DETAILED ACTION
Notice of Pre-AIA or AIA Status
The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
Status of Claims
This action is in reply to the claims filed on 06/29/2026.
Claims 1, 11, and 19 are amended.
Claims 1-20 are currently pending and have been examined.
Continued Examination
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and the fee set forth in 37 CFR 1.17(e) has been timely paid, the finality of the previous Office action has been withdrawn pursuant to 37 CFR 1.114.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 07/28/2026 has been entered.
Subject Matter Free of Prior Art
Claims 1, 11, and 19 are determined to have overcome the prior art of rejection and are free of prior art, however the claims remain rejected under 35 USC 101, as set forth above. All dependent claims are also free of prior art by virtue of dependency, but remain rejected under 35 USC 101.
Claim 1 now recites additional features of: evaluating, by a non-barcoded item predictor, transaction history data and loyalty data to identify previously purchased non-barcoded items by the customer and a frequency of each non- barcoded item purchased by the customer, and assigning a calculated probability to each predicted item code based on current metrics and patterns in the transaction history for which the customer purchased a non-barcoded item corresponding to a given predicted item code.
Claim 11 now recites additional features of: wherein generating further includes analyzing each customer's set of historical non-barcoded item transaction records to obtain metrics and patterns comprising at least a frequency of purchase of each non-barcoded item and repeated purchase patterns by day of week, month, or in combination with a barcoded item being purchased in a same transaction.
Claim 19 now recites additional features of: analyzing the set of historical non-barcoded item transaction records to obtain metrics and patterns for each predicted item code, and dynamically sorting the data structure during the current transaction based on a context of item codes scanned for the current transaction to adjust top predicted item codes of the data structure.
The closest prior art was found to be as follows:
Migdal (US 2022/0277313 A1) is directed to method for image-based product recognition and verification. Migdal discloses maintaining a list of predicted item codes for non-barcoded items based on a transaction history of a customer (¶ [0028],¶ [0030], providing a predicted item code obtained from the list (¶ [0030]), causing the transaction interface to present the predicted item code to the customer as a selectable item code for current non-barcoded item before the customer performs an item code search within the transaction interface for the potential item code (¶ [0030]; ¶ [0036]).
However Migdal does not anticipate nor render obvious: wherein maintaining further includes generating a set of historical non- barcoded item transaction records for the customer from a customer's historical transactions, wherein each record includes items processed in the customer's historical transactions for which an item code was manually entered or provided during a current transaction as an indication of a previously purchased non-barcoded item, and analyzing the set of historical non-barcoded item transaction records to obtain a variety of metrics and patterns; evaluating, by a non-barcoded item predictor, transaction history data and loyalty data to identify previously purchased non-barcoded items by the customer and a frequency of each non- barcoded item purchased by the customer, and assigning a calculated probability to each predicted item code based on current metrics and patterns in the transaction history for which the customer purchased a non-barcoded item corresponding to a given predicted item code.
Jacobs (US 2002/0194074 A1) is directed to a method of and apparatus for self-checkout of non-bar coded items which includes using a graphic user interface (GUI) on a touch screen display. Jacobs discloses wherein maintaining further includes generating a set of historical non- barcoded item transaction records for the customer from a customer's historical transactions (¶ [0058]), wherein each record includes items processed in the customer's historical transactions for which an item code was manually entered or provided during a current transaction as an indication of a previously purchased non-barcoded item (¶ [0058]), and analyzing the set of historical non-barcoded item transaction records to obtain a variety of metrics and patterns (¶¶ [0058]-[0059]); evaluating, by a non-barcoded item predictor, transaction history data to identify previously purchased non-barcoded items by the customer and a frequency of each non- barcoded item purchased by the customer (¶ [0060]), and assigning a calculated probability to each predicted item code based on current metrics and patterns in the transaction history for which the customer purchased a non-barcoded item corresponding to a given predicted item code (¶ [0057]).
However, Jacobs does not disclose or render obvious: using loyalty data; wherein generating further includes analyzing each customer's set of historical non-barcoded item transaction records to obtain metrics and patterns comprising at least a frequency of purchase of each non-barcoded item and repeated purchase patterns by day of week, month, or in combination with a barcoded item being purchased in a same transaction; or and dynamically sorting the data structure during the current transaction based on a context of item codes scanned for the current transaction to adjust top predicted item codes of the data structure.
