This DETAILED ACTION
This is office action on the merits in response to the application filed on 10/10/2025.
Claims 1-17 have been filed by the applicant.
Claims 2, 9 and 15 were previously canceled.
Claims 1 and 8 are currently amended.
Claims 1, 3-8, 10-14 and 16-17 are currently pending and have been examined.
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 Argument
The applicant argues that the amendment of “a plurality of POS terminal receiving insertion of credit card and distributed across different geographical location” is not abstract idea and integrate the abstract idea to a practical application. The examiner respectfully disagrees. The amendment of receiving data by POS terminal is recited at high level of generality and amounts to mere data gathering, which is a form of adding insignificant extra-solution activity to the judicial exception (MPEP 2106.05(g)) as analyzed in 2A. As further analyzed in 2B, “a plurality of POS terminal receiving insertion of credit card and distributed across different geographical location” is well-known, routine and conventional function, as evidenced by Chau (US 20090119194 A1) in [0003 0016]. It is also agreed by the applicant in the Remark on page 16 that a conventional POS system is capable of accepting insertion of cards for payment.
The applicant further argues that the claims recites technological improvement because the claims improved the way data is processed. The examiner respectfully disagree. Although improvement is provided by the claims, the claims recite a data process directed to abstract idea. Therefore, the claims is reciting improvement of the abstract idea, instead of technological improvement.
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, 3-8, 10-14 and 16-17 are rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more.
In the instant case, claims 1, 3-7 and 16 are directed to a system comprising a memory and a processor, claims 8, 10-14 and 17 are directed to a method. Therefore, these claims fall within the four statutory categories of invention.
The limitations of independent claim 1, which is representative of independent claims 8, have been denoted with letters by the Examiner for easy reference. The judicial exceptions recited in claim 1 are identified in bold below:
A computer-implemented system for optimal identification of a merchant name and corresponding information from a transaction string using a multi-path merchant matching process, the system comprising:
a plurality of physical point of sale (POS) terminals, each of the plurality of POS receives an insertion of a credit card or a debit card for conducting a transaction, generates transaction information for the credit card or the debit card and transmits the transaction information to a payment network, wherein the plurality of POS terminals are distributed across different geographical locations, and wherein the transaction information includes merchant information in a free flow text form and without uniformity, such that the merchant information is provided in a differing text description by each of the plurality of POS terminals;
a database; and
a computer processor that is programmed to:
gather input information, comprising a plurality of transaction strings from the payment network, wherein the plurality of transaction strings includes the transaction information generated by each of the plurality of POS terminals, wherein each transaction string comprises a plurality of transaction attributes corresponding to a most probable merchant name (MPMN) and one or more of a merchant city, merchant state, merchant zip code, merchant street address, merchant phone number, merchant parent company, and a merchant category code (MCC);
identify and remove extraneous noise from each of the plurality of transaction strings to provide a plurality of modified transaction strings having smaller amount of data, wherein the extraneous noise includes transaction intermediaries;
parse each of the plurality of modified transaction strings to derive a transaction dataset comprising of a most probable merchant name, a most likely merchant zip code and one or more transaction attribute values for each of the plurality of modified transaction strings, wherein the most likely merchant zip code is derived based on a most frequent customer zip code used in transactions identified from the plurality of modified transaction strings;
extract, from the transaction dataset, unique merchant city and state attribute values for each modified transaction string having a city and state attributes and identify, from a truth set comprising third party provided merchant information records for a plurality of merchants, one or more merchant records corresponding to the state attribute values extracted from the modified transaction strings;
assign, based on a comparative string distance with the unique merchant city attribute values from each of the plurality of modified transaction strings, a match score to a merchant city attribute associated with each of the one or more merchant records;
process the transaction dataset to create a first data subset consisting of transaction strings with a valid city attribute, and a second data subset consisting of transactions strings without a valid city attribute, wherein a valid city attribute correspond to a match score, with at least one merchant city in the truth set, that is above a predefined threshold;
execute a first merchant matching process, using a logistic regression model, between transaction strings in the first data subset and a plurality of merchant records in the truth set, the first merchant matching process comprising assigning a set of individual attribute scores to each of one or more merchant records in the truth set that match transaction attributes in the plurality of modified transaction strings, wherein the attribute scores are based on a comparative string distance to corresponding transaction attributes in the plurality of modified transaction strings;
for each transaction string in the first data subset, compute an overall match score with respect to each of the one or more merchant records in the truth set and tag each transaction string with a merchant record corresponding to the highest overall match score, wherein the overall match score with respect to a merchant record is calculated as a function of the set of individual attribute score assigned to the merchant record;
