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 .
Continued Examination Under 37 CFR 1.114
A request for continued examination under 37 CFR 1.114, including the fee set forth in 37 CFR 1.17(e), was filed in this application after final rejection. Since this application is eligible for continued examination under 37 CFR 1.114, and the fee set forth in 37 CFR 1.17(e) has been timely paid, the finality of the previous Office action has been withdrawn pursuant to 37 CFR 1.114. Applicant's submission filed on 5/1/2026 has been entered.
Response to Arguments
Applicant's arguments filed with respect to rejections under 35 USC 101 have been fully considered but they are not persuasive. Applicant argues the claims cannot practically be performed in the human mind and refers to the processor, computer-readable medium, using a machine learning model, applying a dimensionality reduction operation, etc. Examiner agrees that these additional elements are not abstract, however, the remaining steps of the claims – receiving…, determining…, determining…, constructing…, identifying…, altering…, extracting…, generating…, generating… are all evaluations and observations that fall within mental processes as they can all be performed in the mind and/or with pen and paper. Further they are certain methods of organizing human activity. For example, a person can gather transaction information, make determinizations and evaluations of the data to construct profiles and then use the profile to make predictions based on other gathered data related to geolocation and receipt level data to generate clusters of behavior patterns. The computer elements and machine learning are merely used to perform the abstract idea and there is nothing that integrates the abstract idea into a practical application. MPEP 2106.05 (a-h)
In response to comments regarding the dimensionality reduction, Applicant admits the operations involve algorithmic transformations. Mathematical algorithms are abstract (see MPEP 2106.04(a)(2)). Using a computer processor to implement a mathematical algorithm to perform the feature reduction operations amounts to using a computer as a tool to perform an abstract idea.
Continuing to focus on the dimensionality reduction operations, Applicant asserts the claims are directed to an improvement in the functioning of a computer or other technology and therefore integrate the abstract idea into a practical application. Examiner notes the use of the dimensionality reduction operations may lend to an improved way to analyze and cluster the behavior data, but this does not reflect a technological improvement. It is important to keep in mind that an improvement in the abstract idea itself is not an improvement in technology. For example, in Trading Technologies Int’l v. IBG, 921 F.3d 1084, 1093-94, 2019 USPQ2d 138290 (Fed. Cir. 2019), the court determined that the claimed user interface simply provided a trader with more information to facilitate market trades, which improved the business process of market trading but did not improve computers or technology.
With respect to Step 2B, Applicant argues the claims recite a non-conventional combination of computer-implemented operations that meaningfully limit any alleged judicial exception. Examiner disagrees. It is important to note that in order for a method claim to improve computer functionality, the broadest reasonable interpretation of the claim must be limited to computer implementation. That is, a claim whose entire scope can be performed mentally, cannot be said to improve computer technology. Synopsys, Inc. v. Mentor Graphics Corp., 839 F.3d 1138, 120 USPQ2d 1473 (Fed. Cir. 2016)
Applicant asserts the combination of elements provides a concrete technical improvement over conventional transaction analysis and machine learning systems and points to the dimensionality reduction as a n integral part of model generation. It is noted that as described in the specification any number of dimensionality reduction techniques may be used. Further, these types of mathematical algorithms are abstract and even if implemented with a computer processor, there is no integration into a practical application. While the claims may offer an improved judicial exception, there is no improvement to any computer or technology.
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.
Claim(s) 21-23, 25-36, 38, 39 are rejected under 35 U.S.C. 101 because the claimed invention is directed to a judicial exception (i.e., a law of nature, a natural phenomenon, or an abstract idea) without significantly more. Claim(s) 21-23, 25-36, 38, 39 is/are directed to a method, system, and computer program product. Thus, all the claims are within the four potentially eligible categories of invention (a process, a machine and an article of manufacture, respectively), satisfying Step 1 of the Subject Matter Eligibility (SME) test.
As per Prong One of Step 2A of the §101 eligibility analysis set forth in MPEP 2106, the Examiner notes that the claims recite mental processes, mathematical concepts and certain methods of organizing human activity.
More specifically, the independent claims recite:
receiving first transaction information associated with a first transaction at a first time, the first transaction information being anonymized and not including a full transaction card number [mental process – observation/evaluation - in the mind or with pen/paper];
determining that the first transaction information shares a threshold amount of attributes with second transaction information associated with at least one second transaction at one or more second times different from the first time [mental process – observation/evaluation - in the mind or with pen/paper];
based on the determination that the first transaction information shares a threshold amount of attributes with the second transaction information, determining that the first transaction information and the second transaction information are associated with a single purchaser [mental process – observation/evaluation - in the mind or with pen/paper];
identifying geolocation information for multiple stores; [mental process – observation/evaluation, in the mind or with pen/paper]
altering receipt-level transaction data received from the multiple stores by imputing categories or values to the receipt level transaction data; [mental process – observation/evaluation, in the mind or with pen/paper]
extracting features from the altered receipt level transaction data for model generation; [mental process – observation/evaluation, in the mind or with pen/paper]
applying a dimensionality reduction operation to the extracted features to generate reduced-dimension features [mathematical concepts]; and
generating clusters of behavior patterns based on the reduced-dimension features; [mathematical concepts] and
generating a predictive output of the at least one future transaction associated with the single purchaser using the temporal behavioral profile [mental process – observation/evaluation, in the mind or with pen/paper].