Moreover, the Examiner agrees with Applicant’s arguments presented on pages 13-14 of the Remarks, that when combining Migdal in view of Jacobs one of ordinary skill in the art would not arrive at the claimed invention.
Molander (US 2017/0046675 A1) is directed to conducting purchase transactions, and more specifically, to displaying repeating purchase transaction elements based on a determined hierarchy. Molander discloses using loyalty data (¶ [0017] and integrating access to the data structure into a loyalty account of a loyalty system of the customer (¶ [0017]).
However, Molander does not disclose or render obvious: evaluating, by a non-barcoded item predictor, transaction history data and loyalty data to identify previously purchased non-barcoded items by the customer and a frequency of each non- barcoded item purchased by the customer, and assigning a calculated probability to each predicted item code based on current metrics and patterns in the transaction history for which the customer purchased a non-barcoded item corresponding to a given predicted item code; wherein generating further includes analyzing each customer's set of historical non-barcoded item transaction records to obtain metrics and patterns comprising at least a frequency of purchase of each non-barcoded item and repeated purchase patterns by day of week, month, or in combination with a barcoded item being purchased in a same transaction; or analyzing the set of historical non-barcoded item transaction records to obtain metrics and patterns for each predicted item code, and dynamically sorting the data structure during the current transaction based on a context of item codes scanned for the current transaction to adjust top predicted item codes of the data structure.
Claim Rejections- 35 U.S.C. § 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 an abstract idea without significantly more.
Under Step 1 of the subject matter eligibility (SME) analysis described in MPEP 2106.03, the instant claims fall within the four statutory categories of invention identified by 35 U.S.C. 101. In the instant case, claims 1-18 are directed to methods, and claims 19-20 are directed to a machine. Claims 1, 11, and 19 are parallel in nature, therefore, the analysis will use claim 11 as the representative claim.
In Step 2A Prong One, it must be considered whether the claims recite a judicial exception. Claim 1 recites abstract concepts including: maintaining a list of predicted item codes for non-barcoded items based on a transaction history of a customer, wherein maintaining further includes generating a set of historical non- barcoded item transaction records for the customer from a customer's historical transactions, wherein each record includes items processed in the customer's historical transactions for which an item code was manually entered or provided during a current transaction as an indication of a previously purchased non-barcoded item, and analyzing the set of historical non-barcoded item transaction records to obtain a variety of metrics and patterns; evaluating, by a non-barcoded item predictor, transaction history data and loyalty data to identify a previously purchased non-barcoded items by the customer and frequency of each non-barcoded item purchased by the customer, and assigning a calculated probability to each predicted item code based on current metrics and patterns in the transaction history for which the customer purchased a non-barcoded item corresponding to a given predicted item code; providing a predicted item code obtained from the list of predicted item codes during the current transaction of the customer ... responsive to an indication that the customer is operating ... to locate a potential item code for a current non- barcoded item; and causing ... to present the predicted item code to the customer as a selectable item code for the current non-barcoded item before the customer performs an item code search ... for the potential item code.
Claim 11 recites abstract concepts including: generating a data structure that identifies predicted item codes for non-barcoded items purchased by customer, wherein generating includes identifying each customer using a unique loyalty account or identifier within loyalty data, and identifying historical transactions for a corresponding customer from transaction data using a corresponding loyalty account, and generating a set of historical non-barcoded item transaction records for each customer from a corresponding customer’s historical transactions, wherein generating further includes analyzing each customer’s set of historical non-barcoded item transaction records to obtain metrics and patterns comprising at least a frequency of purchase of each non-barcoded item and repeated purchase patterns by day of week, month, or in combination with a barcoded item being purchased in a same transaction; integrating access to the data structure into a loyalty account ... of the customer; and providing access to the data structure through the loyalty account to enhance a transaction ... during a current transaction of the customer by presenting at least one of the predicted item codes as a selectable option to the customer for a current non-barcoded item in addition to an item code searching option provided by the transaction.
