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 .
Claims 1-20 are pending.
Amendments filed 01/15/2026 are entered.
Response to Arguments
Arguments presented in Remarks (01/15/2026) are fully considered however are not moot in light of the change of the scope of the claim, i.e. addition of the limitation of a first field is identified based the first field being within a threshold distance of a second field, which necessitates new searches/consideration. A new ground of rejection has been established below.
The Double Patenting Rejections are sustained and updated as Applicant has yet not taken necessary steps to remedy the issues.
Claim Rejections - 35 USC § 103
In the event the determination of the status of the application as subject to AIA 35 U.S.C. 102 and 103 (or as subject to pre-AIA 35 U.S.C. 102 and 103) is incorrect, any correction of the statutory basis (i.e., changing from AIA to pre-AIA ) for the rejection will not be considered a new ground of rejection if the prior art relied upon, and the rationale supporting the rejection, would be the same under either status.
The following is a quotation of 35 U.S.C. 103 which forms the basis for all obviousness rejections set forth in this Office action:
A patent for a claimed invention may not be obtained, notwithstanding that the claimed invention is not identically disclosed as set forth in section 102, if the differences between the claimed invention and the prior art are such that the claimed invention as a whole would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to which the claimed invention pertains. Patentability shall not be negated by the manner in which the invention was made.
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.
Claim(s) 1-8, 10-20 is/are rejected under 35 U.S.C. 103 as being unpatentable over Gordon et al. (US 2021/0073769) and in further view of Sror et al. (US 2021/0312485) in view of Chou et al. - WO (2015/081060) and in further view of D’Oria (US 2022/0012406).
As to claim 1:
Gordon discloses a method comprising:
obtaining, by a computing device, a document associated with a transaction; ( Abstract, ¶0054, ¶0059-0061, receiving at least one transaction record data frame 400 (i.e. electronic ‘document’), which has a plurality transaction fields and metadata field, per ¶0060 “the transactional data frame 400 may comprise a transaction key field 401 as provided by the PII extraction processor 214 along with one or more PII transaction fields PT1-PTN 402 and one or more metadata fields MD1-MDX 403. The PII transaction fields PT1-PTN 402 contain one or more pieces of PII information that have been extracted from transaction input data frames 300. The metadata fields MD1-MDX 403 contain all other data from the input data frames 300 that has not been identified as PII information such as, but not limited to, order type, order time, geolocation, etc. For example, one of the PII transaction fields PT1-PTN 402 may comprise an email address corresponding to the transaction. Other PII transaction fields PT1-PTN 403 may include PII information that includes, but is not limited to, patron name (provided verbally, digitally, or read from a credit card reader), patron address, patron phone number, patron loyalty or gift card number”)
identifying, based on an automated analysis of the document, a plurality of fields; (¶0054, transaction document includes transaction record 202 having data of item(s) purchased, payment info, consumer data etc. ¶0059-0061, once received, the system automatically configured to identify and extract a plurality of fields, each containing data associated with the purchase)
extracting and storing a plurality of details from the plurality of fields, (See ¶0059 - 0061, and 0064’s discussion of field analysis and extraction of parameters of transactions from transaction records, such as items type, group purchase, time, amount)
wherein a first field, of the plurality of fields, identifies one or more items purchased via the transaction; (¶0054, ‘items’ purchased, 0066, at least one field identifying what items purchased, for example alcohol, dessert etc.)
categorizing, based on the plurality of details, each item purchased via the transaction; (¶0066, perform analysis of transaction data to categorizing purchases using extracted details such as type of product purchases, group purchases, individual purchases, desert purchases, alcohol purchases, purchase time categorization etc.…)
generating, based on categorization of each item purchased via the transaction, an expenditure report indicative of the transaction; (See ¶0066, 0045, 0138, generating a report associated with the individual including data indicative of spending habits with details as discussed above, i.e. tastes, type of product purchases, food etc.…)
Gordon discloses the transaction record 400 in at least ¶0060 which comprises various fields identifying various information pertaining the transaction (patron name, order type/ID, location of establishment associated with the particular purchase the transaction frame 400 is associated ith etc.), however does not explicitly mention the document identifying the merchant associated with the document.
Sror, in a related field of transaction data aggregation, discloses obtaining transaction data from both transaction record of physical or electronic form (See ¶0030, “Financial transaction data may include one or more fields extracted from one or more digital and/or physical documents containing evidence of a transaction, for example, invoices, receipts), wherein the transactional data in the document identifies a merchant associated with the document (See at least ¶0030-0032, “Transaction documents used to generate financial transaction data may have several different formats and any one of the merchant identifiers for a merchant may be included in financial transaction data for a particular transaction.”)
It would have been obvious to one of ordinary skill in the art before the effective filing time of the invention that Gordon’s transactional record frame 400 to have a field identifying a merchant as with Sror’s transaction record. Given that any invoice/receipt is wide known to identify the merchant (for identification, record keeping, return/exchange), such inclusion is natural, if not necessary, rather than an inventive step. Moreover, in ¶0060, Gordon suggests the transaction fields already disclose location of establishment, the more evidence that the name of the establishment (or merchant’s) should also be included as a more vital piece of evidence. Thus, the inclusion of merchant identity is not just beneficial but necessary for record keeping and other activities such as dispute, return etc.
