DETAILED ACTION
Notice of Pre-AIA or AIA Status
The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
Introduction
The following is a final Office action in response to Applicant’s submission filed on 3/11/2026. Currently claims 1-20 are pending and claims 1, 6, 18 are independent. Claims 1, 6, 12, 18 have been amended from the previous claim set dated 10/6/2023. No claims have been added or cancelled. Priority to provisional application 63/378,638 (filed 10/6/2022) is acknowledged.
Response to Amendments
Applicant’s amendments are acknowledged and necessitated the new grounds of rejection in this Office Action. The 35 USC § 112(b) rejection of claim 12 is withdrawn in light of the amendments.
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 1-20 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), specifically an abstract idea, without significantly more. With respect to claims 1-20, following the guidance contained within MPEP 2106, the inquiry for patent eligibility follows two steps: Step 1: Does the claimed invention fall within one of the four statutory categories of invention? Step 2A (Prong 1): Is the claim “directed to” an abstract idea? Step 2A (Prong 2): Is the claim integrated into a practical application? Step 2B: Does the claim recite additional elements that amount to “significantly more” than the abstract idea?
In accordance with these steps, the Examiner finds the following:
Step 1: Claim 1 and its dependent claims (claims 2-5) are directed to a statutory category, namely a system/machine. Claim 6 and its dependent claims (claims 7-17) are directed to a statutory category, namely a method. Claim 18 and its dependent claims (claims 19, 20) are directed to a statutory category, namely an article of manufacture.
Step 2A (Prong 1): Claims 1, 6, and 18, which are substantially similar claims to one another, are directed to the abstract idea of “Certain methods of organizing human activity”, or more particularly, “Concepts relating to commercial or legal interactions (including: advertising, marketing or sales activities or behaviors; business relations) (See MPEP 2106).” In this application that refers to using a computer system to analyze a user’s spending transactions and classify/categorize them in order to apply themes to the spending to help the user understand their spending. To clarify this further, the Applicant’s disclosed invention is a conceptual system meant to perform the same function that an individual might do when reviewing their spending habits. The abstract elements of claims 1, 6, and 18, recite in part “Extract transaction data…Clean data…Enrich geo-data…Create geo-polygon…Scrape theme data…Verify geo-data…Map geodata…Determine whether polygons are same…label data…Generate report…”. Dependent claims 2-5, 7-17, 19, 20 add to the abstract idea the following limitations which recite in part “Store data…Retrieve data…Define information…Analyze information…Store information…Input criterion…Determine place…Search for place…Determine place existence…Perform permutation…Extract data…Store data…Retrieve data…Search for coordinates…Create theme database…Retrieve transaction place…Retrieve destination place…Compare places…Label transaction data…Store data…Determine overlay…Calculate haversine distance…Label data…Store data… ”. All of these additional limitations, however, only serve to further limit the abstract idea, and hence are nonetheless directed towards fundamentally the same abstract idea as independent claims 1, 6, and 18.
Step 2A (Prong 2): Independent claims 1, 6, and 18, which are substantially similar claims to one another, do not contain additional elements, either considered individually or in combination, that effectively integrate the exception into a practical application of the exception. These claims do include the limitation that recites in part “Processors…Memory…Database…Non-transitory computer readable medium…” which limits the claims to a networked/computer based environment, but this is insufficient with respect to integration into a practical application because it is merely applying the abstract idea to a general computer (See MPEP 2106.05(f)).
Additionally, dependent claims 2-5, 7-17, 19, 20 do not include any additional elements to conduct a further Step 2A (Prong 2) analysis.
Step 2B: Independent claims 1, 6, and 18, which are substantially similar claims to one another, include additional elements, when considered both individually and as an ordered combination, which are insufficient to amount to significantly more than the judicial exception. The additional elements of these claims recite in part “Processors…Memory…Database…Non-transitory computer readable medium …”. These items are not significantly more because these are merely the software and/or hardware components used to implement the abstract idea (analyze a user’s spending transactions and classify/categorize them in order to apply themes to the spending to help the user understand their spending) on a general purpose computer (See MPEP 2106.05(f)). This is exemplified in the Applicant’s specification in [0130] – “The host machine 4002 may be a computer or computing device, a personal computer (PC), a tablet PC, a set-top box (STB), a personal digital assistant (PDA), a cellular telephone...”
