DETAILED ACTION
Notice of Pre-AIA or AIA Status
The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
Response to Amendment
2. The Amendment filed on 06/26/2026 has been entered. Claims 1, 3, 8 and 15 have been amended, claims 9, 13 and 20 have been cancelled and claim 23 is newly added. Claims 1 – 8, 10 – 12, 14 – 19 and 21 - 23 are currently pending.
Response to Arguments
35 U.S.C. §103
3. Applicant's arguments, see Remarks pp. 9 -13, filed 06/26/2026, with
respect to the rejections of claims 1-22 under 35 U.S.C. §103 have been fully
considered and they are persuasive.
Applicant argues that none of the cited references, alone or in combination, discloses or suggests a unified data enrichment service that provides each of these three components, namely, (i) the secure API endpoint, (ii) the database containing the entity-representing data structure, and (iii) the image database
Examiner respectfully agrees
Secondly, Applicant argues that IZENSON fails to disclose or suggest the API-based, credential- protected, data-enrichment-service architecture recited in amended claim 1, nor does IZENSON disclose or suggest combining transaction-event entries with the image lookup and enrichment features as recited in claim 1, as amended.
Examiner respectfully agrees
Thirdly, Applicant argues that IZENSON, AVETISOV, and CALL, fail to disclose or suggest obtaining a resource identifier identifying a location of an image as recited in claim 1, as amended
Examiner respectfully agrees
Fourthly, Applicant argues that the cited references fail to disclose or suggest the recited reusable, system-generated credentials.
Examiner respectfully agrees
Fifthly, Applicant argues that the Cited References Fail to Disclose the Recited Two-Stage Logo Presentation Based on Request Feature as amended
Examiner respectfully agrees
Upon further consideration new grounds of rejection have been necessitated due
to Applicant's amendments and are made in view of Manda et al., (United States Patent Publication Number 2024/0160953) hereinafter Manda
Claim Rejections – 35 U.S.C. §103
4. 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.
5. 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:
a. Determining the scope and contents of the prior art
b. Ascertaining the differences between the prior art and the claims at issue
c. Resolving the level of ordinary skill in the pertinent art
d. Considering objective evidence present in the application indicating
obviousness or nonobviousness
Claims 1 – 8, 10 - 12 and 14 - 19 are rejected under 35 U.S.C. 103 as being unpatentable over Izenson et al. (United States Patent Publication Number 20190236601 ), hereinafter Izenson, in view of Manda et al., (United States Patent Publication Number 2024/0160953) hereinafter Manda
Regarding claim 1 Izenson teaches a system for data enrichment, (Fig. 1A transaction processing system [0014]) see also merchant system [0031] the system , (Fig. 1A transaction processing system [0014]) see also merchant system [0031] comprising: one or more memories; (memory [0061], [0083]) and one or more processors, (processor [0061]) communicatively coupled to the one or more memories, (memory [0061], [0083]) configured to:
Izenson does not full provision, to a user device, a secure endpoint of an application programming interface (API), wherein the secure endpoint is configured to accept a set of structured data, the secure endpoint is provided by a data enrichment service associated with the system; receive, from the user device and at the secure endpoint, an API call that includes the set of structured data including a plurality of entries of a set of events related to transactions; determine, using a fuzzy search for the partial string, a corresponding data structure in a database that is associated with the data enrichment service, wherein the corresponding data structure represents an entity; generate; a standardized name for the entity based on the corresponding data structure; perform a lookup process on an image database associated with the data enrichment service, based on using the generated standardized name; obtain, based on performing the lookup using the generated standardized name, a resource identifier identifying a location of a corresponding image for the standardized name; and in response to a request to present the enriched set of structured data, cause a logo associated with the corresponding image to be presented in association with the standardized name and a structured data of the set of structured data.
