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 preliminary amendment filed on 12/19/2025 and IDS filed on 8/12/2025. Claim 1 was cancelled. Claims 2-21 are new. Claims 2-21 are pending and examined.
Information Disclosure Statement
The information disclosure statement (IDS) was submitted on 8/12/25. The submission is in compliance with the provisions of 37 CFR 1.97. Accordingly, the information disclosure statement was considered by the examiner.
Priority
This application discloses and claims only subject matter disclosed in prior Application No. 17565224, filed on 12/29/21, and names the inventor or at least one joint inventor named in the prior application. Accordingly, this application may constitute a continuation or divisional. Should applicant desire to claim the benefit of the filing date of the prior application, attention is directed to 35 U.S.C. 120, 37 CFR 1.78, and MPEP § 211 et seq. The presentation of a benefit claim may result in an additional fee under 37 CFR 1.17(w)(1) or (2) being required, if the earliest filing date for which benefit is claimed under 35 U.S.C. 120, 121, 365©, or 386© and 1.78(d) in the application is more than six years before the actual filing date of the application.
Specification
The disclosure is objected to because of the following informalities: The priority section in paragraph 1 claims priority to the US patent application 17/565224 instead of US patent 12367467. Correction claiming priority to the US patent is required.
Examiner Notes
The claims are subject matter eligible because of additional elements including:
“update, in real-time, the corresponding graphical user interface on each customer device to reflect a corresponding selection status of each of the one or more items for payment” and
“at least one corresponding selection status associated with one of the one or more items indicates, via a visual indicator, a real-time collaboration by at least two customers of the plurality of customers sharing a cost associated with the or more items”,
that integrate the abstract idea into a practical application because they are more than “[u]se of a computer or other machinery in its ordinary capacity for economic or other tasks”, see MPEP 2106.05(f)(2), because of technological details including visual update on client device that shows selection status and the selection status visually displaying indicators showing a collaboration between two users.
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 (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 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.
Claims 2-5, 8-12, 14-18 and 20-21 are rejected under 35 U.S.C. 102(a)(1) as being anticipated by US 20200160296 A1 (Park).
As to claim 2, 10 and 16,
Park teaches,
receive, from a merchant device of a merchant, transaction data associated with a transaction (¶ 23 “order information”), wherein the transaction is between the merchant and a plurality of customers (FIG. 1, item 100 para. 23 “an affiliate”, para. 27 “an affiliate POS”), wherein each customer of the plurality of customers is associated with a separate customer device (FIG. 1, item 100, para. 27 “The user terminal 100 executes a payment app to request bill splitting”);
configure each customer device of the plurality of customers with a corresponding graphical user interface to reflect the transaction data, the transaction data including reference to one or more items associated with the transaction (para. 42 “A browser requests payment through the payment app by using the mobile phone number for the payment. After refreshing, the mobile bill is changed to the status “Bill Splitting in Progress.”, FIG. 5, items 100b-cc, para. 43 “a user terminal 100b or summons a mobile bill through a message uniform resource locator (URL) received when the bill splitting”, FIG. 13, para. 47);
update, in real-time, the corresponding graphical user interface on each customer device to reflect a corresponding selection status of each of the one or more items for payment (FIG. 13, para. 47 “the user may enter the amount to be paid only by checking information about a currently ordered menu item and a price of the menu item and then clicking an “Add Amount to be Paid” button”), wherein:
each of the one or more items is selectable by more than one of the plurality of customers (FIG. 13, para. 47); and
at least one corresponding selection status associated with one of the one or more items indicates, via a visual indicator, a real-time collaboration by at least two customers of the plurality of customers for sharing a cost associated with the one of the one or more items (FIG. 13, para. 48 “The amount to be paid is updated to the remaining amount 4,000 won after user B pays 9,000 won, and the affiliate POS 200 displays “Bill Splitting in progress” as the status”),
apportion amounts for each of the one or more items based on the corresponding selection status of each of the one or more items (FIG. 6, item 100a, para. 85 “ {circle around (1)} An amount to be divided indicates an amount of an order or an amount required to be paid. {circle around (2)} The sum of amounts entered indicates the sum of amounts requested to be paid of mobile phone numbers of designated payers”, FIG. 13, para. 48); and
process, as part of processing a total amount for the transaction, a corresponding sub-transaction for each of the plurality of customers based on the apportioned amounts (FIG. 13, para.54 “performs bill splitting through a payment app provided from the payment server 400”).
Additionally, with respect to claim 2,
Park teaches,
A payment system (para. 104 “bill splitting system”) comprising:
one or more memories storing computer-readable instructions (para. 104 “memory”); and
one or more processors configured to execute the computer-readable instructions (para. 104 “processor”, para. 105) to.
Additionally, with respect to claim 10,
Park teaches,
One or more non-transitory computer-readable media storing computer- readable instructions, which when executed by one or more processors of a payment system, cause the payment system (para. 104-105, 108) to.
Additionally, with respect claim 16,
Park teaches,
A method (para. 105, 107) comprising.
As to claims 3, 11 and 17, Park teaches all limitation of claims 2, 10 and 16.
