DETAILED ACTIONStatus of Claims
The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA . This action is in response to an amendment dated June 26, 2026. Claims, 1, 10 and 20 are amended. Claims 1-20 are pending. All pending claims are examined.
Response to Arguments
Art and 101 Rejection Analysis
Art Rejection
Borysek discloses a process of classification of transactions as recurring which involves a comparison of scores to a threshold (Borysek, para. 0014) and therefore Examiner maintains the prior art rejection.
101 Analysis
In line with the "2019 Revised Patent Subject Matter Eligibility Guidance," which explains how we must analyze patent-eligibility questions under the judicial exception to 35 U.S.C. § 101. 84 Fed. Reg. 50-57 ("Revised Guidance"), the first step of Alice (i.e., Office Step 2A) consists of two prongs. In Prong One, we must determine whether the claim recites a judicial exception, i.e., an abstract idea, a law of nature, or a natural phenomenon. 84 Fed. Reg. at 54 (Section III.A. I.). If it does not, the claim is patent eligible. Id.
An abstract idea must fall within one of the enumerated groupings of abstract ideas in the Revised Guidance or be a "tentative abstract idea, "with the latter situation predicted to be rare. Id. at 51-52 (Section I, enumerating three groupings of abstract ideas), 54 (Section III.A. I., describing Step 2A Prong One), 56-57 (Section III.D., explaining the identification of claims directed to a tentative abstract idea).
If a claim does recite a judicial exception, the next is Step 2A Prong Two, in which we must determine if the "claim as a whole integrates the recited judicial exception into a practical application of the exception." Id. at 54 (Section II.A.2.) If it does, the claim is patent eligible. Id.
If a claim recites a judicial exception but fails to integrate it into a practical application, we move to the second step of Alice (i.e., Office Step 2B). to evaluate the additional limitations of the claim, both individually and as an ordered combination, to determine whether they provide an inventive concept. Id. at 56 (Section III.B.). In particular, we look to whether the claim:
• Adds a specific limitation or combination of limitations that are not well-understood, routine, conventional in the field, which is indicative that an inventive concept may be present; or
• simply appends well-understood, routine, conventional activities previously known to the industry, specified at a high level of generality, to the judicial exception, which is indicative that an inventive concept may not be present.
The analysis in line with current 101 guidelines. Even if the abstract idea is deemed to be novel, the abstract idea is no less abstract (see Flook- new mathematical formula was an abstract idea).
“ In accordance with judicial precedent and in an effort to improve consistency and predictability, the 2019 Revised Patent Subject Matter Eligibility Guidance extracts and synthesizes key concepts identified by the courts as abstract ideas to explain that the abstract idea exception includes the following groupings of subject matter, when recited as such in a claim limitation(s) (that is, when recited on their own or per se):
(b) Certain methods of organizing human activity—fundamental economic principles or practices (including hedging, insurance, mitigating risk); commercial or legal interactions (including agreements in the form of contracts; legal obligations; advertising, marketing or sales activities or behaviors; business relations); managing personal behavior or relationships or interactions between people (including social activities, teaching, and following rules or instructions)1 – See Federal Register / Vol. 84, No. 4 / Monday, January 7, 2019 / p.52.
“20. A method comprising:
obtaining, by a computer device, data indicative of financial transactions associated with one or more customer accounts with a financial institution;
performing, by the computer device, at least one data transformation operation on descriptions of the financial transactions in the obtained data table identification of recurring transactions, including grouping the financial transactions based on a similarity of the descriptions;
combining, by the compute device, determinations from multiple analysis algorithms executed on a group of the financial transactions to obtain a confidence score indicative of whether the group of transactions represents a recurring transaction, wherein each of the multiple analysis algorithms independently produces a respective score for the group of the financial transactions, and the confidence score is obtained by summing the respective scores produced by each of the multiple analysis algorithms;
comparing, by the compute device, the confidence score to a threshold score to determine whether the group of financial transactions represents a recurring transaction;
presenting, by the compute device and in response to a determination that the confidence score indicates that the group of financial transactions represents a recurring transaction, a predicted amount and date for a recurrence of the recurring transaction.”