Manda teaches provision, to a user device, (client devices [0107]) a secure endpoint (endpoint 370 which can include a URL generated for a particular instance [0068]) of an application programming interface (API), (API gateway [0038]) wherein the secure endpoint (endpoint 370 which can include a URL generated for a particular instance [0068]) is configured to accept a set of structured data, (structured data set 546 [0087] – [0089]) the secure endpoint (endpoint 370 which can include a URL generated for a particular instance [0068]) is provided by a data enrichment service (analytics environment 120 [0068]) associated with the system; (Figs. 7 and 8 computer system [0019] – [0020]) receive, from the user device (client devices [0107]) and at the secure endpoint, (endpoint 370 which can include a URL generated for a particular instance [0068]) an API call ( make requests to internal application programming interfaces (APis) for associated data stored in a database and delivered to a browser via HTTP requests as indicated by HTML code, and the like. [0043]) that includes the set of structured data(structured data [0087]) including a plurality of entries of a set of events related to transactions; (Extracted property information can be utilized in insurance claim settlement, risk adjustment, to facilitate transactions [0075])
determine, using a fuzzy search for the partial string, (The matching can be performed using a suitable technique. For instance, one example implementation used the SequenceMatcher function of the difflib library, which uses the Levenshtein distance technique to match two strings and provide a match score [0074]) such as “fuzzy search for the partial string” a corresponding data structure (Fig. 6D searchable data structure [0018]) in a database (in a database [0043]) that is associated with (associated with [0093]) the data enrichment service, (analytics environment 120 [0068]) wherein the corresponding data structure(Fig. 6D searchable data structure [0018]) represents an entity; (medication-related entity [0074]) generate; a standardized name (medication name [0073]) for the entity (medication-related entity [0074]) based on the corresponding data structure; (Fig. 6D searchable data structure [0018]) perform a lookup process (extracted medication entities are matched with medication names in a reference database, [0074]) such as “lookup process” on an image database (in a reference database, such as the RxNorm database available at nih.gov. [0074]) associated with (associated with [0093]) the data enrichment service, (analytics environment 120 [0068]) based on (based on [0096]) using the generated standardized name; (medication name [0073]) obtain, based on performing the lookup (The matching can be performed using a suitable technique. For instance, one example implementation used the SequenceMatcher function of the difflib library, which uses the Levenshtein distance technique to match two strings and provide a match score [0074]) such as “lookup process” using the generated standardized name, (medication name [0073]) a resource identifier identifying a location ( The component uses enriched features that encode row and column information (frow and fcol). The component generates bounding boxes according to the spatial location which can be fed to either a graph-based engine or a rule-based engine to obtain corresponding logical location. If using a rule-based approach, text output from OCR can be assigned (e.g., bound to, associated with) to the predicted cell boxes according to the spatial location. In some embodiments, can be used to identify or predict the location of the text elements and their corresponding bounding boxes for cells within a table. [0082]) of a corresponding image (the image [0082]) for the standardized name; (medication name [0073]) and in response to a request (client requests [0106]) to present the enriched set (enriched features [0082]) of structured data, (structured data [0087]) cause a logo (drug name [0072]) associated with (associated with [0093]) the corresponding image (the image [0082]) to be presented in association with(associated with [0093]) the standardized name (medication name [0073]) and a structured data (structured data [0087]) of the set of structured data. (structured data set 546)
It would have been prima facie obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have modified Izenson to incorporate the teachings of Manda whereby provision, to a user device, a secure endpoint of an application programming interface (API), wherein the secure endpoint is configured to accept a set of structured data, the secure endpoint is provided by a data enrichment service associated with the system; receive, from the user device and at the secure endpoint, an API call that includes the set of structured data including a plurality of entries of a set of events related to transactions; determine, using a fuzzy search for the partial string, a corresponding data structure in a database that is associated with the data enrichment service, wherein the corresponding data structure represents an entity; generate; a standardized name for the entity based on the corresponding data structure; perform a lookup process on an image database associated with the data enrichment service, based on using the generated standardized name; obtain, based on performing the lookup using the generated standardized name, a resource identifier identifying a location of a corresponding image for the standardized name; and in response to a request to present the enriched set of structured data, cause a logo associated with the corresponding image to be presented in association with the standardized name and a structured data of the set of structured data. By doing so AI models, can be used to generate natural-language responses to queries and to generate