Neither Gordon nor Sror explicitly disclose: causing the expenditure report with categorization of items purchased to be displayed.
Nevertheless, it is within reach of one of ordinary skilled in the art to contemplate such a feature, as evidenced in reference Chou, in at least ¶0098, 0099, transactional data of a person is aggregated and analyzed to generate a report of spending/consumption habit and to be displayed at a display terminal.
It would have been obvious to one of ordinary skill in the art before the effective filing time of the invention that such analytical data concerning an individual’s spending habit as generated to be displayed to intended audience, as visual demonstration is one of primary way to cause a person to be aware of data, given that Gordon in ¶0125, 0126 disclosing at least a display for displaying various generated consumer data. Furthermore, displaying such information allows a user to review purchases for self-inform purposes ( Chou, ¶0099). As with service’s provider point of view, such feature allows an operator/management to increase awareness of consumer base for future operation such as advertisement for example.
Gordon in view of Sror/Chou is/are silent on the first field is identified based the first field being within a threshold distance of a second field.
D’Oria, in a related field extracting data from electronic/legacy documents, discloses a document analysis system/method where data fields are recognized and extracted. In particular, ¶0049-0053, 0034, wherein several document elements are detected and identified, for example an input field and text block field that identifies or describes the input field. This identification is based on determining a distance between the input field and the text block and whether said distance is within a threshold. For example, if a text block is within a threshold distance to the right of the input field, and the text block includes one or more keywords indicating a type of unit, the type of input field may be identified.
It would have been obvious to one of ordinary skill in the art before the effective filing time of the invention that the system of Gordon’s combination to identify various data fields using the similar distance-based technique of D’Oria. The system of D’Oria, per ¶0034, uses distance threshold, to determine whether adjacent fields are pertinent to each other or simply being independent set of data. Thus, this implementation advantageously prevents unrelated data to be mistakenly categorized together, improving integrity of the resulting report.
As to claims 10 and 18:
Gordon discloses a computing device comprising: one or more processors; and memory, and also one or more non-transitory computer-readable media comprising instructions that, when executed, configure a computing device to storing instructions that, when executed by the one or more processors, causes the computing device to:
obtain a document associated with a transaction; ( Abstract, ¶0054, transaction document obtained.… ¶0059-0061)
identify, based on an automated analysis of the document, a plurality of fields; (¶0054, transaction document includes transaction record 202 having data of item(s) purchased, payment info, consumer data etc.… ¶0059-0061, once received, the system automatically configured to identify and extract a plurality of fields, each containing data associated with the purchase)
extract and store a plurality of details from the plurality of fields, (See ¶0059 - 0061, and 0064’s discussion of field analysis and extraction of parameters of transactions from transaction records, such as items type, group purchase, time, amount)
wherein a first field identifies one or more items purchased via the transaction; (¶0066, at least one field identifying what items purchased, for example alcohol, dessert etc.)
categorize, based on the plurality of details, each item purchased via the transaction; (¶0066, perform analysis of transaction data to categorizing purchases using extracted details such as type of product purchases, group purchases, individual purchases, desert purchases, alcohol purchases, purchase time categorization etc.…)
generate, based on categorization of each item purchased via the transaction, an expenditure report indicative of the transaction; (See ¶0066, 0045, 0138, generating a report associated with the individual including data indicative of spending habits with details as discussed above, i.e. tastes, type of product purchases, food etc.…)
Gordon discloses the transaction record 400 in at least ¶0060 which comprises various fields identifying various information pertaining the transaction (patron name, order type/ID, location of establishment associated with the particular purchase the transaction frame 400 is associated ith etc.), however does not explicitly mention the document identifying the merchant associated with the document.
Sror, in a related field of transaction data aggregation, discloses obtaining transaction data from both transaction record of physical or electronic form (See ¶0030, “Financial transaction data may include one or more fields extracted from one or more digital and/or physical documents containing evidence of a transaction, for example, invoices, receipts), wherein the transactional data in the document identifies a merchant associated with the document (See at least ¶0030-0032, “Transaction documents used to generate financial transaction data may have several different formats and any one of the merchant identifiers for a merchant may be included in financial transaction data for a particular transaction.”)
It would have been obvious to one of ordinary skill in the art before the effective filing time of the invention that Gordon’s transactional record frame 400 to have a field identifying a merchant as with Sror’s transaction record. Given that any invoice/receipt is wide known to identify the merchant (for identification, record keeping, return/exchange), such inclusion is natural, if not necessary, rather than an inventive step. Moreover, in ¶0060, Gordon suggests the transaction fields already disclose location of establishment, the more evidence that the name of the establishment (or merchant’s) should also be included as a more vital piece of evidence. Thus, the inclusion of merchant identity is not just beneficial but necessary for record keeping and other activities such as dispute, return etc.
Neither Gordon nor Sror explicitly disclose: causing the expenditure report with categorization of items purchased to be displayed.
