area and a core base statistical area.
7. The method of claim 1, wherein the one or more location indicators comprise one or more zip codes.
8. The method of claim 1, wherein the at least one predetermined criteria includes one or more of a coverage area and a population density.
9. The method of claim 1, the method further comprising: continually monitoring, via the at least one server, the data among the one or more data source systems in at least one of real-time or near real-time; and obtaining the data responsive to the monitoring.
10. The method of claim 1, the method further comprising: determining, by the at least one server, at least one of a score and a ranking of the at least one credit risk indicator based on at least one predetermined attribute of the additional data.
11. The method of claim 1, the method further comprising: storing the obtained geo-spatial data, the security data and the additional data in one or more data tables associated with the at least one storage structure.
12. The method of claim 1, the method further comprising: converting, using a data integrator tool associated with the at least one server, at least a portion of the data among the geo-spatial data, the security data, and the additional data from at least one non-standardized format into a common format, prior to entry and storage within the filtered data tables.
13. The method of claim 1, wherein the at least one storage structure comprises one or more of at least one database and at least one in-memory cache.
14. The method of claim 1, wherein the identified at least one security comprises at least one municipal security.
15. The method of claim 1, the method further comprising: receiving, by the at least one server, user input via the one or more user tools, the user input associated with at least one of querying the at least one third data table and creating user-customized instrument-level data.
16. The method of claim 1, wherein the one or more links comprise a first link and a second link, the method further comprising: creating the first link between the identified at least one security and at least one among the one or more geo-spatial areas based on the one or more cross-references in the at least one first data table, and creating the second link between the at least one credit risk indicator among the credit risk indicator data in the at least one second data table and the identified at least one security based on the first link, to form the instrument-level data for the identified at least one security.
Claim Rejections - 35 USC § 101
35 U.S.C. 101 reads as follows:
Whoever invents or discovers any new and useful process, machine, manufacture, or composition of matter, or any new and useful improvement thereof, may obtain a patent therefor, subject to the conditions and requirements of this title.
Claims 1-17 are directed to a system which is one of the statutory categories of invention. (Step 1: YES).
Claims 1-17 are rejected under 35 U.S.C. 101 because the claimed invention is directed to a judicial exception (i.e., a law of nature, a natural phenomenon, or an abstract idea) without significantly more. The claims do not include additional elements that are sufficient to amount to significantly more than the judicial exception because the additional computer elements, which are recited at a high level of generality, provide generic computer functions that do not add meaningful limits to practicing the abstract idea.
Claim 1, in part, recites a system for geographical mapping and linking of disparate data structures for interaction, the system comprising: at least one server in communication with one or more data source systems, the at least one server configured to: obtain data generated from among the one or more data source systems, the data comprising geo-spatial data comprising a plurality of geo-spatial areas having disparate formats, security data, and additional data; create, in at least one storage structure, a set of data tables; identify a relationship between a location identifier and one or more geo-spatial areas of the plurality of geo-spatial areas outside of an area defined by the location identifier based on at least one statistical algorithm configured to determine a best fit; create, using a geo-spatial join process, a cross-reference between the location identifier and the one or more geo-spatial areas, the geo-spatial join process comprising: converting the geo-spatial data associated with the location identifier into first data having a tabular format, converting the geo-spatial data associated with the one or more geo-spatial areas into second data having the tabular format, and merging the first data and the second data via a tabular operation; store, in a first data table among the set of data tables, the cross-reference indexed by the location identifier; create and store, in a second data table among the set of data tables, for each of the one or more geo-spatial areas, an indicator based on the additional data; identify a security within the security data, the associated with the location identifier; query the first data table for the location identifier to identify the cross-references; create one or more links between the security, the one or more geo-spatial areas, and the indicator, based on the cross-references, to form instrument-level data for the security including the indicator; store, in a third data table among the set of data tables, the instrument-level data for the security; update the set of data tables in response to any changes in the data obtained from the one or more data source systems, by at least one of: updating one or more existing data entries stored among the set of data tables and adding one or more new data entries among the set of data tables; and generate an interactive graphical user interface (GUI) configured for display on one or more of an interactive webpage and a mobile application, the interactive GUI comprising one or more user tools configured to query the set of data tables including any updated data entries and any added data entries. The concept here is similar to the concept of geo-spatial mapping with credit risk indicators. Such concept is directed to business relations – commercial interactions. Hence, they fall within the “Certain Methods of Organizing Human Activity” grouping of abstract ideas.
