Notice of Pre-AIA or AIA Status
The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
Response to Amendment
Applicant’s “Response to Amendment and Reconsideration” filed on 12/23/2025 has been considered.
Claim 1-16, 26 are cancelled. Claims 33-35 are added. Claims 17-25, 27-35 are pending in this application and an action on the merits follows.
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 17-25, 27-35 are rejected under 35 U.S.C. 101 because the claimed invention is directed to a judicial exception (abstract idea) without significantly more.
Regarding claim 17, under Step 2A, recites a judicial exception (abstract idea) that is not integrated into a practical application and does not provide significantly more.
Under Step 2A (prong 1), and taking claim 17 as representative recite:
checking in the customer for the sequence of multiple purchase transactions;
receiving items of billing data for each of the purchase transactions, each item comprising a purchase revenue of the purchase transaction,
checking out the customer for the sequence of purchase transactions;
adding up the purchase revenues, and e) generating payment data from the added-up purchase revenues and from payment service provider data of the customer,
wherein checking out of the customer triggers at least the step of generating the payment data and
the customer is checked out automatically by the seller unit depending on previously stored seller-specific and/or customer-specific checking-out base data, by
determining a checking-out time at which the checking-out will be performed on the basis of the checking-out base data and/or a checking-out criterion, checking a plausibility of the billing data performing a plausibility check by:
evaluating the checking out base-data using one or more predetermined criteria, wherein the checking-out base data comprises as seller-specific data a typical length of stay in a sales outlet in which the sequence of the multiple purchase transactions is performed, and/or standard ordering procedures, and/or as customer-specific data, a history of products already purchased, a history of past purchase transactions, and/or a number of people associated with the billing data, and
wherein the plausibility check is based on one or more fixed rules and/or one or more self-learning algorithms, and wherein the steps are performed in the seller unit without any interaction with the customer.
These limitations recite fundamental economic practice, commercial interaction and mental processes (see: MPEP 2106.04(a)(2)(II)). This is because the limitations above recite managing purchases, aggregating transactions, generating payment, checking in and out, billing, determining when to check out based on patterns (human)... Accordingly, under step 2A (prong 1) the claim recites an abstract idea of commercial payment processing and customer session management that fall within the “Certain methods of organizing human activity and mental processes” grouping of abstract ideas.
Under Step 2A (prong 2), viewed individually or as a whole the abstract idea is not integrated into a practical application. The Examiner acknowledges that additional elements such as seller unit, plausibility check, and generic terms of receiving, checking, generating, adding without technical implementation. Dependent claims recite additional elements such as mobile device, machine learning. Although reciting additional elements, these elements are not sufficient to integrate the abstract idea into a practical application. This is because the additional elements are recited at a high level of generality (i.e. as generic computing hardware) such that they amount to nothing more than the mere instructions to implement or apply the abstract idea on generic computing hardware or, merely uses a computer as a tool to perform an abstract idea. Further, the additional elements do no more than generally link the use of a judicial exception to a particular technological environment or field of use (such as computers or computing networks).
Secondly, the additional elements are insufficient to integrate the abstract idea into a practical application because the claim fails to (i) reflect an improvement in the functioning of a computer, or an improvement to other technology or technical field, (ii) implement the judicial exception with, or use the judicial exception in conjunction with, a particular machine or manufacture that is integral to the claim, (iii) effect a transformation or reduction of a particular article to a different state or thing, or (iv) applies or uses the judicial exception in some other meaningful way beyond generally linking the use of the judicial exception to a particular technological environment. Claim recitations automate a business decision of when to check out and charge, which does not present a technical problem in computing.
Even considered as an ordered combination (as a whole), the additional elements of dependent claims 18-25, 27-35, do not add anything further than when they are considered individually.
In view of the above, under Step 2A (prong 2), claims 17-25, 27-35 do not integrate the recited exception into a practical application (see again: 2019 PEG).
Under Step 2B, examiners should evaluate 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). In this case, the claims do not include additional elements that are sufficient to amount to significantly more than the judicial exception.