2A, Prong One, Taking the broadest reasonable interpretation, the invention is directed to comparing the cleaned and normalized transactions within each customer account to identify groups that likely represent recurring payments or deposits. The objective is to improve detection of transaction groups that qualify as recurring.
This is a method of organizing human activity that is commercial or legal interactions (including agreements in the form of contracts; legal obligations; advertising, marketing or sales activities or behaviors; business relations); because it entails evaluating transaction history and patterns data based on pre-defined rules and making predictions (App. Spec. para. 0010-0013).
Reviewing the raw data and making a determination based on predefined criteria as recited in the claims are nothing more than gathering data and applying a set of instructions to the data.
2A- Prong Two
Beyond the abstract idea, the additional elements recite hardware components such as a processor and user device (see App. Spec. paras. 0012-0016, 0020), there does not appear to be any technology being improved.
They are described at a high level of generality where each step does no more than require a generic computer to perform generic computer functions. Absent is any support in the specification that the claims as recited require specialized computer hardware or other inventive computer components.
Unlike, McRO, the present claims contain improvements to the context, including the nature of the transactions that are evaluated and not one of a technology or technological field.
Although the claims recite:
“combining, by the compute device, determinations from multiple analysis algorithms executed on a group of the financial transactions to obtain a confidence score indicative of whether the group of transactions represents a recurring transaction, wherein each of the multiple analysis algorithms independently produces a respective score for the group of the financial transactions, and the confidence score is obtained by summing the respective scores produced by each of the multiple analysis algorithms;
comparing, by the compute device, the confidence score to a threshold score to determine whether the group of financial transactions represents a recurring transaction;
As recited it suggests a process similar to a feedback loop in which feedback is used to update the data fed the algorithm that does the scoring. It suggests evaluating data albeit from “group of financial transactions” and the fact that it is an iterative process, that is commonplace for many business operations which are updated periodically as more data becomes available.
Absent is any support for the claims as recited for how it is an improvement to the computer or technical field beyond automating the evaluation and scoring process. In particular, there is a lack of improvement to a computer or technical field of accessing the transaction data because the data processing performed merely uses a system as a tool to perform an abstract idea- see MPEP 2106.05(f). Therefore, the claims are directed to an abstract idea. The invention as claimed recites a generic computer component and the claim does not pass step 2A, Prong Two.
Step 2B; The next step is to identify any additional limitations beyond the judicial exception. The additional elements are user device and processor (see App. Spec. paras. 0010, 0012-0020) which is disclosed in the specification at a high degree of generality. Absent is any genuine issue of material fact that this component requires any specialized hardware or inventive computer component.
Likewise, the dependent claims 2-19 provide additonal details about the process of determining recurring transactions based on a scoring process. For example, claims 2-4 which provide additional details about the factors used in the evaluation and do not address the issues raised in the independent claims and therefore do not amount to a technical improvement or an integration of a practical application.
In conclusion, merely “applying” the exception using generic computer components cannot provide an inventive concept. Independent claims 1 and 20 are rejected under 35 U.S.C. § 101 including dependent claims 2-19. Therefore, claims 1-20 are not patent eligible under 35 USC 101.
Claim Rejections - 35 USC § 101
35 U.S.C. 101 reads as follows:
Whoever invents or discovers any new and useful process, machine, manufacture, or composition of matter, or any new and useful improvement thereof, may obtain a patent therefor, subject to the conditions and requirements of this title.
Claims 1-20 are rejected under 35 U.S.C. 101 because the claimed invention is directed to a judicial exception (abstract idea) without significantly more.
The claim recites abstract idea of organizing human activities. This judicial exception is not integrated into a practical application and the claim(s) does/do not include additional elements that are sufficient to amount to significantly more than the judicial exception.
Analysis
The claims are directed to one or more of the following statutory categories: a process, a machine, a manufacture, and a composition of matter.