Additionally, dependent claims 2-5, 7-17, 19, 20 do not include any additional elements to conduct a further 2B analysis.
Accordingly, whether taken individually or as an ordered combination claims 1-20 are rejected under 35 USC § 101 because the claimed invention is directed to a judicial exception, 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 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 1-10, 18-20 are rejected under 35 U.S.C. 103 as being unpatentable over Reedy et al. (US 20210390573 A1) in view of Unser et al. (US 20150324823 A1) further in view of McNeel (US 9589259 B2)
Regarding claims 1, 6, and 18, Reedy discloses an event driven system for segmenting traveler thematic destination data (Reedy ABS - The device may determine travel-related data items in a set of transaction data, of the sets of transaction data, associated with a set of customers assigned to a particular cluster, and may use a second machine learning model to identify a travel experience that has a threshold likelihood of being of interest to the set of customers), the event driven system comprising: a processor; a memory coupled to the processor, wherein the memory stores machine instructions executable by the processor (Reedy Fig. 3); wherein when executed by the processor the machine instructions cause the processor to: extract clearance and settlement transaction data from a clearance and settlement database (Reedy ¶99 - As shown in FIG. 5, process 500 may include receiving, from one or more account entity devices, a plurality of sets of transaction data for transactions between a plurality of merchants and a plurality of customers (block 510). For example, the device (e.g., using computing resource 265, processor 320, communication interface 370, and/or the like) may receive, from one or more account entity devices, a plurality of sets of transaction data for transactions between a plurality of merchants and a plurality of customers); enrich and standardize the geo-data associated with the clearance and settlement transaction data (Reedy ¶40 - In some implementations, the recommendation platform may identify geographical locations of the set of customers based on the set of transaction data); verify the theme data is relevant for a geographic location corresponding to geo- data associated with of the theme data; enrich and standardize the geo-data associated with the theme data (Reedy ¶35 - In some implementations, the recommendation platform may utilize the model to identify a theme of the travel experience, where the theme is based on transaction data that includes descriptions of transactions with one or more of a plurality of merchants that are related to the theme. In some implementations, the recommendation platform may identify the travel experience based on the travel experience having at least a threshold likelihood of being of interest to the set of customers).
Reedy lacks clean geo-data associated with the clearance and settlement transaction data; scrape theme data associated with a plurality of predefined destination themes from an external data source on a public network, wherein the processor scrapes the theme data in compliance with the terms and conditions of the external data source; map the enriched and standardized geo-data associated with the clearance and settlement transaction data to the enriched and standardized geo-data associated with the theme data to create analysis data based on the clearance and settlement transaction data; and generate an analysis report based on the analysis data and an input criterion.
Unser, from the same field of endeavor, teaches clean geo-data associated with the clearance and settlement transaction data (Unser ¶50 - The main source of the data is cleaned, transformed, cataloged and made available for use by managers and other business professionals for data mining, online analytical processing, market research and decision support); scrape theme data associated with a plurality of predefined destination themes from an external data source on a public network, wherein the processor scrapes the theme data in compliance with the terms and conditions of the external data source (Unser ¶13- The present disclosure still further provides a method for generating one or more predictive travel pattern profiles. The method comprises…retrieving from one or more databases a second set of information comprising external information); map the enriched and standardized geo-data associated with the clearance and settlement transaction data to the enriched and standardized geo-data associated with the theme data (Unser Fig. 2 - Unser ¶44 - In another embodiment, data warehouse 200 aggregates the information by merchant and/or category and/or location. In still another embodiment, data warehouse 200 integrates data from one or more disparate sources. Data warehouse 200 stores current as well as historical data and is used for creating reports, performing analyses on the network, merchant analyses, and performing predictive analyses); label the clearance and settlement transaction data; create an analysis data based on the clearance and settlement transaction data and generate an analysis report based on the analysis data and an input criterion (Unser ¶47 - The integration layer integrates at 208 the disparate data sets by transforming the data from the staging layer often storing this transformed data in an operational data store database 210. For example, the payment card transaction information 202 can be aggregated by merchant and/or category and/or location at 208. Also, the reporting and data analysis, including the storing, reviewing, and/or analyzing of information, for the various purposes described above, can occur in data warehouse 200. The integrated data is then moved to yet another database, often called the data warehouse database or data mart 212, where the data is arranged into hierarchical groups often called dimensions and into facts and aggregate facts. The access layer helps users retrieve data).