This judicial exception is not integrated into a practical application. In particular, the claim only recites additional elements such as at least a system, data source systems, one server, one storage structure, an interactive graphical user interface (GUI), an interactive webpage, and other generic computer components to perform identifying, storing, displaying. The generic computer components are recited at a high-level of generality (identifying, storing, and displaying) such that it amounts no more than mere instructions to apply the exception using a generic computer component. Accordingly, these additional elements do not integrate the abstract idea into a practical application because they do not impose any meaningful limits on practicing the abstract idea. Hence, the claim is directed to an abstract idea
Next the claim as a whole is analyzed to determine whether any element, or combination of elements, is sufficient to ensure the claim amounts to significantly more than an abstract idea. Claim 1 does not include additional elements such as a system, data source systems, one storage structure, a location identifier, an interactive graphical user interface (GUI), that are sufficient to amount to significantly more than the judicial exception because the additional elements of at least a computing device to perform receiving and identifying data are merely additional elements performing the abstract idea on a generic device i.e., abstract idea and apply it. There is no improvement to computer technology or computer functionality MPEP 2106.05(a) nor a particular machine MPEP 2106.05(b) nor a particular transformation MPEP 2106.05(c). Additionally, the limitation of sending a request or message over network is recognized as well-understood, routine, conventional activity. Receiving or transmitting data over a network, e.g., using the Internet to gather data, Symantec, 838 F.3d at 1321, 120 USPQ2d at 1362 (utilizing an intermediary computer to forward information); TLI Communications LLC v. AV Auto. LLC, 823 F.3d 607, 610, 118 USPQ2d 1744, 1745 (Fed. Cir. 2016) (using a telephone for image transmission); OIP Techs., Inc., v. Amazon.com, Inc., 788 F.3d 1359, 1363, 115 USPQ2d 1090, 1093 (Fed. Cir. 2015) see MPEP 2106.05(d). Furthermore, the limitations are not indicative of integration into a practical application because they are merely adding the words “apply it” to a judicial exception on a generic computing device. See MPEP 2106.05(f). Given the above reasons, a generic processing device associating geospatial area with risk indicators is not an Inventive Concept. Thus, the claim is not patent eligible.
The dependent claims have been given the full two part analysis (Step 2A – 2-prong tests and step 2B) including analyzing the additional limitations both individually and in combination. The Dependent claim(s) when analyzed both individually and in combination are also held to be patent ineligible under 35 U.S.C. 101 because for the same reasoning as above and the additional recited limitation(s) fail(s) to establish that the claim(s) is/are not directed to an abstract idea. The additional limitations of the dependent claim(s) when considered individually and as ordered combination do not amount to significantly more than the abstract idea.
Claims 2, 3, 4, 5 are rejected under 35 U.S.C. 101 because the claimed invention is directed to judicial exception (i.e., a law of nature, a natural phenomenon, or an abstract idea) without significantly more. The claim(s) recite(s) a method of disseminating data. This judicial exception is not integrated into a practical application because the limitations are adding the words “apply it” (or an equivalent) with the judicial exception, or mere instructions to implement an abstract idea on a computer, or merely uses a computer as a tool to perform an abstract idea - see MPEP 2106.05(f). The claim(s) does/do not include additional elements (such as an entity, a client device, a system, an external distribution system, a delivery platform, an external database) that are sufficient to amount to significantly more than the judicial exception because the limitations are adding the words “apply it” (or an equivalent) with the judicial exception, or mere instructions to implement an abstract idea on a computer, or merely uses a computer as a tool to perform an abstract idea - see MPEP 2106.05(f).
Claims 6, 7, 8 are rejected under 35 U.S.C. 101 because the claimed invention is directed to judicial exception (i.e., a law of nature, a natural phenomenon, or an abstract idea) without significantly more. The claim(s) recite(s) area, population density and zip codes. This judicial exception is not integrated into a practical application because the limitations are Adding the words “apply it” (or an equivalent) with the judicial exception, or mere instructions to implement an abstract idea on a computer, or merely uses a computer as a tool to perform an abstract idea - see MPEP 2106.05(f). The claim(s) does/do not include additional elements (such as a GUI) that are sufficient to amount to significantly more than the judicial exception because the limitations are adding the words “apply it” (or an equivalent) with the judicial exception, or mere instructions to implement an abstract idea on a computer, or merely uses a computer as a tool to perform an abstract idea - see MPEP 2106.05(f).
Claims 9, 10, 11 are rejected under 35 U.S.C. 101 because the claimed invention is directed to judicial exception (i.e., a law of nature, a natural phenomenon, or an abstract idea) without significantly more. The claim(s) recite(s) a method of monitoring data, determining a ranking, storing security data. This judicial exception is not integrated into a practical application because the limitations are Adding the words “apply it” (or an equivalent) with the judicial exception, or mere instructions to implement an abstract idea on a computer, or merely uses a computer as a tool to perform an abstract idea - see MPEP 2106.05(f). The claim(s) does/do not include additional elements (one server, data source systems, a ranking, one storage structure) that are sufficient to amount to significantly more than the judicial exception because the limitations are adding the words “apply it” (or an equivalent) with the judicial exception, or mere instructions to implement an abstract idea on a computer, or merely uses a computer as a tool to perform an abstract idea - see MPEP 2106.05(f).