Claim 19, which recites abstract limitations similar to those identified in claim 11, additionally recites analyzing the set of historical non-barcoded item transaction records to obtain metrics and patterns for each predicted item code, and dynamically sorting the data structure during the current transaction based on a context of item codes scanned for the current transaction to adjust top predicted item codes of the data structure.
These identified limitations of claims 1, and 11 and 19 set forth and describe the abstract idea of “predicting item codes for non-barcoded items”, which falls within the “Certain Methods of Organizing Human Activities” grouping as this concept is a sales activity or behavior. These limitations describe data analysis, organizing, and sorting used to perform the abstract item code prediction. Additionally, the limitations reciting generating, integrating access, and providing access to a data structure are described at such a high level they could be performed in the human mind. For example, a person can mentally generate a list, associate the list with a loyalty account (integrate access to the data structure), and make the list available (provide access to the data structure). Accordingly, claims 1, 11, and 19 recite an abstract idea. See MPEP 2106.04.
In Step 2A, Prong Two Examiners evaluate whether the claim recites additional elements that integrate the judicial exception into a practical application. Instant claims 1, 11, and 19 recite additional elements including: a terminal; a loyalty system; a transaction interface of a terminal; at least one server comprising at least one processor and a non-transitory computer-readable storage medium; the non-transitory computer-readable storage medium comprising instructions. The loyalty system and transaction interface are understood to refer to executable instructions (specification ¶ [0012]-[0013]), and the server, processor, and non-transitory computer-readable medium are not described in any relevant detail to distinguish this hardware from generic computer components. As explained in MPEP 2106.05(f), the use of a computer or other machinery in its ordinary capacity for economic or other tasks (e.g., to receive, store, or transmit data) or simply adding a general purpose computer or computer components after the fact to an abstract idea (e.g., a fundamental economic practice or mathematical equation) does not integrate a judicial exception into a practical application or provide significantly more. The additional elements, in combination with the identified abstract limitations, amount to no more than mere instruction to apply the abstract idea with a generic computer which cannot provide integration. See MPEP 2106.05. Claims 1, 11, and 19 are thus directed to an abstract idea.
Under Step 2B of the SME analysis, if it is determined that the claims recite a judicial exception that is not integrated into a practical application of that exception, it is then necessary to evaluate the additional elements individually and in combination to determine whether they provide an inventive concept (i.e., whether the additional elements amount to significantly more than the exception itself).
The claims do not include additional elements that are sufficient to amount to significantly more than the judicial exception because, as discussed above with respect to integration of the abstract idea into a practical application, the additional element(s) individually and in combination are merely being used to apply the abstract idea to a general computer components. For the same reason, the elements are not sufficient to provide an inventive concept. Implementing an abstract idea on a generic computer, does not add significantly more in Step 2B, similar to how the recitation of the computer in the claim in Alice amounted to mere instructions to apply the abstract idea of intermediated settlement on a generic computer (MPEP 2106.05(f). Accordingly, claims 1, 11, and 19 are ineligible.
Dependent claim(s) 2-10 and 11-17 do not aid in the eligibility of the independent claims. These claims merely further define the abstract idea without reciting any further additional elements. Thus, dependent claims 2-10 and 11-17 are also ineligible.
Dependent claim 18 recites additional elements including: providing an application programming interface call to retrieve the data structure using a loyalty identifier for the loyalty account. Similar to the additional elements identified above, the application programming interface call is described in ordinary terms and merely used as a tool in performance of the abstract idea. The additional element does not provide integration or provide significantly more than the abstract idea because it simply applies the abstract idea with an API without any recitation of details of how to carry out the retrieving. See MPEP 2106.05(f). Accordingly, claim 18 is ineligible.
Dependent claim 20 recite additional elements including: wherein the terminal is a self-service terminal ... or the terminal is a point-of-sale terminal. Limitations that amount to merely indicating a field of use or technological environment in which to apply a judicial exception do not amount to significantly more than the exception itself, and cannot integrate a judicial exception into a practical application (MPEP 2106.05(h)). Confining the use of the abstract idea (predicting non-barcoded items during checkouts) to a particular technological environment (a self-service terminal or point-of-sale terminal), where these terminals are not recited in any specific technical detail, does not add significantly more similar to how requiring that the abstract idea be performed using a computer merely indicated a field of use in which to apply the judicial exception (buySAFE Inc. v. Google, Inc., 765 F.3d 1350, 1354, 112 USPQ2d 1093, 1095-96 (Fed. Cir. 2014).