It would be obvious for one of ordinary skill in the art before the effective filing date of the Applicant’s claimed invention to modify the transaction categorization methodology/system of Reedy by including the transaction analysis techniques of Unser because Unser discloses “The method and system provide advantages in fraud prevention, and can also be used by merchants or businesses to better target customers or enhance existing customer relationships (Unser ABS)”. Additionally, Reedy further details that “Many companies such as merchants, payment card issuers, and financial institutions regularly market products and/or services to attract new customers, increase sales to existing customers, and/or the like (Reedy ¶1)” so it would be obvious to consider including the additional transaction analysis techniques that Unser discloses because it would improve customer experience and enable the system of Reedy to increase sales to those customers.
Reedy further lacks enriching the geo-data comprises creating a geo-polygon associated the clearance and settlement transaction data; enriching the geo-data comprises creating a geo-polygon associated with the theme data; determine whether the geo-polygon associated with the clearance and settlement transaction data and the geo-polygon associated with the theme data correspond to a same place.
McNeel, from the same field on endeavor, teaches enriching the geo-data comprises creating a geo-polygon associated the clearance and settlement transaction data; enriching the geo-data comprises creating a geo-polygon associated with the theme data; determine whether the geo-polygon associated with the clearance and settlement transaction data and the geo-polygon associated with the theme data correspond to a same place (McNeel COL 5 ROW 32 - entering geographic coordinate data into a geographic information system; analyzing the geographic coordinate data by utilizing a feature overlay of coordinate-based data models or vector data in the form of a point, line or polygon that graphically shows the legal boundary of a tax area; and performing a spatial type relationship function on the geographic coordinate data to determine if the geographic coordinate data is within the tax area, wherein the spatial type relationship function includes multiple coordinate-based data models or multiple vector data overlays or layers).
It would be obvious for one of ordinary skill in the art before the effective filing date of the Applicant’s claimed invention to modify the transaction categorization methodology/system of Reedy by including the transaction location analysis techniques of McNeel because McNeel discloses “The invention further relates to geographic information systems, and more specifically, methods and systems for capturing geographic coordinates at the point of consummation of a transaction, and geospatially analyzing the geographic coordinate (McNeel COL 1 ROW 8)”. Additionally, Reedy further details that “In some implementations, the recommendation platform may identify geographical locations of the set of customers based on the set of transaction data, and may receive offers associated with traveling from the geographical locations of the set of customers to a geographical location associated with the travel experience (Reedy ¶40)” so it would be obvious to consider including the additional transaction location analysis techniques that McNeel discloses because it would improve the identification of customer location and enable the system of Reedy to better recommend location based offers.
Regarding claims 2, 7, Reedy in view of Unser further in view of McNeel discloses store the enriched and standardized geo-data associated with the clearance and settlement transaction data in a first database; and store the enriched and standardized geo-data associated with the theme data associated with the plurality of predefined destination themes in a second database (Reedy Fig. 1D).
Regarding claims 3, 8, Reedy in view of Unser further in view of McNeel discloses retrieve the enriched and standardized geo-data associated with the clearance and settlement transaction data from the first database; and retrieve the enriched and standardized geo-data associated with the theme data associated with the plurality of predefined destination themes from the second database (Reedy Fig. 1D).