Claim 12 is rejected under 35 U.S.C. 101 because the claimed invention is directed to judicial exception (i.e., a law of nature, a natural phenomenon, or an abstract idea) without significantly more. The claim(s) recite(s) a method of filtering, normalizing and formatting data. This judicial exception is not integrated into a practical application because the limitations are Adding the words “apply it” (or an equivalent) with the judicial exception, or mere instructions to implement an abstract idea on a computer, or merely uses a computer as a tool to perform an abstract idea - see MPEP 2106.05(f). The claim(s) does/do not include additional elements (such as a server) that are sufficient to amount to significantly more than the judicial exception because the limitations are adding the words “apply it” (or an equivalent) with the judicial exception, or mere instructions to implement an abstract idea on a computer, or merely uses a computer as a tool to perform an abstract idea - see MPEP 2106.05(f).
Claim 13, 14, 15 are rejected under 35 U.S.C. 101 because the claimed invention is directed to judicial exception (i.e., a law of nature, a natural phenomenon, or an abstract idea) without significantly more. The claim(s) recite(s) database and memory catch, municipal security and creating customized instrument level data. This judicial exception is not integrated into a practical application because the limitations are Adding the words “apply it” (or an equivalent) with the judicial exception, or mere instructions to implement an abstract idea on a computer, or merely uses a computer as a tool to perform an abstract idea - see MPEP 2106.05(f). The claim(s) does/do not include additional elements (such as one database, one in-memory cache) that are sufficient to amount to significantly more than the judicial exception because the limitations are adding the words “apply it” (or an equivalent) with the judicial exception, or mere instructions to implement an abstract idea on a computer, or merely uses a computer as a tool to perform an abstract idea - see MPEP 2106.05(f).
Claims 16, 17 are rejected under 35 U.S.C. 101 because the claimed invention is directed to judicial exception (i.e., a law of nature, a natural phenomenon, or an abstract idea) without significantly more. The claim(s) recite(s) creating links between geo-spatial areas and data table and mapping credit risk indicators to intersection between location. This judicial exception is not integrated into a practical application because the limitations are Adding the words “apply it” (or an equivalent) with the judicial exception, or mere instructions to implement an abstract idea on a computer, or merely uses a computer as a tool to perform an abstract idea - see MPEP 2106.05(f). The claim(s) does/do not include additional elements (such as geo-spatial areas, one security, one server) that are sufficient to amount to significantly more than the judicial exception because the limitations are adding the words “apply it” (or an equivalent) with the judicial exception, or mere instructions to implement an abstract idea on a computer, or merely uses a computer as a tool to perform an abstract idea - see MPEP 2106.05(f).
Therefore, Claims 1-17 are not drawn to eligible subject matter as they are directed to an abstract idea without significantly more.
Claim Rejections - 35 USC § 103
The following is a quotation of 35 U.S.C. 103 which forms the basis for all obviousness rejections set forth in this Office action:
A patent for a claimed invention may not be obtained, notwithstanding that the claimed invention is not identically disclosed as set forth in section 102, if the differences between the claimed invention and the prior art are such that the claimed invention as a whole would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to which the claimed invention pertains. Patentability shall not be negated by the manner in which the invention was made.
The factual inquiries set forth in Graham v. John Deere Co., 383 U.S. 1, 148 USPQ 459 (1966), that are applied for establishing a background for determining obviousness under 35 U.S.C. 103 are summarized as follows:
1. Determining the scope and contents of the prior art.
2. Ascertaining the differences between the prior art and the claims at issue.
3. Resolving the level of ordinary skill in the pertinent art.
4. Considering objective evidence present in the application indicating obviousness or nonobviousness.
Claims 1, 4-7, 9, 11-16 are rejected under 35 U.S.C. 103 as being unpatentable over Heath, (US 2013/0073387 A1) in view of Diriye et al., (US 2020/0118131 A1) in further view of Coogan-Pushner, (US 2018/0158158 A1) in further view of Kamalski (US 2009/0165120 A1).
Regarding claim 1, Heath discloses: A system for geographical mapping and linking of disparate data structures for interaction, the system comprising: at least one server in communication with one or more data source systems, the at least one server configured to: obtain data generated from among the one or more data source systems, the data comprising geo-spatial data, comprising a plurality of geo-spatial areas having disparate formats, security data, and additional data (Heath, see at least par. [0188] “. . . In a constructed embodiment, the information obtained comprises a postal zip code associated with the user, and a State where the user resides. Personal information such as the users and members name, e-mail address, residence address, social security number, telephone number, and the like is not obtained in step 107 . . .”) Interpretation: obtaining disparate set of data including geo-spatial data such as zip code, a state’s name (which has different format). Security data could be SSN and other data could be telephone number, etc., comprising one or more of economic data and demographic data (Heath, see at least par. [0015] “. . . a method for collecting user data, and optionally creating a user profile. A part of an end users online or user profile is their Volunteered Geographic Information (VGI) such as a user's current geographical location. Social network members in different cities, countries, or continents engage in different activities due to accessibility, economy . . .” & [0102] “ The present invention can in one embodiment gather basic demographic profile information including the user's current location and behavior data as they purchase and/or view ad links, promotions, online coupons, mobile services, Products, Goods, or Services, entertainment shopping, penny auctions or online auctions, advertisements and affiliate advertising or services on Social Earth, which can be sent to advertisers or otherwise capitalized by the users of the invention. By gathering this valuable demographic information, the present invention provides the ability to target market to Social Shoppers based upon specific location, demographic profile and selected social layer . . .”) Interpretation: economic data and demographic data are associated to represent the geographic area.