Response to Arguments
Applicant's arguments filed 06/29/2026 with respect to the § 101 rejection of claims 1-20 have been fully considered but they are not persuasive.
On page 7 of the Remarks, Applicant argues “II. The Claims Are Directed to a Specific Technical Improvement, Not an Abstract Idea”.
The Examiner respectfully disagrees. In computer-related technologies, the examiner should determine whether the claim purports to improve computer capabilities or, instead, invokes computers merely as a tool. Enfish, LLC v. Microsoft Corp., 822 F.3d 1327, 1336, 118 USPQ2d 1684, 1689 (Fed. Cir. 2016). To show that the involvement of a computer assists in improving the technology, the claims must recite the details regarding how a computer aids the method, the extent to which the computer aids the method, or the significance of a computer to the performance of the method. Merely adding generic computer components to perform the method is not sufficient. Thus, the claim must include more than mere instructions to perform the method on a generic component or machinery to qualify as an improvement to an existing technology.
The claims are directed to an abstract method of maintaining a list of predicted item codes based on a transaction history of a customer and providing a predicted item code during a transaction based on a calculated probability. The recitation of “maintaining a data structure” is not tied to any specific hardware, architecture, etc., but is recited so broadly that it amounts to a simple list. The features Applicant relied on as providing a technical improvement – analyzing loyalty account data, transaction history, and metrics and patterns to generate a predicted list of item codes and dynamically sorting the list based on the context of a transaction – are themselves directed to the abstract idea. These limitations amount to collecting and analyzing data and outputting a result, which are activities the courts have found to be mental processes and do not reflect an improvement to computer functionality of any other technology (MPEP 2106.04(a)(2) “a claim to ‘collecting information, analyzing it, and displaying certain results of the collection and analysis,’ where the data analysis steps are recited at a high level of generality such that they could practically be performed in the human mind”, Electric Power Group v. Alstom, S.A., 830 F.3d 1350, 1353-54, 119 USPQ2d 1739, 1741-42 (Fed. Cir. 2016). Similarly, “dynamically” sorting the list does not add technical substance because sorting dynamically or automatically using a generic computer does not transform an abstract idea into a technical improvement ( "claiming the improved speed or efficiency inherent with applying the abstract idea on a computer" does not integrate a judicial exception into a practical application or provide an inventive concept. Intellectual Ventures I LLC v. Capital One Bank (USA), 792 F.3d 1363, 1367, 115 USPQ2d 1636, 1639 (Fed. Cir. 2015)).
Applicants arguments to a purported technical problem are unpersuasive because the claimed solution does not solve a technical problem with technical means but instead relies on data analysis and generic computer components. A customer’s transaction experience is improved by better predicting what they are buying, not by any improvement to how the computer, network, or terminal functions (see para [0001] "experience can become frustrating").
DDR Holdings and BASCOM do not support eligibility of the present claims, because the facts of those cases are materially different from the present claims. Unlike DDR, where the claims solved a problem “necessarily rooted in computer technology”, the present claims solve a business problem of helping a customer avoid manually and incorrectly providing an item code which is not unique to computer technology and could be perform by a cashier using the customer’s known purchase history and loyalty information. The claims recite generic computer components executing in their ordinary capacity to store data, execute instructions, and display results; they do not alter the way a computer or network normally operates as the claims in DDR did.
In BASCOM the inventive concept arose from a specific, unconventional technical arrangement (installing individually customizable filtering tool at a remote ISP server) which changed the network architecture itself. The Applicant does not identify a comparable unconventional technical arrangement. Storing customer-specific predictive lists linked to a loyalty account and displaying them on a terminal before a search is performed is a business strategy for personalizing when and what information is displayed, not an unconventional arrangement of hardware or network components. Accordingly, the present claims do not reflect a technical improvement to the terminal, server, or storage medium themselves as they are only invoked in their ordinary capacity to perform generic functions including to store data, execute instructions, and display results.