Regarding claims 4, 9, and 19, Reedy in view of Unser further in view of McNeel discloses define trip information based on the enriched and standardized geo-data associated with the clearance and settlement transaction data, wherein the trip information comprises at least one of a trip, a trip theme of the plurality of predefined destination themes, or a traveler segment of a plurality of predefined traveler segments; analyze the trip information based on each of the plurality of predefined destination themes and traveler segments to generate the analysis data; and store the trip information and analysis data in a third database (Reedy ¶35 - In some implementations, the recommendation platform may utilize the model to identify a theme of the travel experience, where the theme is based on transaction data that includes descriptions of transactions with one or more of a plurality of merchants that are related to the theme. In some implementations, the recommendation platform may identify the travel experience based on the travel experience having at least a threshold likelihood of being of interest to the set of customers. The threshold likelihood may be based on a quantity of customers within the set of customers that are associated with a product that is associated with the travel experience, a service that is associated with the travel experience, an entity that is associated with the travel experience, and/or the like).
Regarding claims 5, 10, and 20, Reedy in view of Unser further in view of McNeel discloses
Unser further teaches the input criterion is a location or a first traveler segment of the plurality of predefined traveler segments (Unser ¶49 - The data mart 212 is a small data warehouse focused on a specific area of interest {i.e. input criterion}. For example, the data mart 212 can be focused on one or more of reporting and data analysis, including the storing, reviewing, and/or analyzing of information, for any of the various purposes described above {i.e. locations}. Data warehouses can be subdivided into data marts for improved performance and ease of use within that area).
It would be obvious for one of ordinary skill in the art before the effective filing date of the Applicant’s claimed invention to modify the transaction categorization methodology/system of Reedy by including the transaction analysis techniques of Unser because Unser discloses “The method and system provide advantages in fraud prevention, and can also be used by merchants or businesses to better target customers or enhance existing customer relationships (Unser ABS)”. Additionally, Reedy further details that “Many companies such as merchants, payment card issuers, and financial institutions regularly market products and/or services to attract new customers, increase sales to existing customers, and/or the like (Reedy ¶1)” so it would be obvious to consider including the additional transaction analysis techniques that Unser discloses because it would improve customer experience and enable the system of Reedy to increase sales to those customers.
Claims 11, 12, 15, 16, 17 are rejected under 35 U.S.C. 103 as being unpatentable over Reedy et al. (US 20210390573 A1) in view of Unser et al. (US 20150324823 A1) further in view of McNeel (US 9589259 B2) further in view of Dubey et al. (US 20230047717 A1)
Regarding claim 11, Reedy in view of Unser further in view of McNeel discloses an event driven system for segmenting traveler thematic destination data (Reedy ABS - The device may determine travel-related data items in a set of transaction data, of the sets of transaction data, associated with a set of customers assigned to a particular cluster, and may use a second machine learning model to identify a travel experience that has a threshold likelihood of being of interest to the set of customers).
Reedy in view of Unser further in view of McNeel lacks the cleaning, by the processor, of the geo- data associated with the clearance and settlement transaction data comprises determining, by the processor, a transaction place; searching, by the processor, for the transaction place on a public geographic database service; determining, by the processor, whether the transaction place exists in a transaction country; performing, by the processor, text permutations on the transaction place; performing, by the processor, text permutations on the transaction country; extracting, by the processor, standardized geo-data about the transaction place; and storing, by the processor, clean transaction geo-data in the first database.
Dubey, from the same field of endeavor teaches the cleaning, by the processor, of the geo- data associated with the clearance and settlement transaction data comprises determining, by the processor, a transaction place; searching, by the processor, for the transaction place on a public geographic database service; determining, by the processor, whether the transaction place exists in a transaction country; performing, by the processor, text permutations on the transaction place; performing, by the processor, text permutations on the transaction country; extracting, by the processor, standardized geo-data about the transaction place; and storing, by the processor, clean transaction geo-data in the first database (Dubey Fig. 6A - Dubey ¶95 - The processor 206 is configured to normalize address fields of non-matched payment transaction records 310 (i.e., unmatched transaction strings) based on address normalization (see, 312). The address normalization process may include normalizing or standardizing portions of data into a common form. For example, a data normalization process may be on merchant location data. For example, merchant location data may be conformed to match the standards recognized by a government agency (e.g., the U.S. Postal Service). In one embodiment, the address normalization may include multilingual tokenization, abbreviation expansion, address language classification, numeric expression parsing, transliteration, etc. In similar manner, the processor 206 is also configured to normalize address fields of clean merchant records stored in the clean merchant database).