Returning to claim 17 taken individually or as a whole the additional elements do not provide an inventive concept (i.e. they do not amount to “significantly more” than the exception itself). As discussed above with respect to the integration of the abstract idea into a practical application, the additional elements used to perform the claimed process amount to no more than the mere instructions to apply the exception using a generic computer and/or no more than a general link to a technological environment. For instance, using standard computer technology to automate tab managements and checkout timing is routine. Machine learning of checkout time is a predictable use of machine learning in commerce. Tracking purchases are standard POS functions, aggregating totals is basic accounting, using customer history is common in retail systems, fraud/plausibility check is conventional, automation of a checkout is a known trend, self-learning algorithm is claimed functionally not technically.
The additional elements fail to provide significantly more also because the claim simply appends well-understood, routine, conventional activities previously known to the industry, specified at a high level of generality, to the judicial exception. For example, the additional elements of claim 17 utilize operations the courts have held to be well-understood, routine, and conventional (see: MPEP 2106.05(d)(II)), including at least:
receiving or transmitting data over a network
storing and retrieving information in memory
performing repetitive calculations
Further, see MPEP 2106.05(f), “Other examples where the courts have found the additional elements to be mere instructions to apply an exception, because they do no more than merely invoke computers or machinery as a tool to perform an existing process include: i. A commonplace business method or mathematical algorithm being applied on a general purpose computer, Alice Corp. Pty. Ltd. V. CLS Bank Int’l, 134 S. Ct. 2347, 1357, 110 USPQ2d 1976, 1983 (2014); Gottschalk v. Benson, 409 U.S. 63, 64, 175 USPQ 673, 674 (1972); Versata Dev. Group, Inc. v. SAP Am., Inc., 793 F.3d 1306, 1334, 115 USPQ2d 1681, 1701 (Fed. Cir. 2015);”.
See MPEP 2106.05(d), “i. Receiving or transmitting data over a network, e.g., using the Internet to gather data, Symantec, 838 F.3d at 1321, 120 USPQ2d at 1362 (utilizing an intermediary computer to forward information); TLI Communications LLC v. AV Auto. LLC, 823 F.3d 607, 610, 118 USPQ2d 1744, 1745 (Fed. Cir. 2016) (using a telephone for image transmission); OIP Techs., Inc., v. Amazon.com, Inc., 788 F.3d 1359, 1363, 115 USPQ2d 1090, 1093 (Fed. Cir. 2015) (sending messages over a network); buySAFE, Inc. v. Google, Inc., 765 F.3d 1350, 1355, 112 USPQ2d 1093, 1096 (Fed. Cir. 2014) (computer receives and sends information over a network); but see DDR Holdings, LLC v. Hotels.com, L.P., 773 F.3d 1245, 1258, 113 USPQ2d 1097, 1106;
Even considered as an ordered combination (as a whole), the additional elements of dependent claims 18-25, 27-35 do not add anything further than when they are considered individually.
In view of the above, claims 17-25, 27-35 do not provide an inventive concept (“significantly more”) under Step 2B, and is therefore ineligible for patenting.
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 17, 19, 21-23, 25, 31-33, 35 are rejected under 35 U.S.C. 103 as being unpatentable over Puerini et al. (U.S. Patent Publication No. 2015/0012396), in view of Liu et. al. (U.S. Patent Publication No. 2015/0178735).