Nevertheless, it is within reach of one of ordinary skilled in the art to contemplate such a feature, as evidenced in reference Chou, in at least ¶0098, 0099, transactional data of a person is aggregated and analyzed to generate a report of spending/consumption habit and to be displayed at a display terminal.
It would have been obvious to one of ordinary skill in the art before the effective filing time of the invention that such analytical data concerning an individual’s spending habit as generated to be displayed to intended audience, as visual demonstration is one of primary way to cause a person to be aware of data, given that Gordon in ¶0125, 0126 disclosing at least a display for displaying various generated consumer data. Furthermore, displaying such information allows a user to review purchases for self-inform purposes ( Chou, ¶0099). As with service’s provider point of view, such feature allows an operator/management to increase awareness of consumer base for future operation such as advertisement for example.
Gordon in view of Sror/Chou is/are silent on the first field is identified based the first field being within a threshold distance of a second field.
D’Oria, in a related field extracting data from electronic/legacy documents, discloses a document analysis system/method where data fields are recognized and extracted. In particular, ¶0049-0053, 0034, wherein several document elements are detected and identified, for example an input field and text block field that identifies or describes the input field. This identification is based on determining a distance between the input field and the text block and whether said distance is within a threshold. For example, if a text block is within a threshold distance to the right of the input field, and the text block includes one or more keywords indicating a type of unit, the type of input field may be identified.
It would have been obvious to one of ordinary skill in the art before the effective filing time of the invention that the system of Gordon’s combination to identify various data fields using the similar distance-based technique of D’Oria. The system of D’Oria, per ¶0034, uses distance threshold, to determine whether adjacent fields are pertinent to each other or simply independent. Thus, this implementation advantageously prevents unrelated data to be mistakenly categorized together.
As to claims 3, 12:
Gordon in view of Chou, Sror, and D’Oria discloses all limitations of claims 1/10, wherein the document comprises at least one of: a receipt; a proof of purchase; or an invoice. (Gordon, ¶0054, the purchase record includes items ordered/purchase and associated payment information, information of the purchaser, i.e. invoice or proof of purchase)
As to claims 8:
Gordon in view of Chou, Sror, and D’Oria discloses all limitations of claim 1, wherein the categorization of each item purchased via the transaction comprises: identifying a product associated with each field of the plurality of fields; and determining, based on the product, a category for each field of the plurality of fields. (See Gordon, ¶0061, identifying a product, i.e. “item #1” on the menu, as an example. ¶0066, the system is configured to infer and categorize the particular purchase as whether it is vegetarian, Mexican, Indian, or alcohol purchase, or desert purchases)
As to claims 2, 11 and 19:
v discloses all limitations of claim 1/10/18, however is silent on the document is obtained by at least one of an image capture device, a scanner, being imported from an email account, or being imported from a text message.
Sror, in a related field of analysis of transaction/spending of a user, discloses a system/method to analyze purchase/transaction information of a user, in which the system obtains the data of a physical/electronic invoice/receipt in form of a digital scan, i.e. obtained by some sort of scanning device/imaging device or received from an email or message (See ¶0018).
It would have been obvious to one of ordinary skill in the art before the effective filing time of the invention that the system of Gordon/Chou would be implemented to include a plethora of different means to obtain the transactional data. Since merchants use various ways to document/record purchases, this implementation allows improved flexibility in means to obtain transactional data and thus minimizing risk of inability to import transaction record.
As to claims 5, 14:
Gordon in view of Chou, Sror, and D’Oria discloses all limitations of claim 1/10, further comprising: identifying a particular field type associated with the document, wherein the plurality of fields is identified based on information, associated with the field type, received from a database. (See ¶0059 of Gordon, the processor identifies and extract content of a particular field type based on a known unique transaction field identifier value, ¶0060, example of various but not limited to field types such as email address, order type etc.…Such unique identifier values are known the system, thus stored in the system’s storage, i.e. “database”, Sror also discloses in at least ¶0030 that invoice, receipts, proof of purchase includes field indicative of merchant and is to be extracted by the automated system.)
As to claims 6, 15:
Gordon in view of Chou, Sror, and D’Oria discloses all limitations of claims 5, 14, Sror further discloses: determining, using a radiodetermination mechanism, a location of a user device, wherein the merchant is identified based on the location of the user device. (See ¶0064,0073, 0074, using cellular network and/or GPS (i.e. radiodetermination means), the system is aware of the user location and based on which to determine an appropriate POS (merchant) associated with the user location. Such implementation advantageously allows for immediate knowledge of merchant venues associated with the user even before a purchase is made, thus providing opportunities for targeted advertisement for example, per ¶0099 of Sror.
As to claims 7, 16:
Gordon in view of Chou, Sror, and D’Oria discloses all limitations of claims 1/10, however is silent on the automated analysis of the document comprises at least one of natural language processing (NLP), object character recognition (OCR), or computer vision.