Park teaches,
detect an interaction with an interactive element associated with the transaction data on the corresponding graphical user interface of a customer device (FIG. 13, para. 47 “the user may enter the amount to be paid only by checking information about a currently ordered menu item and a price of the menu item and then clicking an “Add Amount to be Paid” button”); and
display on the corresponding graphical user interface of the customer device a push notification for selecting apportionment of the one or more items with at least one other customer of the plurality of customers (FIG. 13, para. 48 “The amount to be paid is updated”)
As to claim 4, Park teaches all limitations of claim 2.
Park teaches,
display on the corresponding graphical user interface of each customer device, a corresponding customized list of items of the one or more items for a corresponding one of the plurality of customers (FIG. 13, para. 47).
As to claim 5, Park teaches all limitations of claims 2 and 4.
Park teaches,
determine the corresponding customized list of items for each of the plurality of customers (FIG. 13, para. para. 47-48).
As to claims 8, 15 and 20, Park teaches all limitations of claims 2, 10 and 16.
Park teaches,
generate a data structure associated with the transaction (FIG.s 2A-2C, para. 76 “when users A, B, and C order their menu items, order details and a table number where the users are sitting are entered to the affiliate POS”, para. 79 “the user terminal 100a summons a mobile bill”), wherein the data structure stores the transaction data associated with the transaction including the corresponding sub- transaction for each of the plurality of customers, and a record generated based on the transaction data, the record including one or more of an order, a bill, a receipt, or a user interface associated with the transaction (para. 79 “mobile bill”).
As to claims 9, 14 and 21, Park teaches all limitations of claims 2, 10 and 16.
Park teaches,
determine an interaction with a first item of the one or more items on a first customer device associated with a first customer of the plurality of customers (FIG. 13, para. 47 “the user may enter the amount to be paid only by checking information about a currently ordered menu item and a price of the menu item and then clicking an “Add Amount to be Paid” button”); and
provide a notification on the corresponding graphical user interface of at least a second customer device associated with a second customer of the plurality of customers, to indicate that the first customer has selected the first item for payment (FIG. 13, para. 48 “The amount to be paid is updated …”).
As to claims 11 and 18, Park teaches all limitations of claims 10 and 16.
Park teaches,
determine a corresponding customized list of items for each of the plurality of customers (FIG. 13, para. para. 47-48);
display on the corresponding graphical user interface of each customer device, the corresponding customized list of items of the one or more items (FIG. 13, para. para. 47).
Claim Rejections - 35 USC § 103
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 6, 7, 13 and 19 are rejected under 35 U.S.C. 103 as being unpatentable over Park in view of US 20220005045 A1 (Wu).
As to claims 6 and 13, Park teaches all limitations of claims 1, 4-5, 10 and 12.
Park does not teach,
determine the corresponding customized list of items using a machine learning model trained using at least prior transaction history associated with customers.
however, Wu teaches,
determine the corresponding customized list of items using a machine learning model trained using at least prior transaction history associated with customers (FIG. 6, items 602-608, para. 57 “a bill splitting recommendation is determined and provided … transaction data 402 received at machine learning models … historical bills and billing information …”).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to combine bill splitting of Park with AI based bill splitting of Wu because AI based bill splitting improves bill splitting by automating item to customer assignment in the split bill.
As to claim 7, combination of Park and Wu teach all limitations of claims 1, 4-6.
Park does not teach,
wherein the machine learning model is one of a logic regression model, a support vector machine, a neural network model, or a classifier.
however, Wu teaches,
wherein the machine learning model is one of a logic regression model, a support vector machine, a neural network model, or a classifier (para. 29 “machine learning models 404 are individually trained through supervised learning. Some non-limiting examples of supervised learning models include, for example and without limitation, nearest neighbor, naïve Bayes, decision trees, support vector machines, neural networks, or any machine learning algorithm suitable for classification problems”).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to combine bill splitting of Park with AI based bill splitting of Wu because AI based bill splitting improves bill splitting by automating item to customer assignment in the split bill.
As to claim 19, Park teaches all limitations of claims 16 and 18.
Park does not teach,
determining, by the one or more processors of the payment system, the corresponding customized list of items using a machine learning model trained using at least prior transaction history associated with customers, wherein the machine learning model is one of a logic regression model, a support vector machine, a neural network model, or a classifier.
however, Wu teaches,
determining, by the one or more processors of the payment system, the corresponding customized list of items using a machine learning model trained using at least prior transaction history associated with customers (FIG. 6, items 602-608, para. 57), wherein the machine learning model is one of a logic regression model, a support vector machine, a neural network model, or a classifier (para. 29).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to combine bill splitting of Park with AI based bill splitting of Wu because AI based bill splitting improves bill splitting by automating item to customer assignment in the split bill.
Conclusion
References made of record, not relied upon, pertinent to Applicant’s disclosure include:
US 20150120344 A1 (Rose) disclosing apportioning shared financial expenses,
US 20210097511 A1 (Kim) split payment,
(NPL) Aguilar, Eduardo, et al. "Grab, pay, and eat: Semantic food detection for smart restaurants." IEEE Transactions on Multimedia 20.12 (2018): 3266-3275.
Any inquiry concerning this communication or earlier communications from the examiner should be directed to BROCK E TURK whose telephone number is (571)272-5626. The examiner can normally be reached Monday-Friday 9AM-5PM EST.
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If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Ryan Donlon can be reached at 571-270-3602. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
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/BROCK E TURK/Examiner, Art Unit 3692
/RYAN D DONLON/Supervisory Patent Examiner, Art Unit 3692 August 4, 2026
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