It would be obvious for one of ordinary skill in the art before the effective filing date of the Applicant’s claimed invention to modify the transaction categorization methodology/system of Reedy by including the transaction cleaning techniques of Dubey because Dubey discloses “The present disclosure allows improved matching of transactions associated with a particular merchant (Dubey ¶38)”. Additionally, Reedy further details that “A device may receive, from account entity devices, sets of transaction data for transactions between merchants and customers (Reedy ABS)” so it would be obvious to consider including the additional transaction cleaning techniques that Dubey discloses because it would improve the matching of transactions to merchants within the system of Reedy.
Regarding claim 12, Reedy in view of Unser further in view of McNeel further in view of Dubey discloses an event driven system for segmenting traveler thematic destination data (Reedy ABS - The device may determine travel-related data items in a set of transaction data, of the sets of transaction data, associated with a set of customers assigned to a particular cluster, and may use a second machine learning model to identify a travel experience that has a threshold likelihood of being of interest to the set of customers).
Dubey further teaches retrieving, by the processor, Global Merchant Repository (GMR) location of the transaction place; and searching, by the processor, for coordinates of the transaction place on a public geographic database service (Dubey Fig. 6A - Dubey ¶95 - The processor 206 is configured to normalize address fields of non-matched payment transaction records 310 (i.e., unmatched transaction strings) based on address normalization (see, 312). The address normalization process may include normalizing or standardizing portions of data into a common form. For example, a data normalization process may be on merchant location data. For example, merchant location data may be conformed to match the standards recognized by a government agency (e.g., the U.S. Postal Service). In one embodiment, the address normalization may include multilingual tokenization, abbreviation expansion, address language classification, numeric expression parsing, transliteration, etc. In similar manner, the processor 206 is also configured to normalize address fields of clean merchant records stored in the clean merchant database).
It would be obvious for one of ordinary skill in the art before the effective filing date of the Applicant’s claimed invention to modify the transaction categorization methodology/system of Reedy by including the transaction cleaning techniques of Dubey because Dubey discloses “The present disclosure allows improved matching of transactions associated with a particular merchant (Dubey ¶38)”. Additionally, Reedy further details that “A device may receive, from account entity devices, sets of transaction data for transactions between merchants and customers (Reedy ABS)” so it would be obvious to consider including the additional transaction cleaning techniques that Dubey discloses because it would improve the matching of transactions to merchants within the system of Reedy.
Regarding claim 15, Reedy in view of Unser further in view of McNeel discloses an event driven system for segmenting traveler thematic destination data (Reedy ABS - The device may determine travel-related data items in a set of transaction data, of the sets of transaction data, associated with a set of customers assigned to a particular cluster, and may use a second machine learning model to identify a travel experience that has a threshold likelihood of being of interest to the set of customers).
Reedy in view of Unser further in view of McNeel lacks retrieving, by the processor, a normalized transaction place; retrieving, by the processor, a normalized destination place; and comparing, by the processor, geographic polygons associated with the normalized transaction place and the normalized destination place.
Dubey, from the same field of endeavor teaches retrieving, by the processor, a normalized transaction place; retrieving, by the processor, a normalized destination place; and comparing, by the processor, geographic polygons associated with the normalized transaction place and the normalized destination place (Dubey Fig. 6A - Dubey ¶95 - The processor 206 is configured to normalize address fields of non-matched payment transaction records 310 (i.e., unmatched transaction strings) based on address normalization (see, 312). The address normalization process may include normalizing or standardizing portions of data into a common form. For example, a data normalization process may be on merchant location data. For example, merchant location data may be conformed to match the standards recognized by a government agency (e.g., the U.S. Postal Service). In one embodiment, the address normalization may include multilingual tokenization, abbreviation expansion, address language classification, numeric expression parsing, transliteration, etc. In similar manner, the processor 206 is also configured to normalize address fields of clean merchant records stored in the clean merchant database).