Sror, in a related field of analysis of transaction/spending of a user, discloses a system/method to analyze purchase/transaction information of a user, in which the system, using at least OCR or other extraction techniques, obtains the data of a physical/electronic invoice/receipt in form of a digital scan, i.e. obtained by some sort of scanning device/imaging device or received from an email or message (See ¶0018).
It would have been obvious to one of ordinary skill in the art before the effective filing time of the invention that the system of Gordon/Chou would be implemented to include a plethora of different means to obtain the transactional data. Since merchants use various ways to document/record purchases, this implementation allows improved flexibility in means to obtain transactional data and thus minimizing risk of inability to import transaction record.
As to claim 17:
Gordon in view of Chou, Sror, and D’Oria discloses all limitations of claim 11, wherein the instructions, when executed by the one or more processors, cause the computing device to categorize each of the one or more purchases by: identifying a product associated with each field of the plurality of fields; and determining, based on the product, a category for each field of the plurality of fields. (See Gordon, ¶0061, identifying a product, i.e. “item #1” on the menu, as an example. ¶0066, the system is configured to infer and categorize the particular purchase as whether it is vegetarian, Mexican, Indian, or alcohol purchase, or desert purchases)
As to claims 4, 13, 20:
Gordon in view of Chou, Sror, and D’Oria discloses all limitations of claim 1/10/18, wherein D’Oria also discloses identifying, based on identification of an anchor field and during the automated analysis of the document, the plurality of fields. (¶0053, one or more rectangular cell (for example in input field) is detected, detecting one or more other adjacent boxes/entry in contact with the cell and that is/are separated by a threshold distance in in parallel/perpendicular orientation, a table of fields are detected and thus identified and arranged accordingly, for instance “One or more entries in the table may be determined based on text included in the boxes, position of content included in the boxes, controls included in the boxes, or a combination thereof. For example, text in cells may be detected as labels or headers, ”)
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 Itemman, 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.
Claim 1-20 is/are rejected on the ground of nonstatutory double patenting as being unpatentable over the below-cited claims of U.S. Patent No. 12080088 and in view of reference of record Sror and also D’Oria
As to claim 1:
Claim 1 of the Patent discloses a method comprising:
obtaining, by a computing device, a document associated with a transaction; ( “based on an automated analysis of a document”, while the obtaining step is not explicitly disclosed, however it is implicitly disclosed. For a document to be analyzed, it must be obtained)
identifying, based on an automated analysis of the document, a plurality of fields; (Claim 1, “identifying, by a computing device and based on an automated analysis of a document, a plurality of fields”)
extracting and storing a plurality of details from the plurality of fields, (Claim 1, “extracting one or more purchases from the plurality of fields; categorizing each of the one or more purchases”)
wherein a first field, of the plurality of fields, identifies one or more items purchased via the transaction; (“a plurality of fields; extracting one or more purchases from the plurality of fields”, while worded differently, it is obvious to one of ordinary skill in the art that details pertaining a purchase naturally would at least indicate what the purchases are, first and foremost )
categorizing, based on the plurality of details, each item purchased via the transaction; (Claim 1, “categorizing each of the one or more purchases”, “the expenditure report comprises a category for each of the one or more purchases”.)
generating, based on categorization of each item purchased via the transaction, an expenditure report indicative of the transaction; causing the expenditure report to be displayed.
(Claim 1, ”generating, based on monitoring incoming and outgoing transactions associated with the account and based on the automated analysis of the document, an expenditure report indicative of a user's spending habits, wherein the expenditure report comprises a category for each of the one or more purchases; and causing the expenditure report to be displayed.”)
The Patent however does not explicitly mention the document identifying the merchant associated with the document.
Sror, in a related field of transaction data aggregation, discloses obtaining transaction data from both transaction record of physical or electronic form (See ¶0030, “Financial transaction data may include one or more fields extracted from one or more digital and/or physical documents containing evidence of a transaction, for example, invoices, receipts), wherein the transactional data in the document identifies a merchant associated with the document (See at least ¶0030-0032, “Transaction documents used to generate financial transaction data may have several different formats and any one of the merchant identifiers for a merchant may be included in financial transaction data for a particular transaction.”)
It would have been obvious to one of ordinary skill in the art before the effective filing time of the invention that the transaction record in the patent to have a field identifying a merchant as with Sror’s transaction record. Given that any invoice/receipt is wide known to identify the merchant (for identification, record keeping, return/exchange), such inclusion is natural, if not necessary, rather than an inventive step. Thus, the inclusion of merchant identity is not just beneficial but necessary for record keeping and other activities such as dispute, return etc.
Regarding the first field is identified based on the first field being within a threshold distance of a second field:
D’Oria, in a related field extracting data from electronic/legacy documents, discloses a document analysis system/method where data fields are recognized and extracted. In particular, ¶0049-0053, 0034, wherein several document elements are detected and identified, for example an input field and text block field that identifies or describes the input field. This identification is based on determining a distance between the input field and the text block and whether said distance is within a threshold. For example, if a text block is within a threshold distance to the right of the input field, and the text block includes one or more keywords indicating a type of unit, the type of input field may be identified.