insights based on the structured data. Manda [0087]
Claims 8 and 15 correspond to claim 1 and are rejected accordingly
Regarding claim 2 Izenson in view of Manda teaches the system of claim 1,
Izenson as modified further teaches wherein the partial string comprises a name (possible variations (e.g., "ABC's Cafe", "ABCs' Cafe", "ABCs Cafe") [0095]))or a numerical identifier (merchant identifier [0081])
Regarding claim 3 Izenson in view of in view of Manda teaches the system of claim 1,
Izenson as modified further teaches wherein each data structure (the raw data [0126]) includes at least the standardized name (Fig., 8, (806) normalize merchant name [0139]) and the location indicator (Fig., 8, (808) normalize merchant geographic location [0139])
Regarding claim 4 Izenson in view of Manda teaches the system of claim 1,
Izenson as modified further teaches wherein the one or more processors, (processor [0061]) to extract(retrieve [0101]) the partial string, (possible variations (e.g., "ABC's Cafe", "ABCs' Cafe", "ABCs Cafe") [0095])) are configured to: apply a machine learning model to parse (generated by the rule generation module 108c-5 and the processor 108b based on pre-existing rules and/or via machine learning. [0097]) see parsed Merchant name in Fig 3B the entries (transaction data [0062])
Regarding claim 5 Izenson view of Manda teaches the system of claim 1,
Izenson as modified further teaches wherein each corresponding image comprises a logo, a capital letter image, or a category image (one or more graphics [0034])
Regarding claim 6 Izenson in view of Manda teaches the system of claim 1,
Izenson as modified further teaches wherein the one or more processors (processor [0061]) are configured to: generate, (The rules may indicate how the raw merchant name may be modified or transformed to generate a normalized merchant name 372 [0102]) for at least one of the plurality entries, (entries for "Raw Merchant Name" 302, "Descriptor Merchant Name" 304, "Parsed Merchant Name" 306, "Normalized Merchant Name" 308, "Doing Business As (DBA)" 310, and "Merchant Corporate Name" 312. [0086]) a counterparty (Fig. 3B (362) ABCs Café and Lounge [0103]) based on the partial string, (possible variations (e.g., "ABC's Cafe", "ABCs' Cafe", "ABCs Cafe") [0095])) wherein the modified set of structured data (Fig. 8 (818) enriched transaction message [0147]) further includes a name (doing business as (DBA) ABCs Café and Lounge [0103]) associated with the counterparty. (Fig. 3B (362) ABCs Café and Lounge [0103])
Regarding claim 7 Izenson in view of Manda teaches the system of claim 6,
Izenson as modified further teaches wherein the one or more processors (processor [0061]) are configured to: determine, (determine [0103]) for the counterparty, (Fig. 3B (362) ABCs Café and Lounge [0103]) a corresponding image (one or more graphics, a token a bar code a QR code [0033]) using the name of the counterparty (doing business as (DBA) ABCs Café and Lounge [0103]) and the image database, (merchant attributes database [0035]) wherein the modified set of structured data (Fig. 8 (818) enriched transaction message [0147]) further includes the corresponding image(one or more graphics, a token a bar code a QR code [0033]) for the counterparty. (doing business as (DBA) ABCs Café and Lounge [0103])
Regarding claim 10 Izenson in view of Manda teaches the method of claim 8,
Izenson as modified further teaches wherein extracting(retrieve [0101]) the partial string (retrieve a string of characters of a merchant name [0101]) comprises: extracting (retrieve [0101]) a plurality of words (Fig. 3A parsed merchant name [0089]) from the corresponding description string; (merchant name [0101]) and generating a normalized plurality of words (normalized merchant names [0090]) from the plurality of words, (Fig. 3A parsed merchant name [0089]) wherein the partial string(retrieve a string of characters of a merchant name [0101]) is based on the normalized plurality of words (normalized merchant names [0090])
Regarding claim 11 Izenson in view of Manda teaches the method of claim 10,
Izenson as modified further teaches wherein extracting the partial string (retrieve a string of characters of a merchant name [0101]) further comprises: tokenizing the normalized plurality of words(normalized merchant names [0090]) to generate a plurality of word tokens, (the merchant identifier may also be a series of alphanumeric characters, one or more graphics, a token [0034]) wherein the partial string (retrieve a string of characters of a merchant name [0101]) is based on the plurality of word tokens (merchant identifier may be a token [0033])
Regarding claim 12 Izenson in view of Manda teaches the method of claim 8,