It would be obvious for one of ordinary skill in the art before the effective filing date of the Applicant’s claimed invention to modify the transaction categorization methodology/system of Reedy by including the transaction cleaning techniques of Dubey because Dubey discloses “The present disclosure allows improved matching of transactions associated with a particular merchant (Dubey ¶38)”. Additionally, Reedy further details that “A device may receive, from account entity devices, sets of transaction data for transactions between merchants and customers (Reedy ABS)” so it would be obvious to consider including the additional transaction cleaning techniques that Dubey discloses because it would improve the matching of transactions to merchants within the system of Reedy.
Regarding claim 16, Reedy in view of Unser further in view of McNeel further in view of Dubey discloses an event driven system for segmenting traveler thematic destination data (Reedy ABS - The device may determine travel-related data items in a set of transaction data, of the sets of transaction data, associated with a set of customers assigned to a particular cluster, and may use a second machine learning model to identify a travel experience that has a threshold likelihood of being of interest to the set of customers).
Dubey further teaches determining, by the processor, whether the normalized transaction place and the normalized destination place share a country, wherein if the normalized transaction place and the normalized destination place share a country, the event driven method further comprising: labeling, by the processor, the clearance and settlement transaction data with a theme type; and storing, by the processor, clean transaction geo-data in the first database (Dubey Fig. 6A - Dubey ¶95 - The processor 206 is configured to normalize address fields of non-matched payment transaction records 310 (i.e., unmatched transaction strings) based on address normalization (see, 312). The address normalization process may include normalizing or standardizing portions of data into a common form. For example, a data normalization process may be on merchant location data. For example, merchant location data may be conformed to match the standards recognized by a government agency (e.g., the U.S. Postal Service). In one embodiment, the address normalization may include multilingual tokenization, abbreviation expansion, address language classification, numeric expression parsing, transliteration, etc. In similar manner, the processor 206 is also configured to normalize address fields of clean merchant records stored in the clean merchant database).
It would be obvious for one of ordinary skill in the art before the effective filing date of the Applicant’s claimed invention to modify the transaction categorization methodology/system of Reedy by including the transaction cleaning techniques of Dubey because Dubey discloses “The present disclosure allows improved matching of transactions associated with a particular merchant (Dubey ¶38)”. Additionally, Reedy further details that “A device may receive, from account entity devices, sets of transaction data for transactions between merchants and customers (Reedy ABS)” so it would be obvious to consider including the additional transaction cleaning techniques that Dubey discloses because it would improve the matching of transactions to merchants within the system of Reedy.
Regarding claim 17, Reedy in view of Unser further in view of McNeel further in view of Dubey discloses an event driven system for segmenting traveler thematic destination data (Reedy ABS - The device may determine travel-related data items in a set of transaction data, of the sets of transaction data, associated with a set of customers assigned to a particular cluster, and may use a second machine learning model to identify a travel experience that has a threshold likelihood of being of interest to the set of customers).
Dubey further teaches determining, by the processor, whether there is an overlay between the geographic polygons associated with the normalized transaction place and the normalized destination place; calculating, by the processor, a Haversine distance between coordinates of the normalized transaction place and the normalized destination place; and wherein if the Haversine distance between the normalized transaction place and the normalized destination place is within a predetermined range, the event driven method further comprising: labeling, by the processor, the clearance and settlement transaction data with a theme type; and storing, by the processor, clean transaction geo-data in the first database (Dubey Fig. 6A - Dubey ¶95 - The processor 206 is configured to normalize address fields of non-matched payment transaction records 310 (i.e., unmatched transaction strings) based on address normalization (see, 312). The address normalization process may include normalizing or standardizing portions of data into a common form. For example, a data normalization process may be on merchant location data. For example, merchant location data may be conformed to match the standards recognized by a government agency (e.g., the U.S. Postal Service). In one embodiment, the address normalization may include multilingual tokenization, abbreviation expansion, address language classification, numeric expression parsing, transliteration, etc. In similar manner, the processor 206 is also configured to normalize address fields of clean merchant records stored in the clean merchant database).
It would be obvious for one of ordinary skill in the art before the effective filing date of the Applicant’s claimed invention to modify the transaction categorization methodology/system of Reedy by including the transaction cleaning techniques of Dubey because Dubey discloses “The present disclosure allows improved matching of transactions associated with a particular merchant (Dubey ¶38)”. Additionally, Reedy further details that “A device may receive, from account entity devices, sets of transaction data for transactions between merchants and customers (Reedy ABS)” so it would be obvious to consider including the additional transaction cleaning techniques that Dubey discloses because it would improve the matching of transactions to merchants within the system of Reedy.