Independent Claim 20, which is illustrative of the independent claim 1 recites:
20. A method comprising:
obtaining, by a computer device, data indicative of financial transactions associated with one or more customer accounts with a financial institution;
performing, by the computer device, at least one data transformation operation on descriptions of the financial transactions in the obtained data table identification of recurring transactions, including grouping the financial transactions based on a similarity of the descriptions;
combining, by the compute device, determinations from multiple analysis algorithms executed on a group of the financial transactions to obtain a confidence score indicative of whether the group of transactions represents a recurring transaction, wherein each of the multiple analysis algorithms independently produces a respective score for the group of the financial transactions, and the confidence score is obtained by summing the respective scores produced by each of the multiple analysis algorithms;
comparing, by the compute device, the confidence score to a threshold score to determine whether the group of financial transactions represents a recurring transaction;
presenting, by the compute device and in response to a determination that the confidence score indicates that the group of financial transactions represents a recurring transaction, a predicted amount and date for a recurrence of the recurring transaction
Taking the broadest reasonable interpretation, the invention is directed to a method of organizing human activity that is commercial or legal interactions (including agreements in the form of contracts; legal obligations; advertising, marketing or sales activities or behaviors; business relations); of determining an account profile based on analysis of historical patterns or and activity (see claims obtaining, by a computer device, data indicative of financial transactions associated with one or more customer accounts with a financial institution;
performing, by the computer device, at least one data transformation operation on descriptions of the financial transactions in the obtained data table identification of recurring transactions, including grouping the financial transactions…)
The evaluation of data from a variety of data sources is based on if certain pre-defined conditions are satisfied.
Besides reciting the abstract idea, the remaining claim limitation is the compute device which is described in terms that suggest it comprises generic computer components (see App Spec. para. 0015-0018; see also Fig. 2).
Further, the dependent claims 2-19, recite additional details about the information used in the determination as to whether a transaction is recurring; For example, claims 2-4 describe the segmenting of the data and descriptive details about the data and functional feature of the data. However, the recited abstract idea is not integrated into a practical application. In particular, the invention as claimed recites a generic computer for obtaining, performing, combining and presenting steps of the invention as recited.
App Spec. para. 0015
includes a compute engine 210, an input/output (I/O) subsystem 216, communication circuitry 218, and one or more data storage devices 222. In some embodiments, the transaction prediction compute device 110 may include one or more display devices 224 and/or one or more peripheral devices 226 (e.g., a mouse, a physical keyboard, etc.). In some embodiments, one or more of the illustrative components may be incorporated in, or otherwise form a portion of, another component. The compute engine 210 may be embodied as any type of device or collection of devices capable of performing various compute functions described below. In some embodiments, the compute engine 210 may be embodied as a single device such as an integrated circuit, an embedded system, a field-programmable gate array (FPGA), a system-on-a-chip (SOC), or other integrated system or device. Additionally, in the illustrative embodiment, the compute engine 210 includes or is embodied as a processor 212 and a memory 214. The processor 212 may be embodied as any type of processor capable of performing the functions described herein. For example, the processor 212 may be embodied as a single or multi-core processor(s), a microcontroller, or other processor or processing/controlling circuit. In some embodiments, the processor 212 may be embodied as, include, or be coupled to an FPGA, an application specific integrated circuit (ASIC), reconfigurable hardware or hardware circuitry, or other specialized hardware to facilitate performance of the functions described herein.
These additional elements are recited at a high-level of generality such that they amount to no more than mere instructions to apply the exception using generic computer components.
Accordingly, these additional elements do not integrate the abstract idea into a practical application because they do not impose any meaningful limits on practicing the abstract idea. Therefore, the claim is directed to a judicial exception that is an abstract idea.
The claim does not include additional elements that are sufficient to amount to significantly more than the judicial exception. As discussed above with respect to integration of the abstract idea into a practical application, the additional element is a compute device and amount to no more than mere instructions to apply the abstract idea using generic computer components.
In conclusion, merely “applying” the exception using generic computer components cannot provide an inventive concept. Therefore, Independent claims 1 and 20 and the dependent claims 2-19 are not patent eligible under 35 USC 101.
Claim Rejections - 35 USC § 102
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 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 the appropriate paragraphs of 35 U.S.C. 102 that form the basis for the rejections under this section made in this Office action:
A person shall be entitled to a patent unless –
(a)(1) the claimed invention was patented, described in a printed publication, or in public use, on sale or otherwise available to the public before the effective filing date of the claimed invention.
Claim(s) 1-3, 7-20 rejected under 35 U.S.C. 102(a)(1) as being anticipated by Borysek, USP Pub. No. 20240161110.