create, in at least one storage structure, a set of data tables (par. [0195] set of data tables correspond to master category list stored in a database server;
identify a relationship between a location identifier and one or more geo-spatial areas of the plurality of geo-spatial areas outside of an area defined by the location identifier based on at least one statistical algorithm configured to determine a best fit (see at least par. [0258] “. . . reference locations within the framework can be specified by and/or translated to and/or from locations defined within a common coordinate system, so as to allow integration of disparate data and functionality with a geospatial browser . . .” & see at least par. [0260] “. . . GM and/or GIS mapping can be based upon and/or filtered by quantities, for example, locations of most and least of a feature. GM and/or GIS mapping can also find and establish relationships between places, features, conditions, and/or events and determine where certain criteria are met and/or not met. GM and/or GIS mapping can also present densities to view concentrations. A density map allows measurement of a number of features using a uniform area unit, such as acres and/or square miles, to clearly present the distribution . . .”) Interpretation: the geo-spatial areas are not bounded or limited to any specific area, but could be the integration of disparate geospatial data and area;;
and generate an interactive graphical user interface (GUI) configured for display on one or more of an interactive webpage, the interactive GUI comprising one or more user tools configured to query the set of data tables including any updated data entries and any added data entries (Heath, Claim 2 see at least “ . . . using internet and mobile websites that provide end user customized interactive displays . . . (h) electronically displaying on said client mobile device or computer system said second end user geospatial interactive display data sets provided in steps (f) or (g) . . .”) The cited portion discloses displaying via a user interface (website) interactive data such that a user could perform several interactions similar to querying data and not limiting to data manipulation.
query the first data table for the location identifier to identify the cross-references (Heath, see at least par. [0333] “. . . The request for ads or social/geo/promo link promotional data sets may also include a query (as entered or parsed), information based on the query (such as geo-location information, whether the query came from an affiliate and an identifier of such an affiliate), and/or information associated with, or based on, the search results. Such information may include, for example, identifiers related to the search results (e.g., document identifiers or "docIDs"), scores related to the search results (e.g., information retrieval ("IR") scores), snippets of text extracted from identified documents (e.g., web pages), full text of identified documents, feature vectors of identified documents, etc. Other information can be included in the request including information related to the content that is to be displayed contemporaneously with the sponsored content. In some implementations, IR scores can be computed from, for example, dot products of feature vectors corresponding to a query and a document, page rank scores, and/or combinations of IR scores and page rank scores, etc.”) Interpretation: the first data table, or database, is queried with cross references such as between identifiers for geolocation and identifiers of business affiliates;
create one or more links between the security, the one or more geo-spatial areas, and the indicator, based on the cross-reference (Heath, see at least Claim 2 “. . . (g) selecting and integrating, into said second end user geospatial interactive displays from step (f), a first social/geo/promo link category for a first position of a social/geo/promo link promotional, data set; and identifying one or more second social/geo/promo link categories using one or more correlation criteria, at least one second social/geo/promo link category having one or more correlation criteria associated with the first social/geo/promo link category . . .”);
Heath does not disclose the following; however, Diriye teaches:
create and store, in a second data table among the set of data tables (see at least par. [0045] “. . . The method and system for tracking transactions associated with contracts may be used to create prohibited lists of items/transactions database with risk levels and other contextual factors including a location, the transacting parties, types of transactions, commodities/assets associated with the transactions, credit scores or financial histories of the transaction parties, etc. Thus, the system may use a database to detect or predict patterns from collected transactions and compare them with prohibited requirements . . .”) Interpretation: prohibited list of transactions database corresponds to second data table among the set of data tables (or databases under BRI), for each of the one or more geo-spatial areas, an indicator based on the additional data (Diriye, see at least par. [0047] “A high-dimensional risk array may represent the transaction/contract and one or more variables and dimensions. Colors may be mapped to risk level or “level of infraction” (red, yellow, green, etc.), or goodness/favorableness level, and this mapping may be set by a user or a third party. A degree of risk involved in the transaction will be stored and may related to the transaction and other contextual factors such as a location, the transacting parties (i.e. if they have a track record of unethical or unfair transactions, etc.), types of transactions, commodities/assets associated with transactions, credit scores, or financial histories of the transaction parties, etc. . . “) a level of risk is mapped based on locational data;
identify a security within the security data, the security associated with the location identifier par. [0077] “. . . The asset requester node/peer 420 obtains parameters from the asset transfer request 411 specifying conditions for transferring an asset. From these parameters, the asset requestor node/peer 420 creates a blockchain transaction 415 and transfers the blockchain transaction 416 to one or more risk assessment nodes/peers 430. The risk assessment nodes/peers 430 identify a smart contract 425 from the blockchain transaction 416. In one embodiment, the smart contract is identified based on a smart contract identifier provided as part of the blockchain transaction 416. In another embodiment, the smart contract is identified from one or more parameters specified in the blockchain transaction 416, which may provide clues as to a context (which may include a location) . . .”) Interpretation: one security could corresponds to a transferred asset (digital trade item) and such transferred asset is associated with a location ;
form instrument-level data for the security including the indicator (par. [0104] & see at least par. [0112] “. . . a smart contract identifier, a predetermined risk level threshold, an approval or modification status for a transaction, and the like. The transaction data may be stored for each of the N transactions . . .”) the use of hash links is based on the concept of linking using cross-references and the risk indicators (or predetermined risk level threshold) could be linked to the transaction in network chain;
It would be obvious to one of ordinary skill in the art before the effective filing date to combine the features in creating geo-spatial table taught by Heath with the elements such as creating credit risk indicators disclosed by Diriye to help managing the transaction based on the geo-spatial risk level (abstract). Therefore, the combination is obvious.