It would have been obvious to one of ordinary skill in the art before the effective filing time of the invention that the system of Patent to identify various data fields using the similar distance-based technique of D’Oria. The system of D’Oria, per ¶0034, uses distance threshold, to determine whether adjacent fields are pertinent to each other or simply independent. Thus, this implementation advantageously prevents unrelated data to be mistakenly categorized together.
As to claims 10 and 18:
Patent’s claim 11 discloses a computing device comprising: one or more processors; and memory, and also one or more non-transitory computer-readable media comprising instructions that, when executed, configure a computing device to storing instructions that, when executed by the one or more processors, (Claim 11, “computing device comprising: one or more processors; and memory storing instructions that, when executed by the one or more processors,”) causes the computing device to:
obtain a document associated with a transaction; ( “based on an automated analysis of a document”, while the obtaining step is not explicitly disclosed, however it is implicitly disclosed. For a document to be analyzed, it must be obtained)
identify, based on an automated analysis of the document, a plurality of fields; (Claim 11, “identifying, by a computing device and based on an automated analysis of a document, a plurality of fields”)
extract and store a plurality of details from the plurality of fields, (Claim 1, “extracting one or more purchases from the plurality of fields; categorizing each of the one or more purchases”)
wherein a first field, of the plurality of fields, identifies one or more items purchased via the transaction; (“a plurality of fields; extracting one or more purchases from the plurality of fields”, while worded differently, it is obvious to one of ordinary skill in the art that details pertaining a purchase naturally would at least indicate what the purchases are, first and foremost )
categorize, based on the plurality of details, each item purchased via the transaction; (Claim 1, “categorizing each of the one or more purchases”, “the expenditure report comprises a category for each of the one or more purchases”.)
generate, based on categorization of each item purchased via the transaction, an expenditure report indicative of the transaction; causing the expenditure report to be displayed.
(Claim 1, ”generating, based on monitoring incoming and outgoing transactions associated with the account and based on the automated analysis of the document, an expenditure report indicative of a user's spending habits, wherein the expenditure report comprises a category for each of the one or more purchases; and causing the expenditure report to be displayed.”)
The Patent however does not explicitly mention the document identifying the merchant associated with the document.
Sror, in a related field of transaction data aggregation, discloses obtaining transaction data from both transaction record of physical or electronic form (See ¶0030, “Financial transaction data may include one or more fields extracted from one or more digital and/or physical documents containing evidence of a transaction, for example, invoices, receipts), wherein the transactional data in the document identifies a merchant associated with the document (See at least ¶0030-0032, “Transaction documents used to generate financial transaction data may have several different formats and any one of the merchant identifiers for a merchant may be included in financial transaction data for a particular transaction.”)
It would have been obvious to one of ordinary skill in the art before the effective filing time of the invention that the transaction record in the patent to have a field identifying a merchant as with Sror’s transaction record. Given that any invoice/receipt is wide known to identify the merchant (for identification, record keeping, return/exchange), such inclusion is natural, if not necessary, rather than an inventive step. Thus, the inclusion of merchant identity is not just beneficial but necessary for record keeping and other activities such as dispute, return etc.
Regarding the first field is identified based on the first field being within a threshold distance of a second field:
D’Oria, in a related field extracting data from electronic/legacy documents, discloses a document analysis system/method where data fields are recognized and extracted. In particular, ¶0049-0053, 0034, wherein several document elements are detected and identified, for example an input field and text block field that identifies or describes the input field. This identification is based on determining a distance between the input field and the text block and whether said distance is within a threshold. For example, if a text block is within a threshold distance to the right of the input field, and the text block includes one or more keywords indicating a type of unit, the type of input field may be identified.
It would have been obvious to one of ordinary skill in the art before the effective filing time of the invention that the system of Patent to identify various data fields using the similar distance-based technique of D’Oria. The system of D’Oria, per ¶0034, uses distance threshold, to determine whether adjacent fields are pertinent to each other or simply independent. Thus, this implementation advantageously prevents unrelated data to be mistakenly categorized together.
Claim 18 is directed to a CRM, which can be read as the memory recited in Patent’s claim 11 and configured to cause the processor to perform the similar steps and are addressed by the same reasoning.
As to claims 3, 12:
Re: wherein the document comprises at least one of: a receipt; a proof of purchase; or an invoice. (Patent’s claim 3 and 13, near verbatim of instant claim 3 and 12, respectively)
As to claims 8:
Re: wherein the categorization of each item purchased via the transaction comprises: identifying a product associated with each field of the plurality of fields; and determining, based on the product, a category for each field of the plurality of fields.
(Patent’s claim 8, near verbatim of instant claim 8,)
As to claim 9:
Patent’s claim 10 and in turns claim 9 discloses: identifying, based on the automated analysis of the document, a first field based on the first field being within a threshold distance of an anchor field, wherein the first field comprises time-sensitive information; extracting and storing a plurality of details from the first field, wherein the plurality of details comprises an expiration date (Patent’s Claim 9, “identifying, based on the automated analysis of the document, a second field based on the second field being within a threshold distance of the anchor field, wherein the second field comprises time-sensitive information; extract and store a plurality of details from the second field, wherein the plurality of details comprises an expiration date”); and determining, using a radiodetermination mechanism, a location of the computing device; and sending, based on a determination that the location of the computing device is associated with a merchant and based on a determination that the expiration date has not passed, a reminder of an offer associated with the time-sensitive information (Claim 10, “determine, using a radiodetermination mechanism, a location of the computing device; and send, based on a determination that the location of the computing device is associated with a merchant and based on a determination that the time-sensitive information has not expired, a reminder of an offer associated with the time-sensitive information.”)