Izenson as modified further teaches further comprising: estimating whether at least one entry in the plurality of entries is recurring, (a pattern of fraud may be determined (e.g., large number of chargebacks, repetitive orders). [0052]) wherein the modified set of structured data (Fig. 8 (818) enriched transaction message sent to data analyzer computer [0147]) further includes an indication of whether the at least one entry is recurring. (a pattern of fraud may be determined (e.g., large number of chargebacks, repetitive orders). [0052])
Regarding claim 14 Izenson in view of Manda teaches the method of claim 8,
Izenson as modified further teaches further comprising: extracting, (retrieve [0101]) for each data structure, (the raw data [0126]) a corresponding uniform resource location (URL) (internet website [0091]) corresponding (corresponding [0169]) to the data structure, (the raw data [0126]) wherein the modified set of structured data (Fig. 8 (818) enriched transaction message sent to data analyzer computer [0147]) further includes, for each entry, (transaction data [0062]) the corresponding URL. (internet website [0091])
Regarding claim 16 Izenson in view of Manda teaches the non-transitory computer-readable medium of claim 15,
Izenson as modified further teaches wherein the one or more instructions that, (code [0062]) cause the device(computing device / payment device [0059]) to extract (retrieve [0101]) the one or more candidate strings, (retrieve a string of characters of a merchant name [0101]) are executed by the one or more processors (processor [0061]) to cause the device(computing device / payment device [0059]) to: apply one or more rules (based on a series of rules stored in the rules database [0093])to a corresponding description string (merchant name [0101])
Regarding claim 17 Izenson in view of Manda teaches the non-transitory computer-readable medium of claim 15,
Izenson as modified further teaches wherein the one or more instructions(code [0062]) that, cause the device(computing device / payment device [0059]) to determine the one or more candidate data structures, (include a plurality of matching results and a plurality of non-matching results. [0096]) are executed by the one or more processors (processor [0061]) to cause the device (computing device / payment device [0059]) to: apply a machine learning model(generated by the rule generation module 108c-5 and the processor 108b based on pre-existing rules and/or via machine learning. [0097]) see parsed Merchant name in Fig 3B to map the one or more candidate strings to the one or more candidate data structures. (include a plurality of matching results and a plurality of non-matching results. For example, "ABCD Cafe", "ABCz Cafe" and "ABC Books" may all be returned as a result of the search query for the text string: "ABC" [0096])
Regarding claim 18 Izenson in view of Manda teaches the non-transitory computer-readable medium of claim 15,
Izenson as modified further teaches wherein the one or more instructions(code [0062]) that, cause the device(computing device / payment device [0059]) to determine, for each entry, (transaction data [0062]) a corresponding category, (For example, the merchant identifier may be one or more of a merchant name, a merchant address, a merchant location, a merchant category code (MCC), [0034]) wherein the modified set of structured data(Fig. 8 (818) enriched transaction message sent to data analyzer computer [0147]) further includes, for each entry, (transaction data [0062]) the corresponding category (For example, the merchant identifier may be one or more of a merchant name, a merchant address, a merchant location, a merchant category code (MCC), [0034])
Regarding claim 19 Izenson in view of Manda teaches the non-transitory computer-readable medium of claim 15,
Izenson as modified further teaches wherein the one or more instructions(code [0062]) when executed, cause the device(computing device / payment device [0059]) to: authenticate the user device (the merchant computer 120 [0062]) based on a secret (authentication request/response messages [0062]) received with the set of structured data, wherein the modified set of structured data(Fig. 8 (818) enriched transaction message sent to data analyzer computer [0147]) is returned (include authentication request/response messages and transaction authorization request/response message. [0076]) based on authenticating the user device (the merchant computer 120 receives transaction data from a user computing device 102 and transmits the transaction data to the acquirer computer 106 for fraud transaction-related processes ( e.g., authentication, authorization). [0062])
Claims 21 - 23 are rejected under 35 U.S.C. 103 as being unpatentable over Izenson et al. (United States Patent Publication Number 20190236601 ), hereinafter Izenson, in view of Manda et al., (United States Patent Publication Number 2024/0160953) hereinafter Manda and in further view Kamal Jain (United States Patent Publication Number 20070179845) hereinafter Jain
Regarding claim 21 Izenson in view of Manda teaches the system of claim 1,
Izenson as modified does not fully disclose wherein the one or more processors are further configured to: receive feedback regarding at least one of the transmitted standardized name, the transmitted location indicator, or the transmitted corresponding image.