As to claim 1(Currently Amended) Borysek discloses A compute device comprising: circuitry configured to:
obtain data indicative of financial transactions associated with one or more customer accounts with a financial institution; perform at least one data transformation operation on descriptions of the financial transactions in the obtained data to enable identification of recurring transactions, including grouping the financial transactions based on a similarity of the descriptions(Borysek, paras. 0003-0005, 0014-0017, 0040-0045; Figs. 5B-C);
combine determinations from multiple analysis algorithms executed on a group of the financial transactions to obtain a confidence score indicative of whether the group of transactions represents a recurring transaction(Borysek, paras.0014-0017 – see para. 0014- classification of given transaction as a recurring transaction… may involve (a) comparing the score for the given transaction to a score threshold, and (b) based on the comparison, either (i) “determine that the given transaction is classified as a recurring charge if the score meets or exceeds the score threshold or (ii) determine that the given transaction is classified as a non-recurring charge if the score is below the score threshold” see also paras. 0040-0045; Figs. 1, 3, 5B-C); wherein each of the multiple analysis algorithms independently produces a respective score for the group of the financial transactions, and the confidence score is obtained by summing the respective scores produced by each of the multiple analysis algorithms (Borysek, paras.0014, 0040-0045);
compare the confidence score to a threshold score to determine whether the group of financial transactions represents a recurring transaction (Borysek, paras.0014- classification of given transaction as a recurring transaction… may involve (a) comparing the score for the given transaction to a score threshold, and (b) based on the comparison, either (i) “determine that the given transaction is classified as a recurring charge if the score meets or exceeds the score threshold or (ii) determine that the given transaction is classified as a non-recurring charge if the score is below the score threshold”); and
present, in response to a determination that the confidence score indicates that the group of financial transactions represents a recurring transaction, a predicted amount and date for a recurrence of the recurring transaction (Borysek, paras. 0003-0005, 0014-0017, 0040-0045; Figs. 5B-C).
As to claim 2, Borysek discloses the compute device of claim 1, wherein to obtain data indicative of financial transactions comprises to exclude data indicative of transactions occurring more than a predefined number of times in a predefined time period(Borysek, para. 0060-0066, Figs. 5B-C).
As to claim 3, Borysek discloses the compute device of claim 2, wherein to exclude data indicative of transactions occurring more than a predefined number of times in a predefined time period comprises to exclude data indicative of transactions occurring more than 52 times in a year (Borysek, paras. 0094-0098, see also paras. 0014-0017, 0040-0045, 0063; Figs. 5B-C; see also paras. 0129-0130).
As to claim 7, Borysek discloses the compute device of claim 1, wherein the circuitry is configured to group financial transactions based additionally on a corresponding customer account associated with each financial transaction, wherein to perform at least one data transformation operation comprises to determine transaction dates from the descriptions (Borysek, paras. 0014-0017, 0040-0045, 0063; Figs. 5B-C; see also paras. 0129-0130).
As to claim 8, Borysek discloses the compute device of claim 7, wherein to determine transaction dates from the descriptions comprises to determine transaction dates by matching the descriptions to a set of predefined date encoding patterns(Borysek, paras. 0014-0017, 0040-0045, 0063; Figs. 5B-C; see also paras. 0129-0130).
As to claim 9, Borysek disclose the compute device of claim 1, wherein to combine determinations from multiple analysis algorithms comprises one or more of:
(i) to determine an identification score, wherein to determine an identification score comprises to determine the identification score as a function of frequency types and frequency methods; (ii) to determine a median days between transactions score; (iii) to determine at least one of an average days between transactions score or a weeks between transactions score; (iv) to determine a standard deviation of days between transactions score; (v) to determine a standard deviation of day of week score; (vi) to determine a standard deviation of day of month score; (vii) to determine a standard deviation of amount score; (viii) to determine a dominant amount score; (ix) to determine an automated clearing house and payroll score (Borysek, paras. 0128; 0147; see also paras. 0014-0016 – comparison to a baseline value).