As to claims 2, 11 and 19:
Re: the document is obtained by at least one of an image capture device, a scanner, being imported from an email account, or being imported from a text message.
(Patent’s claim 2, near verbatim of instant claim 2, “the document is obtained by at least one of an image capture device, a scanner, being imported from an email account, or being imported from a text message”) . In Similar manner, Patent’s claim 12 discloses instant claims 11 and 19.
As to claims 5, 14:
Re: identifying a particular field type associated with the document, wherein the plurality of fields is identified based on information, associated with the field type, received from a database. (Patent’s claim 5, “identifying, based on the location of the user device, a merchant associated with the document, wherein the plurality of fields is identified based on information, associated with the merchant, received from a database”. Patent’s claim 15 also discloses similar limitation with respect to instant claim 14)
As to claims 6, 15:
Re: determining, using a radiodetermination mechanism, a location of a user device, wherein the merchant is identified based on the location of the user device.
(Patent’s claim 5, “determining, using a radiodetermination mechanism, a location of a user device; and identifying, based on the location of the user device, a merchant associated with the document”. Patent’s claim 15 also discloses similar limitation with respect to instant claim 14)
As to claims 7, 16:
Re: the automated analysis of the document comprises at least one of natural language processing (NLP), object character recognition (OCR), or computer vision.
(Patent’s claim 7, “the automated analysis of the document comprises at least one of: natural language processing (NLP); object character recognition (OCR); computer vision”. Patent’s claim 17 also discloses similar limitation with respect to instant claim 16)
As to claim 17:
RE: wherein the instructions, when executed by the one or more processors, cause the computing device to categorize each of the one or more purchases by: identifying a product associated with each field of the plurality of fields; and determining, based on the product, a category for each field of the plurality of fields. (Patent’s claim 18, near verbatim)
As to claims 4, 13, 20:
Re: identifying, based on a first field being within a threshold distance of an anchor field and during the automated analysis of the document, the plurality of fields. (See claim 4 of the Patent, near verbatim. Similarly, Patent’s claim 14 discloses instant claims 13 and 20)
Claim 1, 2, 4-7, 9-11, 13-20 is/are rejected on the ground of nonstatutory double patenting as being unpatentable over the below-cited claims of U.S. Patent No. 11887394 in view of reference Sror and also D’Oria
As to claim 1:
Patent claim 20 (which inherits all limitations of base claim 15 and 16) discloses a method comprising:
obtaining, by a computing device, a document associated with a transaction; ( Patent claim 15, “obtain a document”. Per Patent’s claim 16, the document is associated with a transaction)
identifying, based on an automated analysis of the document, a plurality of fields; (Patent’s claim 15, “identify, based on an automated analysis of the document, an anchor field, (…) a second field”)
extracting and storing a plurality of details from the plurality of fields, (Patent’s claim 15, “extract and store a plurality of details from the second field”)
wherein a first field, of the plurality of fields, identifies one or more items purchased via the transaction; (Patent’s claim 20, “extract one or more purchases from the plurality of fields”, while identification of items is not explicitly stated, however it is obvious to one of ordinary skill in the art that fields containing data indicative of purchases would at least indicate what the purchases are)
categorizing, based on the plurality of details, each item purchased via the transaction; (Patent’s claim 20, “categorize each of the one or more purchases”, the clause “based on the plurality of details” is impolite disclosed because categorization is done only if data regarding categories are known/obtained)
generating, based on categorization of each item purchased via the transaction, an expenditure report indicative of the transaction; causing the expenditure report to be displayed.
(See Patent’s claim 20, “generate an expenditure report indicative of a user's spending habits, wherein the expenditure report comprises a category for each of the one or more purchases; and cause the expenditure report to be presented on the computing device”)
The Patent however does not explicitly mention the document identifying the merchant associated with the document.
Sror, in a related field of transaction data aggregation, discloses obtaining transaction data from both transaction record of physical or electronic form (See ¶0030, “Financial transaction data may include one or more fields extracted from one or more digital and/or physical documents containing evidence of a transaction, for example, invoices, receipts), wherein the transactional data in the document identifies a merchant associated with the document (See at least ¶0030-0032, “Transaction documents used to generate financial transaction data may have several different formats and any one of the merchant identifiers for a merchant may be included in financial transaction data for a particular transaction.”)
It would have been obvious to one of ordinary skill in the art before the effective filing time of the invention that the transaction record in the patent to have a field identifying a merchant as with Sror’s transaction record. Given that any invoice/receipt is wide known to identify the merchant (for identification, record keeping, return/exchange), such inclusion is natural, if not necessary, rather than an inventive step. Thus, the inclusion of merchant identity is not just beneficial but necessary for record keeping and other activities such as dispute, return etc.