Further, the independent claims recite data analysis steps to analyze transaction information, construct a profile and predict future transactions which is certain methods of human activity. The concept of data analysis is a fundamental business practice long prevalent in our system of commerce. The use of data analysis is also a building block of ingenuity in corporate planning. Thus, data analysis, like hedging, is an "abstract idea" beyond the scope of §101. See Alice Corp. Pty. Ltd. at 2356.
Both claims 21 and 34 recite “Using a machine learning model”. In independent claim 21, the nominal recitation of a system comprising at least one processor and a non-transitory computer-readable medium containing instructions that, when executed by the at least one processor, cause the at least one processor to perform the method. Neither of these recitations preclude the claim from reciting an abstract idea as evidenced by the analysis at Prong 2 of Step 2A.
Regarding Prong Two of Step 2A, a claim reciting an abstract idea must be analyzed to determine whether any additional elements in the claim integrate the judicial exception into a practical application. Limitations that are indicative of integration into a practical application include: Improvements to the functioning of a computer, or to any other technology or technical field, as discussed in MPEP 2106.05(a); Applying or using a judicial exception to effect a particular treatment or prophylaxis for disease or medical condition – see Vanda Memo; Applying the judicial exception with, or by use of, a particular machine, as discussed in MPEP 2106.05(b); Effecting a transformation or reduction of a particular article to a different state or thing, as discussed in MPEP 2106.05(c); and Applying or using the judicial exception in some other meaningful way beyond generally linking the use of the judicial exception to a particular technological environment, such that the claim as a whole is more than a drafting effort designed to monopolize the exception, as discussed in MPEP 2106.05(e) and the Vanda Memo issued in June 2018.
In this case, the independent claims do not include limitations that meet the criteria listed above, thus the abstract idea is not integrated into a practical application. Independent claim 21 recites a system comprising at least one processor and a non-transitory computer-readable medium containing instructions that, when executed by the at least one processor, cause the at least one processor to perform the method which amounts to using a computer as a tool to perform the abstract idea. Both independent claims recite “Using a machine learning model” which amounts to using a computer as a tool to perform the abstract idea. There is no integration into a practical application.
The dependent claims further limit the abstract idea and some recite additional elements that do not integrate the abstract idea into a practical application. Claims 22 and 35 describe the temporal behavioral profile which is an abstract idea. Claim 23, 26 and 36, 38 recite details of a machine learning model to construct the profile which amounts to using a computer as a tool to perform an abstract idea. There is no integration into a practical application. Claim 25 recites details of the dimensionality reduction operation which is mathematical concepts and is abstract. Claims 27-31 and 39 recite details of gathering and analyzing transaction data and modifying the profile which is mental process (observation/evaluation) and certain methods of organizing human activity as explained in claim 21. The machine learning algorithm amounts to using a computer as a tool to perform an abstract idea and the system does not integrate the abstract idea into a practical application. Claims 32 and 33 recite details of the recommended action which is an additional step in the abstract idea – certain methods of organizing human activity and can be performed by pen and paper.
The ordered combination of elements in the dependent claims add nothing that is not already present as when the elements are taken individually. The claims do not include limitations beyond generally linking the use of the abstract idea to a particular technological environment. When considered individually, the system and software claim elements only contribute generic recitations of technical elements to the claims. It is readily apparent, for example, that the claim is not directed to any specific improvements of these elements. The invention is not directed to a technical improvement. When the claims are considered individually and as a whole, the additional elements noted above appear to merely apply the abstract concept to a technical environment in a very general sense.
Lastly and in accordance with Step 2B, 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 elements amount to no more than mere instruction to apply the exception using generic computer component. Mere instruction to apply an exception using generic computer components cannot provide an inventive concept.
Allowable Subject Matter
Claims 21-23, 25-36, 38, 39 would be allowable if rewritten to overcome the pending rejection under 35 USC 101. The cited prior art, taken alone or in combination, fails to disclose the temporal behavioral profile is constructed using a machine learning model trained using transaction information generated at different times and from multiple purchasers, wherein the machine learning model is generated by: identifying geolocation information for multiple stores; altering receipt-level transaction data received from the multiple stores by imputing categories or values to the receipt-level transaction data; extracting features from the altered receipt-level transaction data for model generation; and generating clusters of behavior patterns based on the extracted features.
As allowable subject matter has been indicated, applicant's reply must either comply with all formal requirements or specifically traverse each requirement not complied with. See 37 CFR 1.111(b) and MPEP § 707.07(a).
Conclusion
Any inquiry concerning this communication or earlier communications from the examiner should be directed to JOHNNA LOFTIS whose telephone number is (571)272-6736. The examiner can normally be reached M-F 7:00am-3:30pm.
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JOHNNA LOFTIS
Primary Examiner
Art Unit 3625
/JOHNNA R LOFTIS/Primary Examiner, Art Unit 3625
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