Heath in view of Diriye does not disclose the following; however, Coogan-Pushner teaches:
store, in a third data table among the set of data tables, the instrument-level data for the security (Coogan-Pushner, see at least par. [0042] “At block 106, statistical and econometric analysis is performed on all or a subset of the data in the MSX database 104 to understand drivers of solvency and predictors of material financial events, such as tax increases, cuts to essential services, shortfalls in cash flow, and shortfalls in pension cash flow. The result of the analysis in block 106 includes one or more predictive models 108. In accordance with one or more embodiments, the predictive models 108 can provide insight as to the probability of material financial events (MFEs) in addition to the probability of default for certain municipal bonds . . .” Interpretation: securities correspond to municipal bonds & Fig. 2 & see at least par. [0045] “. . . Processing of the collected data can include coding, revaluation, calculating data values, and mapping data fields (e.g., 100 data fields) to each municipal record. As shown in block 204, in one or more embodiment data going back 10 years is collected. As shown in block 206, 10 years of data is kept for each of the municipalities in the MSX index (in this example 150). The 150 municipalities can include all 50 states in the United States, Puerto Rico, the largest 49 counties in the United States and the largest 49 cites/towns in the United States and Washington, D.C. The data for the 150 municipalities is stored in the MSX database as shown in block 208. In the embodiment shown in FIG. 2, the MSX database includes 150,000 data elements.”) Interpretation: Instrument level data such as individual municipal bond is stored in the MSX database in which the MSX database corresponds to third data table;
update the set of data tables in response to any changes in the data obtained from the one or more data source systems, by at least one of: updating one or more existing data entries stored among the set of data tables and adding one or more new data entries among the set of data tables (see at least par. [0050] “As shown in FIG. 4, bond market data 416, which is an example of financial data, are collected from sources outside of municipal reporting entities. In accordance with one or more embodiments, data is collected from external sources . . .” & par. [0052] “The result of the collection, codification, revaluation, mapping and calculations is a comprehensive longitudinal and cross sectional (panel dataset) MSX database 104 that is uniquely compiled, allowing one or more embodiments to perform statistical analysis on the financial strength of each municipality. In one or more embodiments, each municipality has over 1,000 data fields (e.g., 100 data fields for each year) in the MSX database 104. In one or more embodiments, an initial data set has 150 records (largest 150 municipalities) yielding a dataset dimension of 150 records×1,000 or 150,000 elements. The number of data fields increases each quarter, since some data are updated quarterly, and with each reporting year) Interpretation: the data is collected from outside sources and regularly updated in the database or data tables;
It would be obvious to one of ordinary skill in the art before the effective filing date to combine the features storing and updating instrument level data of a municipal bond in a data table or database as taught by Coogan-Pushner with the elements such as creating credit risk indicators disclosed by Heath in view of Diriye to help developing predictive models for municipal solvency based on material financial events (abstract). Therefore, the combination is obvious.