Regarding the first field is identified based on the first field being within a threshold distance of a second field:
D’Oria, in a related field extracting data from electronic/legacy documents, discloses a document analysis system/method where data fields are recognized and extracted. In particular, ¶0049-0053, 0034, wherein several document elements are detected and identified, for example an input field and text block field that identifies or describes the input field. This identification is based on determining a distance between the input field and the text block and whether said distance is within a threshold. For example, if a text block is within a threshold distance to the right of the input field, and the text block includes one or more keywords indicating a type of unit, the type of input field may be identified.
It would have been obvious to one of ordinary skill in the art before the effective filing time of the invention that the system of Patent to identify various data fields using the similar distance-based technique of D’Oria. The system of D’Oria, per ¶0034, uses distance threshold, to determine whether adjacent fields are pertinent to each other or simply independent. Thus, this implementation advantageously prevents unrelated data to be mistakenly categorized together.
As to claims 10 and 18, which is directed to a computing device comprising: one or more processors; and memory, and also one or more non-transitory computer-readable media comprising instructions that, when executed, configure a computing device to storing instructions that, when executed by the one or more processors, causes the computing device to perform the process similar to the instant claim 1, and thus are addressed by similar reasoning over Patent’s claim 20.
As to claim 9:
Patent in view of Sror and D’Oria discloses identifying, based on the automated analysis of the document, a first field based on the first field being within a threshold distance of an anchor field, wherein the first field comprises time-sensitive information; extracting and storing a plurality of details from the first field, wherein the plurality of details comprises an expiration date (Claim 15 (inherited by claim 20), “identify, based on the automated analysis of the document, a second field based on the second field being within a threshold distance of the anchor field, wherein the second field comprises time-sensitive information; extract and store a plurality of details from the second field, wherein the plurality of details comprises an expiration date associated with the time-sensitive information”); and determining, using a radiodetermination mechanism, a location of the computing device; and sending, based on a determination that the location of the computing device is associated with a merchant and based on a determination that the expiration date has not passed, a reminder of an offer associated with the time-sensitive information (Claim 15, “determine, using a radiodetermination mechanism, a location of the computing device; and send, based on a determination that the location of the computing device is associated with a merchant and based on a determination that the time-sensitive information has not expired, a reminder of an offer associated with the time-sensitive information.”)
As to claims 2, 11 and 19:
Patent’s claim 20 in view of Sror and D’Oria discloses all limitations of claim 1/10/18, however is silent on the document is obtained by at least one of an image capture device, a scanner, being imported from an email account, or being imported from a text message.
Sror, in a related field of analysis of transaction/spending of a user, discloses a system/method to analyze purchase/transaction information of a user, in which the system obtains the data of a physical/electronic invoice/receipt in form of a digital scan, i.e. obtained by some sort of scanning device/imaging device or received from an email or message (See ¶0018).
It would have been obvious to one of ordinary skill in the art before the effective filing time of the invention that the Patent would be implemented to include a plethora of different means to obtain the transactional data. Since merchants use various ways to document/record purchases, this implementation allows improved flexibility in means to obtain transactional data and thus minimizing risk of inability to import transaction record.
As to claims 5, 14:
Patent’s claim 20 in view of Sror and D’Oria discloses all limitations of claim 1/10, further comprising: identifying a particular field type associated with the document, wherein the plurality of fields is identified based on information, associated with the field type, received from a database. (Claim 15, implicitly disclosed in “identify, based on an automated analysis of the document, an anchor field; identify, based on the automated analysis of the document, a second field based on the second field being within a threshold distance of the anchor field”, which imply the system can recognize various types of field from its memory)
However, Patent do not explicitly indicate an example of such fields being for indicating merchant.
Reference Sror, again, discloses in at least ¶0030 that invoice, receipts, proof of purchase includes field indicative of merchant and is to be extracted by the automated system.
It would have been obvious to one of ordinary skill in the art before the effective filing time of the invention that invoice/proof of purchases described in Patent must include fields indicative of merchant. Merchant’s ID is an integral part of an invoice, because naturally such information is natural to a receipt/invoice to inform an audience the entity that sells the product and serve the useful purposes of exchange/return. Extraction of merchant identity allows full and complete collection of transaction data.
As to claims 6, 15:
Patent’s claim 20 in view of Sror and D’Oria discloses all limitations of claims 5, 14, Sror further discloses: determining, using a radiodetermination mechanism, a location of a user device, wherein the merchant is identified based on the location of the user device. (See ¶0064,0073, 0074, using cellular network and/or GPS (i.e. radiodetermination means), the system is aware of the user location and based on which to determine an appropriate POS (merchant) associated with the user location. Such implementation advantageously allows for immediate knowledge of merchant venues associated with the user even before a purchase is made, thus providing opportunities for targeted advertisement for example, per ¶0099 of Sror.
As to claims 7, 16:
Patent’s claim 20 in combination discloses all limitations of claims 1/10, however is silent on the automated analysis of the document comprises at least one of natural language processing (NLP), object character recognition (OCR), or computer vision.