As to claim 10, Borysek discloses the compute device of claim 1, wherein the circuitry is further configured to compare the confidence score to a second threshold score different from the threshold score of the classify the recurring transaction into a confidence tier(Borysek, para. 0014- classification of given transaction as a recurring transaction… may involve (a) comparing the score for the given transaction to a score threshold, and (b) based on the comparison, either (i) “determine that the given transaction is classified as a recurring charge if the score meets or exceeds the score threshold or (ii) determine that the given transaction is classified as a non-recurring charge if the score is below the score threshold”; see also paras. 0017, 0040-0045, 0063; Figs. 5B-C; see also paras. 0129-0130).
As to claim 11, Borysek discloses the compute device of claim 1, wherein the circuitry is further configured to perform a recurring transaction recognition operation based on feedback from a consumer indicating that transactions previously identified as recurring transactions are not recurring transactions or that transactions previously not identified as recurring transactions are recurring transactions(Borysek, paras. 0014-0017, 0040-0045, 0063; Figs. 5B-C; see also paras. 0129-0130).
As to claim 12, Borysek discloses the compute device of claim 1, wherein the circuitry is further configured to determine a predicted date for the recurrence of the recurring transaction as a function of a dominant interval indicative of a mode of days between financial transactions associated with the recurring transaction(Borysek, paras. 0014-0017, 0040-0045, 0063; Figs. 5B-C; see also paras. 0129-0130).
As to claim 13, Borysek discloses the compute device of claim 12, wherein the circuitry is further configured to determine a predicted date range for the recurrence of the recurring transaction (Borysek, paras. 0014-0017, 0040-0045, 0059-0065; Figs. 5B-C).
As to claim14, Borysek discloses the compute device of claim 1, wherein the circuitry is further configured to determine, in response to a determination that no dominant interval is present, a predicted date for the recurrence of the recurring transaction as a function of a frequency type associated with the recurring transaction(Borysek, paras. 0014-0017, 0040-0045, 0059-0065; Figs. 5B-C).
As to claim 15, Borysek discloses the compute device of claim 14, wherein to determine the predicted date as a function of a frequency type comprises one or more of: (i) to determine the predicted date as a function of a priority ranking of the frequency types; or (ii) to determine the predicted date as a function of the frequency type comprises to determine a predicted date range for the recurrence(Borysek, paras. 0014-0017, 0040-0045, 0059-0065; Figs. 5B-C).
As to claim 16, Borysek discloses the compute device of claim 1, wherein the circuitry is further configured to determine the predicted price of the recurrence of the recurring transaction, wherein to determine the predicted price comprises one or more of: (i) to determine the predicted price as a function of a dominant amount representing an amount that has occurred a threshold number of times within a predefined time period; or (ii) to determine the predicted price as a function of interquartile ranges(Borysek, paras. 0014-0017, 0040-0045, 0063; Figs. 5B-C; see also paras. 0129-0130).
As to claim 17, Borysek discloses the compute device of claim 1, wherein the circuitry is further configured to present a warning based on a current account balance and a predicted amount of recurring transactions for a remainder of a defined time period(Borysek, paras. 0014-0017, 0040-0045, 0059-0065; Figs. 5B-C).
As to claim 18, Borysek discloses the compute device of claim 17, wherein the circuitry is further configured to present a predicted remaining account balance after payment of the predicted amount(Borysek, paras. 0014-0017, 0040-0045, 0059-0065; Figs. 5B-C).
As to claim 19, Borysek discloses the compute device of claim 1, wherein the circuitry is further configured to present a summary of aggregate recurring transactions over a defined time period(Borysek, paras. 0040-0045, 0060-0067; Figs. 5B-C; see also paras. 0129-0130).