Claim 13 is rejected under 35 U.S.C. 103 as being unpatentable over Reedy et al. (US 20210390573 A1) in view of Unser et al. (US 20150324823 A1) further in view of McNeel (US 9589259 B2) further in view of Yee et al. (US 20210027394 A1)
Regarding claim 13, Reedy in view of Unser further in view of McNeel discloses an event driven system for segmenting traveler thematic destination data (Reedy ABS - The device may determine travel-related data items in a set of transaction data, of the sets of transaction data, associated with a set of customers assigned to a particular cluster, and may use a second machine learning model to identify a travel experience that has a threshold likelihood of being of interest to the set of customers).
Reedy in view of Unser further in view of McNeel lacks creating, by the processor, a theme database.
Yee, from the same field of endeavor teaches creating, by the processor, a theme database (Yee ¶40 - The crowdsourcing annotation system 110 may allow users to submit these annotations, aggregate user-generated annotations, and parse annotations by machine learning algorithms build a crowdsourcing annotation database 320. The crowdsourcing annotation system 110 may use machine learning algorithms to analyze the annotations provided by the users. The crowdsourcing annotation system 110 may use machine learning algorithms to extrapolate common themes among similar transactions by different users. Each common theme may be regarded as an annotation for the transaction. The crowdsourcing annotation system 110 may crowdsource appropriate annotations for each transaction or merchant. The crowdsourcing annotation system 110 may automatically generate annotations for new transactions to facilitate users' understanding of the new transactions).
It would be obvious for one of ordinary skill in the art before the effective filing date of the Applicant’s claimed invention to modify the transaction categorization methodology/system of Reedy by including the transaction annotation techniques of Yee because Yee discloses “Referring to FIG. 9, the user can rely on annotations or tags to easily sort through transactions (Yee ¶59)”. Additionally, Reedy further details that “A device may receive, from account entity devices, sets of transaction data for transactions between merchants and customers (Reedy ABS)” so it would be obvious to consider including the additional transaction annotation techniques that Yee discloses because it would make it easier for the user in Reedy to analyze their transactions.
Claim 14 is rejected under 35 U.S.C. 103 as being unpatentable over Reedy et al. (US 20210390573 A1) in view of Unser et al. (US 20150324823 A1) further in view of McNeel (US 9589259 B2) further in view of Yee et al. (US 20210027394 A1) further in view of Dubey et al. (US 20230047717 A1)
Regarding claim 14, Reedy in view of Unser further in view of McNeel further in view of Yee discloses an event driven system for segmenting traveler thematic destination data (Reedy ABS - The device may determine travel-related data items in a set of transaction data, of the sets of transaction data, associated with a set of customers assigned to a particular cluster, and may use a second machine learning model to identify a travel experience that has a threshold likelihood of being of interest to the set of customers).
Reedy in view of Unser further in view of McNeel further in view of Yee lacks searching, by the processor, unstructured data on the public network; determining, by the processor, whether a transaction place is touristic and to a theme; and searching, by the processor, on a public geographic database service.
Dubey, from the same field of endeavor teaches searching, by the processor, unstructured data on the public network; determining, by the processor, whether a transaction place is touristic and to a theme; and searching, by the processor, on a public geographic database service (Dubey Fig. 6A - Dubey ¶95 - The processor 206 is configured to normalize address fields of non-matched payment transaction records 310 (i.e., unmatched transaction strings) based on address normalization (see, 312). The address normalization process may include normalizing or standardizing portions of data into a common form. For example, a data normalization process may be on merchant location data. For example, merchant location data may be conformed to match the standards recognized by a government agency (e.g., the U.S. Postal Service). In one embodiment, the address normalization may include multilingual tokenization, abbreviation expansion, address language classification, numeric expression parsing, transliteration, etc. In similar manner, the processor 206 is also configured to normalize address fields of clean merchant records stored in the clean merchant database).