Jain teaches wherein the one or more processors (processor [0034]) are further configured to: receive feedback (Fig. 6, (604) receive feedback [0079]) regarding at least one of the transmitted standardized name, (advertiser [0079]) such as “standardized name” the transmitted location indicator, or the transmitted corresponding image.
It would have been prima facie obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have modified Izenson in view of Manda to incorporate the teachings of Jain wherein one or more processors are further configured to: receive feedback regarding at least one of the transmitted standardized name, the transmitted location indicator, or the transmitted corresponding image. By doing so feedback can, for example, verify that a transaction occurred as well as provide other information, such as the size and type of transaction, the consumer's level of satisfaction, etc. Jain [0079]
Regarding claim 22 Izenson in view of Manda and Jain teaches the system of claim 21,
Izenson as modified does not fully disclose wherein the feedback includes at least one of: a ranking, an indication of whether the standardized name, the location indicator, or the corresponding image is correct, and wherein the one or more processors are further configured to update the database based on the feedback.
Jain teaches wherein the feedback (Fig. 6, (604) receive feedback [0079]) includes at least one of: a ranking, (Fig. 6, (606) At 606, an advertiser ranking can be computed and/or updated based, e.g., upon the feedback received at 604. [0079]) an indication of whether the standardized name, the location indicator, or the corresponding image is correct, and wherein the one or more processors are further configured to update the database based on the feedback.
It would have been prima facie obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have modified Izenson in view of Manda to incorporate the teachings of Jain wherein the feedback includes at least one of: a ranking, an indication of whether the standardized name, the location indicator, or the corresponding image is correct, and wherein the one or more processors are further configured to update the database based on the feedback. By doing so enhancing the significance of the advertiser ranking. Jain [0086]
Regarding claim 23 Izenson in view of Manda and Jain teaches the system of claim 21,
Izenson as modified does not fully disclose wherein the one or more processors are configured to: extract, for the corresponding data structure, a uniform resource location (URL) corresponding to the data structure.
Manda teaches wherein the one or more processors are configured to: (wherein the one or more processors are configured to: extract, for the corresponding data structure, a uniform resource location (URL) corresponding to the data structure. [0034]) extract, (extract [0046]) for the corresponding data structure, (input data structure [0052]) a uniform resource location (URL) corresponding to the data structure (the extractive summarizer accelerator 368 via the endpoint 370, which can include a URL generated for a particular instance of the analytics environment 120. [0068])
It would have been prima facie obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have modified Izenson in view of Jain to incorporate the teachings of Manda wherein the one or more processors are configured to: extract, for the corresponding data structure, a uniform resource location (URL) corresponding to the data structure. By doing so it is structured to serve as the entry point for a web service component of the extractive summarizer accelerator 368 Manda [0068]
Conclusion
6. Applicant's amendment necessitated the new ground(s) of rejection presented in this Office action. Accordingly, THIS ACTION IS MADE FINAL. See MPEP § 706.07(a). Applicant is reminded of the extension of time policy as set forth in 37 CFR 1.136(a).
A shortened statutory period for reply to this final action is set to expire
THREE MONTHS from the mailing date of this action. In the event a first reply is
filed within TWO MONTHS of the mailing date of this final action and the advisory action
is not mailed until after the end of the THREE-MONTH shortened statutory
period, then the shortened statutory period will expire on the date the advisory
action is mailed, and any extension fee 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 date of this
final action.
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/KWEKU WILLIAM HALM/Examiner, Art Unit 2166
/SANJIV SHAH/Supervisory Patent Examiner, Art Unit 2166
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