Heath in view of Diriyie in further view of Coogan-Pushner does not disclose the following; however, Kamalski teaches:
create, using a geo-spatial join process, a cross-reference between the location identifier and the one or more geo-spatial areas, the geo-spatial join process comprising: converting the geo-spatial data associated with the location identifier into first data having a tabular format (Kamalski, see par. [0034] “Following the decryption of an encrypted location identifier cLC by the decryption unit 5, the decrypted location identifier is forwarded to the output unit 11 in similar fashion to the case of a location identifier LC transmitted in unencrypted form. Using a tabular map 13 determined by the control data CD, a traffic message is in turn compiled and output visually or audibly in plain text. As an alternative or in addition to the output of plain text, the traffic message can be transferred to a navigation system in a data format provided for this purpose . . .”) the location identifier is converted to tabular format, converting the geo-spatial data associated with the one or more geo-spatial areas into second data having the tabular format (Kamalski, see par. [0004] “In such traffic information systems in which a location statement is provided in the form of a location identifier, converting the location identifier into an intelligible location statement requires a tabular map with location entries in the mobile terminal. Indexed according to the location identifier, the tabular map comprises important parameters for describing the location, including a location name in plain text, inter alia.”) The second format is the tabular entry in describing the location, and merging the first data and the second data via a tabular operation (see at least par. [0029] In this position, received location identifiers LC are forwarded directly to the output unit 11. Using the selection number LTN, the country code CC and possibly the service identifier SID, which are transmitted to the output unit 11 from the evaluation unit 8, the output unit 11 selects from the tabular maps 13 the one which is used to convert the location identifier LC into a clearly intelligible location descriptor. The control data CD also contain an event identifier which is converted into a traffic event in plain text on the basis of a prescribed event table (not shown here). This traffic event forms, together with the location statement, a traffic message which is output by the output unit 11 in the form of a voice message and/or as a visually displayed message. “) The cited portion discloses merging the location identifier with the location description for event table;
store, in a first data table among the set of data tables, the cross-reference indexed by the location identifier (see at least par. [0047] “. . . The associated access profile would need to store the same decryption parameters which were used to modify the tabular map. An unencrypted location identifier LC transmitted by the service provider as part of traffic information TI would then be processed, i.e. in this case encrypted instead of decrypted, by the decryption unit 5 using the provided decryption parameters and would be converted precisely such that the processed location identifier indicates the correct entry in the encrypted tabular map . . .”)
It would be obvious to one of ordinary skill in the art before the effective filing date to combine the features of converting data into a tabular data format as taught by Kamalski with the elements such as creating credit risk indicators disclosed by Heath in view of Diriye in further view of Coogan-Pushner to help encoding location data (abstract). Therefore, the combination is obvious.
Claim 4. Heath in view of Diriye in further view of Coogan-Pushner in further view of Kamalski discloses: The system of claim 1. Heath further teaches: wherein the geo-spatial data comprises one or more of demographic data, economic data, social data and healthcare data (Heath, see at least par. [0102] “. . . By gathering this valuable demographic information, the present invention provides the ability to target market to Social Shoppers based upon specific location, demographic profile and selected social layer. This data can also include GPS for mobile user . . .”).
Claim 5. Heath in view of Diriye in further view of Coogan-Pushner in further view of Kamalski discloses: The system of claim 1. Heath further teaches: wherein the additional data is associated with at least one of the one or more geo-spatial areas, the additional data comprising one or more of population data, income data, migration data, labor data, housing data, education data and healthcare data (heath, Claim 13 “. . . selecting a first educational related social/geo/promo link category for a first position of an educational related social/geo/promo link promotional data set . . .”) the additional data could be associated with educational data set.
Claim 6. Heath in view of Diriye in further view of Coogan-Pushner in further view of Kamalski discloses: The system of claim 1. However, Coogan-Pushner further teaches: wherein the one or more geo-spatial areas comprise one or more of at least one city, at least one subdivision, at least one county, at least one state, a multi-state area, a metropolitan statistical area, a micropolitan statistical area and a core base statistical area (Coogan-Pushner, see at least par. [0026] “The MSX indices can include a family of indices that track the solvency positions of the largest state and local governments.”) The cited portion discloses data related to states and local governments.
It would be obvious to one of ordinary skill in the art before the effective filing date to combine the features locality data as taught by Coogan-Pushner with the elements such as creating credit risk indicators disclosed by Heath in view of Diriye to help developing predictive models for municipal solvency based on material financial events. Therefore, the combination is obvious.
Claim 7. Heath in view of Diriye in further view of Coogan-Pushner in further view of Kamalski discloses: The system of claim 1, wherein the location identifier (see at least par. [0035] “. . . The social/geo/promo link categories can be associated with one or more category identifiers, and at least one of the one or more correlation criteria of a second social/geo/promo link category can be a measure of the correlation between a category identifier associated with the second social/geo/promo link category and a category identifier associated with the first social/geo/promo link category . . .”) comprises one or more zip codes (Heath, par. [0162]) the cited portion discloses data contains a zip code.
Claim 9. Heath in view of Diriye in further view of Coogan-Pushner in further view of Kamalski discloses: The system of claim 1. Heath further teaches: wherein the at least one server is configured to continually monitor the data among the one or more data source systems in at least one of real-time or near real-time and obtain the data responsive to the monitoring (Heath, see at least par. [0013] “. . . system to provide educational related and integrated social networking, real time geospatial mapping, geo-target location based technologies including GPS and GIS and multiple points of interest, receiving current location of user's electronic or mobile device and multiple points of interest . . .” & see at least par. [0271] “The GM and/or GIS server system 202 can also include a security feature, for example, an access control module 222 to establish, control, and monitor access by GM and/or GIS client computers 204 to certain data stored within and/or accessible via the DMD 206 . . .”) Interpretation: The system monitors access to data stored within the database and also receives data in real-time.