execute a second merchant matching process, using a waterfall process, between transaction strings in the second data subset and the plurality of merchant records in the truth set, the second merchant matching process comprising identifying unique information items in the one or more transaction strings of the second data subset, and matching, based on string similarity metric and regular expression rules, the unique information items against the merchant records in the truth set, wherein the one or more unique information items comprises one of a most probable merchant name (MPMN) attributes from a list of selected merchant, a merchant phone number, a uniform resource locator, and a PayPal transaction identifier;
execute an override merchant matching process for transaction strings associated with a uniquely identifiable MCC attribute by overriding a corresponding best matched tag generated for the transaction string by either the first or the second merchant matching process and matching the transaction string with a merchant record from the truth set that corresponds to the uniquely identifiable MCC code;
consolidate results of the first, second and the override merchant matching process to create a master lookup table having transaction attributes from the transaction dataset mapped to matching merchant attributes from the truth set, wherein a hash identifier is generated for each record in the master lookup table;
create a hash identifier, based on transaction attributes, for each new transaction string received and tag the transaction string with corresponding merchant information associated with a matching hash identifier in the master lookup table, wherein transactions that are not matched in the master lookup table are parsed and tagged in accordance to the multi-path merchant matching process and added to the master lookup table;
aggregate and display in a singular report, on a display, tagged transaction strings according to a merchant description included in the master lookup table and not based on the merchant information provided by the plurality of POS terminals; and
create a merchant hierarchy, based on the tagged transaction strings, and displaying the merchant hierarchy for augmenting existing data stored in the database.
Limitations A-K and M-R under the broadest reasonable interpretation covers steps or functions of commercial interactions. Other than reciting generic computer hardware in limitations A-E and Q-R and “hash” in limitation P, nothing in the claim element differentiates the limitation from commercial interactions. For example, the disclosure establishes the context of identifying merchant in transaction data and correlating additional information for marketing. (Spec. 0008-0009). Therefore, limitations A through R recite an abstract idea, as highlighted above, that is consistent with the marketing activities aspects of a Certain Methods of Organizing Human Activity.
Furthermore, limitation K and L recites “logistic regression model,” and “computing score” which is mathematical calculations.
Accordingly, claim 1, and by analogy similar claims 8, recite at least two abstract ideas and the analysis proceed to Step 2A.2.
The judicial exception is not integrated into a practical application. In particular, claim 1 recites the additional elements in bold below:
A computer-implemented system for optimal identification of a merchant name and corresponding information from a transaction string using a multi-path merchant matching process, the system comprising:
a plurality of physical point of sale (POS) terminals, each of the plurality of POS receives an insertion of a credit card or a debit card for conducting a transaction, generates transaction information for the credit card or the debit card and transmits the transaction information to a payment network, wherein the plurality of POS terminals are distributed across different geographical locations, and wherein the transaction information includes merchant information in a free flow text form and without uniformity, such that the merchant information is provided in a differing text description by each of the plurality of POS terminals;
a database; and
a computer processor that is programmed to:
gather input information, comprising a plurality of transaction strings from the payment network, wherein the plurality of transaction strings includes the transaction information generated by each of the plurality of POS terminals, wherein each transaction string comprises a plurality of transaction attributes corresponding to a most probable merchant name (MPMN) and one or more of a merchant city, merchant state, merchant zip code, merchant street address, merchant phone number, merchant parent company, and a merchant category code (MCC);
identify and remove extraneous noise from each of the plurality of transaction strings to provide a plurality of modified transaction strings having smaller amount of data, wherein the extraneous noise includes transaction intermediaries;
parse each of the plurality of modified transaction strings to derive a transaction dataset comprising of a most probable merchant name, a most likely merchant zip code and one or more transaction attribute values for each of the plurality of modified transaction strings, wherein the most likely merchant zip code is derived based on a most frequent customer zip code used in transactions identified from the plurality of modified transaction strings;
extract, from the transaction dataset, unique merchant city and state attribute values for each modified transaction string having a city and state attributes and identify, from a truth set comprising third party provided merchant information records for a plurality of merchants, one or more merchant records corresponding to the state attribute values extracted from the modified transaction strings;
assign, based on a comparative string distance with the unique merchant city attribute values from each of the plurality of modified transaction strings, a match score to a merchant city attribute associated with each of the one or more merchant records;