On page 9 of the Remarks, Applicant argues “III. Desjardins and Kelley Confirm Eligibility”.
The Examiner respectfully disagrees. Applicant’s reliance on Desjardins and Kelley is misplaced because those decisions addressed claims reciting technical improvements to how a machine learning model itself is trained and operated, whereas the present claims do not. Applicant’s assertion that “the same analysis applies here” is unsupported because the features Applicant lists – generating historical transaction records, analyzing metrics and patterns, assigning calculated probabilities, dynamically sorting based on basket content, and proactively presenting predicting item codes – are not technical improvements comparable to Desjardins and Kelley. The argued features describe abstract data gathering, analysis, and outputting a result, not a technical improvement to a model or algorithm. Furthermore, Applicant’s characterization of these elements as improving “how the self-checkout transaction system itself operates” is also unsupported by the claim language because claim 19, for example, does not recite any change to a self-checkout terminal’s hardware, software architecture, or network and instead uses these components only for their generic functions of storing data and displaying an interface. The alleged benefits of reducing friction, improving accuracy, and enhancing transaction throughput, are business benefits resulting from more accurately predicting an item code, not technical benefits that result from an improvement to the transaction system’s underlying operation. Accordingly, because the present claims do not recite any technical improvement to any underlying model, algorithm or system operation, Applicant’s reliance on Kelley and Desjardins does not support a finding of eligibility.
On page 9 of the Remarks, Applicant under “IV. Step 2A, Prong 2 – Integration Into a Practical Application.” Applicant argues the claims recite “a specific technical architecture that improves the functioning of the self-checkout terminal system” and that the Examiner’s characterization of the claims as directed to ‘predicting non-barcoded items’ is an “impermissible over-generalization”.
The Examiner respectfully disagrees. Applicant’s Step 2A, Prong 2 argument fails for the same reasons addressed above – the recited features describe a business strategy performed by generic components and do not recite a specific technical architecture that improves the underlying transaction system operation. Furthermore, Applicant’s over-generalization argument in relation to Enfish, where characterizing the claims at a high level of abstraction ignored a specific claimed improvement, is unpersuasive here. In the present claims, the additional limitations argued as not describing “predicting non-barcoded items” indeed simply describe how the abstract prediction is made and delivered (e.g., using transaction history, loyalty accounts, calculated probabilities, dynamic sorting, and terminal presentation). The Examiner’s characterization is therefore an accurate distillation of the claims, not an improper over-generalization.
On page 9 of the Remarks, under “V. Step 2B – Significantly More” Applicant argues “the ordered combination of claim elements provides significantly more than any abstract idea”.
The Examiner respectfully disagrees. Applicant’s 2B argument is unpersuasive because it relies on the same limitations already found to be abstract above. Applicant does not identify an unconventional technical architecture recited in the claims that is comparable to the remotely installed filtering tool in BASCOM. Linking predictions to a loyalty account and surfacing them before a search is a business arrangement of the abstract idea itself, not a non-conventional technical arrangement of hardware and network components, as in BASCOM, and cannot supply significantly more in step 2B.
For at least these reasons, the Examiner is maintaining the § 101 rejection of claims 1-20.
Applicant's arguments filed 06/29/2026 with respect to the § 103 rejections of claims 1, 3-4, 6, and 8-19 have been fully considered and are persuasive. The 103 rejections of the pending claims have been withdrawn.
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure:
Brakob et al. (US 2023/0037427 A1) is directed to systems and methods for determining whether an unknown product matches a scanned barcode during checkout.
Crompton et al. (US 2023/0100172 A1) is directed to a retail system with automatic recognition of items for self-checkout using item matching.
Gu (US 6,409,085 B1) relates to product checkout devices and more specifically to a method of recognizing produce items using checkout frequency.
V. Nandhakumar, B. Jyothsna and S. Gnanapriya (NPL Reference U) proposes an approach using deep learning to develop a self-checkout system and also streamline the stocking process by implementing an automated system that tracks the purchases and inventory in real-time.
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/K.G.W./Examiner, Art Unit 3688
/KELLY S. CAMPEN/Primary Examiner, Art Unit 3691
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