Claim 11. Heath in view of Diriye in further view of Coogan-Pushner in further view of Kamalski discloses: The system of claim 1. Diriye further teaches: wherein the at least one server is configured to store the geo-spatial data, the security data and the additional data in one or more data tables associated with the at least one storage structure (Diriye, par. [0029]) Interpretation: the cited portion discloses storing data in data tables or blocks in a distributed ledger.
It would be obvious to one of ordinary skill in the art before the effective filing date to combine the features of storing data in a storage structure such as blockchain block as taught by Diriye with the elements such as creating credit risk indicators disclosed by Heath in view of Diriye in further view of Coogan Pushner to help developing predictive models for municipal solvency based on material financial events. Therefore, the combination is obvious.
Claim 12. Heath in view of Diriye in further view of Coogan-Pushner in further view of Kamalski discloses: teaches: The system of claim 11. However, Diriye further teaches: wherein the at least one server is configured to one or more of filter, normalize and format, using a data integrator tool associated with the at least one server, at least a portion of the data among the geo-spatial data, the security data, and the additional data, prior to entry within the one or more data tables (Diriye, par. [0069]) The cited portion discloses converting data into an architected format, or normalized format.
It would be obvious to one of ordinary skill in the art before the effective filing date to combine the features of normalizing data format as taught by Diriye with the elements such as creating credit risk indicators disclosed by Heath in view of Diriye in further view of Coogan Pushner to help developing predictive models for municipal solvency based on material financial events. Therefore, the combination is obvious.
Claim 13. Heath in view of Diriye in further view of Coogan-Pushner in further view of Kamalski teaches: The system of claim 1. Diriye further teaches: wherein the at least one storage structure comprises one or more of at least one database and at least one in-memory cache (Diriye, par. [0105] the cited portion discloses structure comprises a database & see at least par. [0120] “. . . the system memory 806 can include computer system readable media in the form of volatile memory, such as random-access memory (RAM) 810 and/or cache memory 812.).
It would be obvious to one of ordinary skill in the art before the effective filing date to combine the features of storage structure as taught by Diriye with the elements such as creating credit risk indicators disclosed by Heath in view of Diriye in further view of Coogan Pushner to help developing predictive models for municipal solvency based on material financial events. Therefore, the combination is obvious.
Claim 14. Heath in view of Diriye in further view of Coogan-Pushner in further view of Kamalski teaches: The system of claim 1. Coogan-Pushner further teaches: wherein the identified at least one security comprises at least one municipal security (Derner, par. [0050] “. . . An analysis of the drivers of spreads provides an indication of what the market values as having the most relative influence of the credit riskiness of the municipal bonds . . .”) municipal bonds corresponds to municipal securities.
It would be obvious to one of ordinary skill in the art before the effective filing date to combine the features of a municipal bond in a data table or database as taught by Coogan-Pushner with the elements such as creating credit risk indicators disclosed by Heath in view of Diriye to help developing predictive models for municipal solvency based on material financial events. Therefore, the combination is obvious.
Claim 15. Heath in view of Diriye in further view of Coogan-Pushner in further view of Kamalski teaches: The system of claim 1. Coogan-Pushner further teaches: wherein the at least one server is configured to receive user input via the one or more user tools, the user input associated with at least one of querying the third data table and creating user-customized instrument-level data (Coogan-Pushner, par. [0100]) The cited portion discloses querying and creating instrument level data by using index creation method.
It would be obvious to one of ordinary skill in the art effective filing date to combine the features in creating instrumental-level data by querying data table by Coogan-Pushner with the invention disclosed by Heath in view of Diriye in further view of Coogan-Pushner in further view of Kamalski to help improving the geo-spatial table set with the use of credit risk indicators. Therefore, the combination is obvious.
Claim 16. Heath in view of Diriye in further view of Coogan-Pushner in further view of Kamalski teaches: The system of claim 1. However, Diriye further teaches: wherein: the one or more links comprise a first link and a second link, the first link being created between the security and at least one among the one or more geo-spatial areas based on the cross-reference in the first data table (par. [0104] & see at least par. [0112] “. . . a smart contract identifier, a predetermined risk level threshold, an approval or modification status for a transaction, and the like. The transaction data may be stored for each of the N transactions . . .”) the use of hash links is based on the concept of linking using cross-references and the risk indicators (or predetermined risk level threshold) could be linked to the transaction in network chain, and the second link being created between indicator in the second data table and the security based on the first link, to form the instrument-level data for the security (Diriye, par. [0105]) the cited portion discloses chaincode which corresponds to indexing, or linking, between datasets (or tables) in the database.
It would be obvious to one of ordinary skill in the art before the effective filing date to combine the use of hash-link to link cross-references as taught by Diriye with the elements such as creating credit risk indicators disclosed by Heath in view of Diriye in further view of Coogan Pushner in further view of Kamalski to help developing predictive models for municipal solvency based on material financial events. Therefore, the combination is obvious.