process the transaction dataset to create a first data subset consisting of transaction strings with a valid city attribute, and a second data subset consisting of transactions strings without a valid city attribute, wherein a valid city attribute correspond to a match score, with at least one merchant city in the truth set, that is above a predefined threshold;
execute a first merchant matching process, using a logistic regression model, between transaction strings in the first data subset and a plurality of merchant records in the truth set, the first merchant matching process comprising assigning a set of individual attribute scores to each of one or more merchant records in the truth set that match transaction attributes in the plurality of modified transaction strings, wherein the attribute scores are based on a comparative string distance to corresponding transaction attributes in the plurality of modified transaction strings;
for each transaction string in the first data subset, compute an overall match score with respect to each of the one or more merchant records in the truth set and tag each transaction string with a merchant record corresponding to the highest overall match score, wherein the overall match score with respect to a merchant record is calculated as a function of the set of individual attribute score assigned to the merchant record;
execute a second merchant matching process, using a waterfall process, between transaction strings in the second data subset and the plurality of merchant records in the truth set, the second merchant matching process comprising identifying unique information items in the one or more transaction strings of the second data subset, and matching, based on string similarity metric and regular expression rules, the unique information items against the merchant records in the truth set, wherein the one or more unique information items comprises one of a most probable merchant name (MPMN) attributes from a list of selected merchant, a merchant phone number, a uniform resource locator, and a PayPal transaction identifier;
execute an override merchant matching process for transaction strings associated with a uniquely identifiable MCC attribute by overriding a corresponding best matched tag generated for the transaction string by either the first or the second merchant matching process and matching the transaction string with a merchant record from the truth set that corresponds to the uniquely identifiable MCC code;
consolidate results of the first, second and the override merchant matching process to create a master lookup table having transaction attributes from the transaction dataset mapped to matching merchant attributes from the truth set, wherein a hash identifier is generated for each record in the master lookup table;
create a hash identifier, based on transaction attributes, for each new transaction string received and tag the transaction string with corresponding merchant information associated with a matching hash identifier in the master lookup table, wherein transactions that are not matched in the master lookup table are parsed and tagged in accordance to the multi-path merchant matching process and added to the master lookup table;
aggregate and display in a singular report, on a display, tagged transaction strings according to a merchant description included in the master lookup table and not based on the merchant information provided by the plurality of POS terminals; and
create a merchant hierarchy, based on the tagged transaction strings, and displaying the merchant hierarchy for augmenting existing data stored in the database.
The additional element(s) in limitation A-E and Q-R merely serving as a tool to perform the abstract idea (MPEP § 2106.05(f)). The additional element of “hash” in limitation P generally link the use of the judicial exception to a particular technological environment (MPEP § 2106.05(h)). The additional element of “POS terminals receives insertion of cards for transaction; POS terminal distributed across different location” is recited at high level of generality and amounts to mere data gathering, which is a form of adding insignificant extra-solution activity to the judicial exception (MPEP 2106.05(g)). As such, when the additional elements are considered individually and as an ordered combination, the claim as a whole amounts to no more than or mere instructions to implement an abstract idea on a computer, or merely uses a computer as a tool to perform an abstract idea. Accordingly, the additional element(s) do not integrate the abstract idea into a practical application because they do not recite any additional elements indicative of integration into a practical application. Rather, the claim as whole generally links the judicial exception to a technological environment defined by high level recitations of a computer and the Internet. Therefore, the claim is directed to an abstract idea and the analysis proceeds to Step 2B.
The additional element of “a plurality of POS terminal receiving insertion of credit card and distributed across different geographical location” is well-known, routine and conventional function, as evidenced by Chau (US 20090119194 A1) in [0003 0016]. It is also agreed by the applicant in the Remark on page 16-17 that a conventional POS system is capable of accepting insertion of cards for payment. The additional elements, both individually and as an ordered combination, do not amount to significantly more than the judicial exception because the outcome of the considerations at Step 2B will be the same when the considerations from Step 2A.2 are reevaluated. As discussed under Step 2A.2, the additional element(s) amount to no more than generally link the abstract idea to a technological environment performed by a generic computer. This is not enough to provide an inventive concept. Therefore, claims 1 and 8 are not patent eligible.
Dependent claims 3 and 10 further recite determining whether a merchant name from transaction dataset exists in the master lookup table which further recite the abstract idea of commercial interactions. The additional element merely serves as a tool to perform the abstract idea. The additional elements fail to recite a practical application nor significantly more than the abstract idea.