As to claim 20, Borysek discloses A method comprising:
obtaining, by a compute device, data indicative of financial transactions associated with one or more customer accounts with a financial institution;
performing, by the compute device, at least one data transformation operation on descriptions of the financial transactions in the obtained data to enable identification of recurring transactions, including grouping the financial transactions based on a similarity of the descriptions;
combining, by the compute device, determinations from multiple analysis algorithms executed on a group of the financial transactions to obtain a confidence score indicative of whether the group of transactions represents a recurring transaction(Borysek, paras. 0014-0017, see also paras. 0003-0005, 0040-0045; Figs. 5B-C); wherein each of the multiple analysis algorithms independently produces a respective score for the group of the financial transactions, and the confidence score is obtained by summing the respective scores produced by each of the multiple analysis algorithms (Borysek, paras.0014, 0040-0045);
comparing the confidence score to a threshold score to determine whether the group of financial transactions represents a recurring transaction (Borysek, paras.0014- classification of given transaction as a recurring transaction… may involve (a) comparing the score for the given transaction to a score threshold, and (b) based on the comparison, either (i) “determine that the given transaction is classified as a recurring charge if the score meets or exceeds the score threshold or (ii) determine that the given transaction is classified as a non-recurring charge if the score is below the score threshold”); and
and presenting, by the compute device and in response to a determination that the confidence score indicates that the group of financial transactions represents a recurring transaction, a predicted amount and date for a recurrence of the recurring transaction (Borysek, para. 0092 – “…type of merchant-level feature for the given transaction may take the form of a feature that indicates a distribution and/or concentration of the given merchant's historical transactions of a given type (e.g., card-not-present transactions) from some timeframe in the past (e.g., the past 12 months) with respect to the settlement (or authorization) amounts, authorization dates, and/or authorization times of the historical transactions, which may be predictive of whether or not the given transaction is a recurring charge because merchants that use recurring billing tend to follow certain behavioral patterns as it relates to settlement (or authorization) amounts, authorization dates, and/or authorization times of the historical transactions.”; see also paras, 0010, 0072, 0084-0086).
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.
Claims 4-6, are rejected under 35 U.S.C. 103 as being unpatentable over Borysek, USP Pub. No. 20240161110 in view of Elder, USP Pub. No. 20220245103
As to claim 4, Borysek does not directly disclose but Elder discloses the compute device of claim 1, wherein to perform at least one data transformation operation comprises one or more of (1) to convert the descriptions to uppercase; and/or to remove noise in the descriptions of the financial transactions (Elder, para. 0020 –“… lookup table may include one instance of each merchant key that is identified in the raw transaction records. Accordingly, the data cleansing platform may perform a data deduplication process to remove duplicate instances of a merchant key such that the lookup table includes no more than one instance of each merchant key”, see also Figs. 1-2, 4; para. 0001).
It would have been obvious to one skilled in the art before the effective filing date to modify the recurring transaction evaluation process of Borysek with the data cleaning mechanism of Elder because it would result in an optimization of the data processing environment and ultimately improve the quality of the data that is outputted.
As to claim 5, Borysek does not directly disclose but Elder discloses
the compute device of claim 4, wherein to remove noise comprises: (i) to remove digit and letter combinations; (ii) to remove one or more symbols; (iii) to remove month abbreviations; (iv) to expand predefined abbreviations into corresponding words; and/or (v) to remove repeated spaces(Elder, para. 0020 –“… lookup table may include one instance of each merchant key that is identified in the raw transaction records. Accordingly, the data cleansing platform may perform a data deduplication process to remove duplicate instances of a merchant key such that the lookup table includes no more than one instance of each merchant key”, see also Abstract, Figs. 1-2, 4; paras. 0001, 0014 – see rationale for combination in claim 4).
As to claim 6. Borysek does not directly disclose but Elder discloses the compute device of claim 1, wherein to perform at least one data transformation operation comprises to preserve or reinsert an alphanumeric sequence that satisfies a repetition threshold.( Elder, para. 0020 – “… the data cleansing platform may then use the merchant keys stored in the lookup table to generate an initial cleansed dataset (e.g., a baseline cleansed dataset) based on the raw transaction records obtained from the transaction data source. For example, the data cleansing platform may determine a merchant key in the lookup table that includes a combination of fields (e.g., name, city, state, zip, country, and MCC) that matches a corresponding set of fields in the raw transaction record, and the data cleansing platform may generate a cleansed transaction record in which the raw transaction record is associated with the merchant key and/or enhancement data associated with the merchant key (e.g., a logo, website, phone number, and/or location, among other examples). For example, in some implementations, the data cleansing platform may perform a data join operation to combine and/or reformat information included in the various fields of the raw transaction records based on merchant information that is associated with the merchant keys stored in the lookup table. In this way, the data cleansing platform may generate a cleansed dataset in which each transaction record is associated with a corresponding merchant key and/or related enhancement data that is formatted in a manner that is easily deciphered by a human and/or structured in such a way to enable data analytics tools to query, analyze, and/or otherwise interact with the cleansed transaction data.”, see also Abstract, Figs. 1-2, 4; para. 0001 – see rationale for combination in claim 4).