Regarding claim 17, Puerini teaches associate the item identifiers and/or the item identifier list with the user and/or the user profile associated with the user that is receiving the items as part of the transition, [93]:
checking in the customer for the sequence of multiple purchase transactions; (identify, using fourth data collected by at least one of the plurality of input devices in the materials handling facility, the user when the user arrives at the materials handling facility, claim 4;
receiving items of billing data for each of the purchase transactions, each item comprising a purchase revenue of the purchase transaction, (payment instrument associated with a user profile maintained by the inventory management system for the user that may be utilized to charge a fee to the user for the picked items. Likewise, the inventory management system may provide an electronic message to the user confirming the picked items and/or the amount of the fee charged for the picked items, [63]),
checking out the customer for the sequence of purchase transactions; (The exit of the user will be detected and, as the user passes through the exit (transition area), the user, without having to stop or otherwise be delayed, will automatically be charged a fee for the items (the items are transitioned to the user, [17]),
adding up the purchase revenues, (charged a fee for the items, [17]), and e) generating payment data from the added-up purchase revenues and from payment service provider data of the customer, (charge the user for a purchase of the item, charge the user for a use of the item, transfer an ownership of the item to the user, transfer a control of the item to the user, or add the item identifier to a purchase history associated with the user, claim 2),
wherein checking out of the customer triggers at least the step of generating the payment data (automatically be charged a fee for the items (the items are transitioned to the user, the customer is checked out automatically by the seller unit depending on previously stored seller-specific and/or customer-specific checking-out base data, [17]),
determining a checking-out time at which the checking-out will be performed on the basis of the checking-out base data and/or a checking-out criterion, evaluating the checking out base-data using one or more predetermined criteria, (the position or location of the user may be monitored as the user progresses through the materials handling facility. It may then be determined that the user has entered or passed through a transition area based on the monitored position of the user, [89]),
and wherein the steps are performed in the seller unit without any interaction with the customer, (if the user is a customer at a retail location (materials handling facility), rather than having to “check out” with a teller or clerk that identifies each picked item and then charges the customer for the picked items, the user may simply exit the retail location, [63], the items have already been identified, the transition may be done automatically without any affirmative input from the user or delay to the user, [17]).
Puerini does not explicitly disclose checking a plausibility of the billing data performing a plausibility check by wherein the checking-out base data comprises as seller-specific data a typical length of stay in a sales outlet in which the sequence of the multiple purchase transactions is performed, and/or standard ordering procedures, and/or as customer-specific data, a history of products already purchased, a history of past purchase transactions, and/or a number of people associated with the billing data, and wherein the plausibility check is based on one or more fixed rules and/or one or more self-learning algorithms. Puerini teaches determined that the confidence score exceeds the pick threshold, [78].
However, Liu teaches the business rules optimizer service will perform analysis upon the past transaction data of the particular bank or financial institution, as well as that of its peers, for each of these transaction handlers. By way of access to such a large collection of diverse transaction data, the optimizer service arrives at an optimized set of business rules that are to be used when deciding whether or not to authorize future transactions upon this issuer's accounts. As such, the issuer will be using an optimized set of business rules that is based upon a holistic analysis of its accounts across all of the transaction handlers with whom the issuer is in collaboration, [69],
It would have been obvious to one with ordinary skill in the art before the effective filing date of the invention, to modify the method of Puerini, to include the method, as taught by Liu, in order to provide the user with tools to intelligently monitor and update fraud reduction strategies through modification to existing business rules, [5].
Regarding claims 19, 21-23, 25, 31-33, 35, the combination teaches
the checking-out takes place only when the determined checking-out time is reached and/or the checking-out criterion, plausibility of the billing data of the sequence of the purchase transactions, is met. (Puerini, [17]);
the customer is checked in by means of an identification unit of the customer, in particular by means of a mobile device, a chip card and/or a machine-readable code, such as a QR code, (Puerini, [18]);
the previously stored customer-specific and/or seller-specific checking-out base data, and/or the payment service provider data of the customer, (the user profile data store 917, Puerini, [57]);
the previously stored checking-out base data and/or the payment service provider data are provided, in particular retrieved by means of a customer ID, optionally from an external server, (Puerini, [91]);
the plausibility check of the billing data is carried out on the basis of predetermined criteria and in step d) an addition of the purchase revenues from those billing data for which the plausibility check was successful is performed automatically, (Liu, [98]);
after each purchase transaction a message which at least partially contains the billing data is sent to at least one mobile device, (a notification may be provided to the user identifying the item the user has picked from the inventory location, as in 610, [Puerini, 78]);
a mobile identification unit, in particular mobile device, on which an executable piece of customer software can be called up, a seller computer, on which an executable piece of seller software can be called up and which has an interface for transferring payment data to a payment service provider, wherein the customer software and the seller software, in particular if they are executed on the mobile device or the seller's computer or a server, (Puerini, Fig. 3);
the plausibility check prevents the checking out when the checking-out base data does not match one or more learned criteria, predicted criteria, customer-specific data, and/or vendor-specific data, (deny authorization, Liu, [98]);
the plausibility check prevents the checking out when the checking-out base data does not match the predetermined criteria, (deny authorization, Liu, [98]);
Claims 18, 20, 24, 27-30, 34 are rejected under 35 U.S.C. 103 as being unpatentable over Puerini and Liu combination and further in view of Buibas et. al. (U.S. Patent Publication No. 2021/0158430).