It would be obvious for one of ordinary skill in the art before the effective filing date of the Applicant’s claimed invention to modify the transaction categorization methodology/system of Reedy by including the transaction cleaning techniques of Dubey because Dubey discloses “The present disclosure allows improved matching of transactions associated with a particular merchant (Dubey ¶38)”. Additionally, Reedy further details that “A device may receive, from account entity devices, sets of transaction data for transactions between merchants and customers (Reedy ABS)” so it would be obvious to consider including the additional transaction cleaning techniques that Dubey discloses because it would improve the matching of transactions to merchants within the system of Reedy.
Response to Arguments
Applicant's arguments filed 3/11/2026 have been fully considered but they are not persuasive and/or are moot in light of the new rejections addressed above.
As addressed above, the 112(b) rejections are withdrawn in light of the amendments.
Regarding the arguments related to the 35 USC § 101 rejections, as addressed above according to the USPTO guidance contained within MPEP 2106 for 35 USC § 101 rejections, the Examiner maintains that the claimed invention is an abstract idea, without significantly more, and not integrated into a practical application.
Applicant first argues that the claimed invention is patent eligible because the claimed limitations (clean/enrich/standardize/scrape/verify/map/determine/label) are technical solutions and overcome the rejection within the Step 2A (Prong 1) analysis, however Examiner does not find this persuasive. Each claimed step is recited at a high level of generality to where it is not clear what the technical aspect actually is. Rather, Examiner interprets these limitations and business analysis steps and part of the commercial interaction abstract idea.
The Applicant also makes numerous arguments as to how the claimed invention is further integrated into a practical application by addressing the geo-analysis aspect of the claimed invention. While this geo-analysis aspect might be an improvement to the business process of analyzing transactions, and as such, have practical applicability, this practical applicability is not synonymous with USPTO guidance. Specifically, the claimed invention needs to have significant additional elements as to where the claimed invention is effectively integrated into those additional elements. As identified above, the additional elements (Processors…Memory…Database…Non-transitory computer readable medium…) limit the claims to a networked/computer based environment, but this is insufficient with respect to integration into a practical application because it is merely applying the abstract idea to a general computer (See MPEP 2106.05(f)).
Regarding the 35 USC § 101 Step 2B analysis, applicant argues that the identified elements are significantly more. This is unpersuasive because in both the original Office action and in the rejection above, the identified items are found to be not significantly more because they are mere instructions to apply an exception (See MPEP 2106.05(f)) and not because they are standard, routine, and conventional (See MPEP 2106.05(d)).
Regarding the 35 USC § 103 rejections on the previous Office Action, Applicant amended the independent claims to further limit the claims with respect to comparing geo-spatial polygons. In light of this amendment, Examiner agrees that the original references did not teach this, however the amendment necessitated further search and consideration. As a result of this further search and consideration, prior art was found that does teach these limitations (McNeel as discussed above). As such, Applicant’s arguments (with respect to the independent claims and their respective dependent claims) are unpersuasive.
Conclusion
THIS ACTION IS MADE FINAL. Applicant is reminded of the extension of time policy as set forth in 37 CFR 1.136(a).
A shortened statutory period for reply to this final action is set to expire THREE MONTHS from the mailing date of this action. In the event a first reply is filed within TWO MONTHS of the mailing date of this final action and the advisory action is not mailed until after the end of the THREE-MONTH shortened statutory period, then the shortened statutory period will expire on the date the advisory action is mailed, and any nonprovisional extension fee (37 CFR 1.17(a)) pursuant to 37 CFR 1.136(a) will be calculated from the mailing date of the advisory action. In no event, however, will the statutory period for reply expire later than SIX MONTHS from the mailing date of this final action.
Any inquiry concerning this communication or earlier communications from the examiner should be directed to Michael R Koester whose telephone number is (313)446-4837. The examiner can normally be reached Monday thru Friday 8:00AM-5:00 PM EST.
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If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Jerry O'Connor can be reached at (571) 272-6787. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
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/MICHAEL R KOESTER/Examiner, Art Unit 3624
/Jerry O'Connor/Supervisory Patent Examiner,Group Art Unit 3624
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