Dependent claims 4 and 11 further recite examining whether there is matching phone number or URL which further recite the abstract idea of commercial interactions. The additional element merely serves as a tool to perform the abstract idea. The additional elements fail to recite a practical application nor significantly more than the abstract idea.
Dependent claims 5 and 12 further recite generating rank and probability which further recite the abstract idea of mathematical calculation. The additional element merely serves as a tool to perform the abstract idea. The additional elements fail to recite a practical application nor significantly more than the abstract idea.
Dependent claims 6 and 13 further recite using merchant category code to identifying merchant which further recite the abstract idea of commercial interactions. The additional element merely serves as a tool to perform the abstract idea. The additional elements fail to recite a practical application nor significantly more than the abstract idea.
Dependent claims 7 and 14 further recite generating a table of transaction attributes and search for attributes which further recite the abstract idea of commercial interactions. The additional element merely serves as a tool to perform the abstract idea. The additional elements fail to recite a practical application nor significantly more than the abstract idea.
Dependent claims 16 and 17 further defines a predefined match score threshold which further recite the abstract idea of commercial interactions. The claim does not recite additional elements that integrate the abstract idea to a practical application nor provide significantly more than the abstract idea.
In summary, the dependent claims considered both individually and as an ordered combination do not provide meaningful limitations to transform the abstract idea into a patent eligible application of the abstract idea such that the claims amount to significantly more than the abstract idea itself. The claims do not recite an improvement to another technology or technical field, an improvement to the functioning of the computer itself, or provide meaningful limitations beyond generally linking an abstract idea to a particular technological environment. Therefore, the claims are rejected under 35 U.S.C. § 101 as being directed to non-statutory subject matter.
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure.
US 9959574 B2: a clearing system comprising: a database for storing a plurality of accounts; and a risk manager for carrying out a risk assessment for a group of accounts comprising one or more accounts of said plurality of accounts; said risk manager being configured to update a risk assessment for a group of accounts each time the clearing system receives information about a new event affecting at least one account of said group of accounts. The event may be a new trade. The trade may be reported to the clearing system as soon as it has been settled.
US 20140330690 A1: a method of maintaining continuity of transaction data associated with a merchant within a payment card network includes identifying new merchant IDs and associated new merchant information from a database, the new merchant IDs and associated new transactions generated after a predetermined timestamp; and identifying discontinued merchant IDs and associated discontinued merchant information from the database, the discontinued merchant IDs associated only with older transactions generated before the predetermined timestamp and thus appearing to have been discontinued after the predetermined timestamp. The method further includes linking a new merchant ID to a discontinued merchant ID based on continued loyalty of payment card holders, the linked pair of new merchant and discontinued merchant ID having common payment card accounts associated therewith, thereby maintaining continuity of transaction data associated with the merchant corresponding to the linked pair of new and discontinued merchant IDs.
US 20140172507 A1: a method for predictive modeling of merchant attrition in a payment network. The method includes registering a plurality of merchants in the payment network, each merchant associated with at least one merchant acquirer; standardizing merchant registration information for the plurality of merchants to identify duplicate entries; assigning a unique merchant identification to each merchant; receiving transactional data from at least one merchant, the transactional data including at least a transaction amount and a transaction date; building a time series data set for the merchant from the transactional data; determining a merchant category for the merchant based on the primary industry group in which the merchant operates; and calculating a probability for the merchant to switch to a different acquirer based on one of a plurality of attrition models.
US 20110137928 A1: method for matching transaction records to merchant records of a merchant profile database is provided, the transaction records containing transaction data of financial presentation devices that are presentable to a plurality of merchants, the transaction data including merchant identifying data that identifies the merchant for the transaction. The system includes a memory storing a plurality of transaction records, a merchant profile database storing a plurality of merchant profile records, a processor, and a match logic module executable by the processor and adapted to recognize a plurality of variations in the merchant identifying data contained in the transaction records, the match logic module operable to match each of the transaction records to an associated merchant profile record in the merchant profile database according to the recognized variations in the merchant identifying data..
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.
Any inquiry concerning this communication or earlier communications from the examiner should be directed to ZESHENG XIAO whose telephone number is (571)272-6627. The examiner can normally be reached 10:00am-4:30pm M-F.
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/Z.X./Examiner, Art Unit 3698
/PATRICK MCATEE/Supervisory Patent Examiner, Art Unit 3698