Conclusion
THIS ACTION IS MADE FINAL. Applicant is reminded of the extension of time policy as set forth in 37 CFR 1.136(a).
A shortened statutory period for reply to this final action is set to expire THREE MONTHS from the mailing date of this action. In the event a first reply is filed within TWO MONTHS of the mailing date of this final action and the advisory action is not mailed until after the end of the THREE-MONTH shortened statutory period, then the shortened statutory period will expire on the date the advisory action is mailed, and any nonprovisional extension fee (37 CFR 1.17(a)) pursuant to 37 CFR 1.136(a) will be calculated from the mailing date of the advisory action. In no event, however, will the statutory period for reply expire later than SIX MONTHS from the mailing date of this final action.
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/CHIKAODINAKA OJIAKU/Primary Examiner, Art Unit 3696
1 Interval Licensing, 896 F.3d at 1344–45 (concluding that ‘‘[s]tanding alone, the act of providing someone an additional set of information without disrupting the ongoing provision of an initial set of information is an abstract idea,’’ observing that the district court ‘‘pointed to the nontechnical human activity of passing a note to a person who is in the middle of a meeting or conversation as further illustrating the basic, longstanding practice that is the focus of the [patent ineligible] claimed invention.’’); Voter Verified, Inc. v. Election Systems & Software, LLC, 887 F.3d 1376, 1385 (Fed. Cir. 2018) (finding the concept of ‘‘voting, verifying the vote, and submitting the vote for tabulation,’’ a ‘‘fundamental activity’’ that humans have performed for hundreds of years, to be an abstract idea);
In re Smith, 815F.3d 816, 818 (Fed. Cir. 2016) (concluding that ‘‘[a]pplicants’ claims, directed to rules for conducting a wagering game’’ are abstract).
14 If a claim, under its broadest reasonable interpretation, covers performance in the mind but for the recitation of generic computer components, then it is still in the mental processes category unless the claim cannot practically be performed in the mind. See Intellectual Ventures I LLC v. Symantec Corp., 838 F.3d 1307, 1318 (Fed. Cir . 2016) (‘‘[W]ith the exception of generic computer-implemented steps, there is nothing in the claims themselves that foreclose them from being performed by a human, mentally or with pen and paper.’’); Mortg. Grader, Inc. v. First Choice Loan Servs. Inc., 811 F.3d. 1314, 1324 (Fed. Cir. 2016)(holding that computer-implemented method for ‘‘anonymous loan shopping’’ was an abstract idea because it could be ‘‘performed by humans without a computer’’); Versata Dev. Grp. v. SAP Am., Inc., 793 F.3d 1306, 1335 (Fed. Cir. 2015) (‘‘Courts have examined claims that required the use of a computer and still found that the underlying, patent-ineligible invention could be performed via pen and paper or in a person’s mind.’’); CyberSource Corp. v. Retail Decisions, Inc., 654 F.3d 1366, 1375, 1372 (Fed. Cir. 2011) (holding that the incidental use of ‘‘computer’’ or ‘‘computer readable medium’’ does not make a claim otherwise directed to process that ‘‘can be performed in the human mind, or by a human using a pen and paper’’ patent eligible); id. at 1376 (distinguishing Research Corp. Techs. v. Microsoft Corp., 627 F.3d 859 (Fed. Cir. 2010), and SiRF Tech., Inc. v. Int’l Trade Comm’n, 601 F.3d 1319 (Fed. Cir. 2010), as directed to inventions that ‘‘could not, as a practical matter, be performed entirely in a human’s mind’’). Likewise, performance of a claim limitation using generic computer components does not necessarily preclude the claim limitation from being in the mathematical concepts grouping, Benson, 409 U.S.at 67, or the certain methods of organizing human activity grouping, Alice, 573 U.S. at 219–20 - – See Federal Register / Vol. 84, No. 4 / Monday, January 7, 2019
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