Regarding claims 18, 20, 24, 27-30, 34, the combination does not explicitly teach, however, Buibas teaches:
the checking-out time is determined on the basis of the checking-out base data and the billing data, (dwell time, [81], bill, [388]),
the plausibility of the billing data of the sequence of purchase transactions is checked as soon as the determined checking-out time is reached, or the plausibility of the billing data is checked as soon as billing data of a purchase transaction is received, wherein the checking-out is preferably only carried out when a sequence of purchase transactions with plausible accounting data that triggers the checking-out is identified based on the checking-out base data, (track the shopper continuously, [405-407],
repeatedly carrying out the following sub-steps in step b) for the individual purchase transactions of the sequence b) receiving the billing data comprising the purchase revenues of each individual purchase transaction, c) ascertaining the checking-out time in the form of an expected completion time for the sequence of purchase transactions on the basis of the billing data, [58-59],
determine the checking-out time on the basis of the billing data, a period of time is calculated after which no further purchase transaction is expected or the probability of a further purchase transaction falls below a predetermined threshold value, (confidence score is below a threshold value, [80]),
the checking-out time is updated after each purchase transaction, [241],
the checking-out base data is determined using machine learning methods, such as a classification tree or a regression method, (learning, [247, 279-280]).
an order for an individual purchase transaction is activated and booked only after expiry of an objection period, during which the customer can object and cancel the order using a mobile device, [381];
determining the checking-out time comprises using a machine learning model to determine the checking-out time, [202-203]).
It would have been obvious to one with ordinary skill in the art before the effective filing date of the invention, to modify the method of combination, to include the method, as taught by Buibas, in order to o enable accurate tracking of items, [29].
Response to Arguments
With respect to U.S.C. 101 rejection, applicant's arguments filed have been fully considered but they are not persuasive.
The claimed “plausibility check” even when based on predetermine criteria, fixed rules, or self-learning algorithms is recited at a high level of generality and constitutes evaluation and decision making that can be performed mentally. The claims do not recite any specific technological implementation of the algorithms.
Further, improving the accuracy of billing or detecting incorrect charges constitutes an improvement to a business process rather than to computer technology. The recitations that the steps are performed automatically in a seller unit without customer interaction merely reflects automation of the abstract idea using generic computing components and does not integrate the exception into a practical application. Accordingly, the 101 rejection is maintained.
With respect to U.S.C. 103 rejection, applicant’s arguments have been considered but are moot because the new ground of rejection does not rely on any reference applied in the prior rejection of record for any teaching or matter specifically challenged in the argument.
Conclusion
Applicant's amendment necessitated the new ground(s) of rejection presented in this Office action. Accordingly, THIS ACTION IS MADE FINAL. See MPEP § 706.07(a). Applicant is reminded of the extension of time policy as set forth in 37 CFR 1.136(a).
A shortened statutory period for reply to this final action is set to expire THREE MONTHS from the mailing date of this action. In the event a first reply is filed within TWO MONTHS of the mailing date of this final action and the advisory action is not mailed until after the end of the THREE-MONTH shortened statutory period, then the shortened statutory period will expire on the date the advisory action is mailed, and any nonprovisional extension fee (37 CFR 1.17(a)) pursuant to 37 CFR 1.136(a) will be calculated from the mailing date of the advisory action. In no event, however, will the statutory period for reply expire later than SIX MONTHS from the mailing date of this final action.
Any inquiry concerning this communication or earlier communications from the examiner should be directed to MILENA RACIC whose telephone number is (571)270-5933. The examiner can normally be reached M-F 7:30am-4pm EST.
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/MILENA RACIC/Patent Examiner, Art Unit 3627
/FLORIAN M ZEENDER/Supervisory Patent Examiner, Art Unit 3627