Sror, in a related field of analysis of transaction/spending of a user, discloses a system/method to analyze purchase/transaction information of a user, in which the system, using at least OCR or other extraction techniques, obtains the data of a physical/electronic invoice/receipt in form of a digital scan, i.e. obtained by some sort of scanning device/imaging device or received from an email or message (See ¶0018).
It would have been obvious to one of ordinary skill in the art before the effective filing time of the invention that the Patent would be implemented to include a plethora of different means to obtain the transactional data. Since merchants use various ways to document/record purchases, this implementation allows improved flexibility in means to obtain transactional data and thus minimizing risk of inability to import transaction record.
As to claim 17:
Patent in view of Sror and D’Oria discloses all limitations of claim 11, wherein the instructions, when executed by the one or more processors, cause the computing device to categorize each of the one or more purchases by: identifying a product associated with each field of the plurality of fields; and determining, based on the product, a category for each field of the plurality of fields. (See Patent’s claim 20, “ extract one or more purchases from the plurality of fields; categorize each of the one or more purchases (…) expenditure report”, namely categorization can only be done after at least identification of the products purchased are performed)
As to claims 4, 13, 20:
Patent in view of Sror and D’Oria discloses all limitations of claim 1/10/18, where D’Orea discloses: identifying, based on a first field being within a threshold distance of an anchor field and during the automated analysis of the document, the plurality of fields (See ¶053, 0054)
Claims 3, 12, 8 is/are rejected on the ground of nonstatutory double patenting as being unpatentable over the below-cited claims of U.S. Patent No. 11887394 in view of Sror and D’Oria and further in view of Gordon (prior art of record)
As to claims 3, 12:
Patent in view of Sror and D’Oria discloses all limitations of claims 1/10, however is silent on wherein the document comprises at least one of: a receipt; a proof of purchase; or an invoice.
Gordon discloses the document comprises at least one of: a receipt; a proof of purchase; or an invoice (Gordon, ¶0054, the purchase record includes items ordered/purchase and associated payment information, information of the purchaser, i.e. invoice or proof of purchase)
It would have been obvious to one of ordinary skill in the art before the effective filing time of the invention that the document comprises at least one of: a receipt; a proof of purchase; or an invoice, given the context of Patent’s claim 20 includes documents from merchants with details pertaining purchases made.
As to claims 8:
Patent in view of Sror and D’Oria discloses all limitations of claims 1/10, however is silent the categorization of each item purchased via the transaction comprises: identifying a product associated with each field of the plurality of fields; and determining, based on the product, a category for each field of the plurality of fields.
Gordon discloses identifying a product associated with each field of the plurality of fields; and determining, based on the product, a category for each field of the plurality of fields (See Gordon, ¶0061, identifying a product, i.e. “item #1” on the menu, as an example. ¶0066, the system is configured to infer and categorize the particular purchase as whether it is vegetarian, Mexican, Indian, or alcohol purchase, or desert purchases)
It would have been obvious to one of ordinary skill in the art before the effective filing time of the invention that the Patent’s claim would be incorporated with the steps above, given that an expenditure report (patent’s claim 20) would naturally have various fields at least to indicate name of products and prices.
Allowable Subject Matter
Claim 9 is objected to as being dependent upon a rejected base claim, but would be allowable if rewritten in independent form including all of the limitations of the base claim and any intervening claims.
The references on record do not disclose: “ and determining, using a radiodetermination mechanism, a location of the computing device; and sending, based on a determination that the location of the computing device is associated with a merchant and based on a determination that the expiration date has not passed, a reminder of an offer associated with the time-sensitive information. ”
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure.
US 2019/0130453 - The system may be configured to perform operations including receiving, by a processor, internal transaction data from an internal customer profile associated with a customer; receiving, by the processor, external transaction data from an external customer profile associated with the customer; analyzing, by the processor and via a collaborative scoring algorithm, aggregate transaction data comprising the internal transaction data and external transaction data; determining, by the processor, a customer relevance value for an item based on the analyzing the aggregate transaction data; retrieving, by the processor, the item from an item databased based on the customer relevance value.
Applicant's amendment necessitated the new ground(s) of rejection presented in this Office action. Accordingly, THIS ACTION IS MADE FINAL. See MPEP § 706.07(a). Applicant is reminded of the extension of time policy as set forth in 37 CFR 1.136(a).
A shortened statutory period for reply to this final action is set to expire THREE MONTHS from the mailing date of this action. In the event a first reply is filed within TWO MONTHS of the mailing date of this final action and the advisory action is not mailed until after the end of the THREE-MONTH shortened statutory period, then the shortened statutory period will expire on the date the advisory action is mailed, and any nonprovisional extension fee (37 CFR 1.17(a)) pursuant to 37 CFR 1.136(a) will be calculated from the mailing date of the advisory action. In no event, however, will the statutory period for reply expire later than SIX MONTHS from the mailing date of this final action.
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/QUAN M HUA/Primary Examiner, Art Unit 2645