Claims 2, 3 are rejected under 35 U.S.C. 103 as being unpatentable over Heath, (US 2013/0073387 A1) in view of Diriye et al., (US 2020/0118131 A1) in further view of Coogan-Pushner, (US 2018/0158158 A1) in further view of Kamalski (US 2009/0165120 A1) in further view of Narasimhan et al. (US 2017/0300912 A1).
Claim 2. Heath in view of Diriye in further view of Coogan-Pushner teaches: The system of claim 1. However, Narasimhan teaches: wherein the at least one server is configured to disseminate at least one of the instrument-level data and the indicator to at least one dissemination entity (Narasimhan, see at least par. [0094] “In different embodiments, the risk determination may be conducted by the system provider by assessing the fraud and/or credit risk of the sending party, the receiving party (e.g., using the size of the receiving party, a category the receiving party belongs to, a tenure of the receiving party, a tenure of the receiving party on the public ledger, a tenure known to the system provider of the receiving party on the public ledger, any linked public ledger accounts of the receiving party that may be explicitly mentioned or implicitly derived, etc.) or intermediaries in the transaction . . .” &par. [0095]).
It would be obvious to one of ordinary skill in the art before the effective filing date to combine the use providing credit risk between entities as taught by Narasimhan with the elements such as creating credit risk indicators disclosed by Heath in view of Diriye in further view of Coogan Pushner in further view of Kamalski to help developing predictive models for municipal solvency based on material financial events. Therefore, the combination is obvious.
Claim 3. Heath in view of Diriye teaches: The system of claim 2. However, Narasimhan teaches: wherein the at least one dissemination entity comprises at least one of a client device, an external distribution system, a delivery platform and an external database (Narasimhan, par. [0101]) The cited portion discloses at least user devices and other devices in the network.
It would be obvious to one of ordinary skill in the art before the effective filing date to combine the use of a network of devices as taught by Narasimhan with the elements such as creating credit risk indicators disclosed by Heath in view of Diriye in further view of Coogan Pushner in further view of Kamalski to help developing predictive models for municipal solvency based on material financial events. Therefore, the combination is obvious.
Claim 8 is rejected under 35 U.S.C. 103 as being unpatentable over Heath, (US 2013/0073387 A1) in view of Diriye et al., (US 2020/0118131 A1) in further view of Coogan-Pushner, (US 2018/0158158 A1) in further view of Kamalski (US 2009/0165120 A1) in further view of Derner et al. (US 2019/0163349 A1).
Claim 8. Heath in view of Diriye in further view of Coogan-Pushner in further view of Kamalski teaches: The system of claim 1. However, Derner teaches: wherein the at least one predetermined criteria includes one or more of a coverage area and a population density (Derner, par. [0043] “. . . Non-political boundaries may be defined, such as based on physical features (e.g., rivers, valleys, mountain ranges, etc.), population densities, or other criteria. ) . . .”).
It would be obvious to one of ordinary skill in the art before the effective filing date to combine population density as taught by Derner with the elements such as creating credit risk indicators disclosed by Heath in view of Diriye in further view of Coogan Pushner in further view of Kamalski to help developing predictive models for municipal solvency based on material financial events. Therefore, the combination is obvious.
Claim 10 is rejected under 35 U.S.C. 103 as being unpatentable over Heath, (US 2013/0073387 A1) in view of Diriye et al., (US 2020/0118131 A1) in further view of Coogan-Pushner, (US 2018/0158158 A1) in further view of Kamalski (US 2009/0165120 A1) in further view of Ibrahim et al. (US 2021/0241115 A1).
Claim 10. Heath in view of Diriye in further view of Coogan-Pushner in further view of Kamalski teaches: The system of claim 1. However, Ibrahim teaches: wherein the at least one server is configured to determine at least one of a score and a ranking of the at least one credit risk indicator based on at least one predetermined attribute of the additional data (Ibrahim, par. [0023]) The cited portion discloses calculating credit risk based on local attributions or additional data.
It would be obvious to one of ordinary skill in the art before the effective filing date to combine credit risk ranking calculation as taught by Ibrahim with the elements such as creating credit risk indicators disclosed by Heath in view of Diriye in further view of Coogan Pushner in further view of Kamalski to help developing predictive models for municipal solvency based on material financial events. Therefore, the combination is obvious.
Allowable Subject Matter
Claim 17 does not have art applied to the currently. However, other rejections are still outstanding such as the rejection(s) under 35 U.S.C. 101; Double Patenting rejection, 35 U.S.C. 103, set forth in this Office action. The following is a statement of reasons for the indication of withdrawing art: The mapping of a location identifier based on a maximum intersection between a location identifier in accordance with a predetermined criteria . However, the claims still do not overcome 101, Double patenting, 103.
Conclusion
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/TOAN DUC BUI/ Examiner, Art Unit 3693
/ELIZABETH H ROSEN/ Primary Examiner, Art Unit 3693