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
Applicant’s submission filed 10/23/25 has been entered. Claims 1 -20 are presented for examination.
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.
Note: The following analysis is based on the Revised Guidance titled “2019 Revised Patent Subject Matter Eligibility Guidance (Vol. 84, No. 4).
STEP 1
Are the claims directed to a process, machine, manufacture or composition of matter?
Claims 1-20 are all directed to a statutory category (e.g., a process, machine, manufacture, or composition of matter). The answer is YES.
STEP 2A. Prong 1
The claims disclose the abstract idea of auditing purchases at a store.
Exemplary claim 1 recites the following abstract concepts that are found to include “abstract idea”:
“--receive purchase data corresponding to a plurality of items collected in the store and purchased by a customer in a sales transaction;
--assign a score to the sales transaction; --the score associated with a worker, the score comprising historical data of an accuracy of the worker;
--assign, based on at least the score, a quantity of items to be verified by a worker prior to the customer leaving the store, the quantity comprising a number and selected from any one of a plurality of numbers; and
-- output transaction data comprising at least a transaction identifier associated with the sales transaction and the quantity of the items to be verified by the worker; and
--receive the transaction data from the control circuit; and
--display instructions to the worker indicating the quantity of items of the sales transaction to be verified. ”
The remaining limitations are no more than computer elements (i.e., a control circuit, an electronic device, a point of sale mechanism) to be used as a tool to perform this abstract idea.
The recited limitations cover a process that, under its broadest reasonable interpretation, covers subject matter viewed as a certain method of organizing human activity with the additional recitation of generic computer components. For example, but for the “by control circuit ” the language, “receive, assign, output, display” in the context of this claim encompasses the user receiving transaction data, assigning a score to the data, assigning a quantity of items to be verified by a worker based on the score, output data and instructions to the worker indicating a quantity of items to verify.
The practice of receiving, assigning, outputting data, as well as displaying instructions based on score/rule is a commercial or legal interaction long prevalent in our system of commerce. The claims recite the idea of performing various conceptual steps generically resulting in determining the quantity of the items to be verified by the worker. As determined earlier, none of these steps recites specific technological implementation details, but instead get to this result by receiving, selecting and determining data. Thus, the claims are directed to a certain method of organizing human activity
STEP 2A, Prong 2
Are there additional elements or a combination of elements in the claim that apply, rely on, or use the judicial exception in a manner that imposes a meaningful limit on the judicial exception, such that it is more than a drafting effort designed to monopolize the exception?
The claim recites that a control circuit is used to perform steps; instructions are displayed on an electronic device; a point of sale mechanism is used to collect the data; purchase data is received from a machine learning model.
The control circuit, electronic device, point of sale mechanism, machine learning model, in the steps are recited at a high level of generality, i.e., as a generic processor performing a generic computer function of processing data (receiving, by a point of sales mechanism, purchase data). This generic processor limitation is no more than mere instructions to apply the exception using a generic computer component.
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.
The claim is directed to an abstract idea.
STEP 2B
The next issue is whether the claims provide an inventive concept because the additional elements recited in the claims provide significantly more than the recited judicial exception. Taking the claim elements separately, the function performed by the control circuit at each step of the process is purely conventional. 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 of using a control circuit to perform steps amounts to no more than mere instructions to apply the exception using a generic computer component. Mere instructions to apply an exception using a generic computer component cannot provide an inventive concept. The claim is not patent eligible.
Considered as an ordered combination, the computer components of Applicants' claims add nothing that is not already present when the steps are considered separately. The claimed invention does not focus on an improvement in computers as tools, but rather certain independently abstract ideas that use computers as tools. {Elec. Power, 830 F.3d at 1354). (Step 2B: NO).
There is no indication that indication that the control circuit is anything other than a generic, off-the-shelf computer component, and the Symantec, TLI, and OIP Techs. Court decisions cited in MPEP 2106.05(d)(II) indicate that mere collection or receipt of data over a network is a well‐understood, routine, conventional function when it is claimed in a merely generic manner (as it is here).
Independent claim 15 recites similar limitations as claim 1 and is therefore rejected under the same rationale.
The dependent claims when analyzed as a whole are held to be patent ineligible under 35 U.S.C. 101 because the additional recited limitations fail to establish that the claims are not directed to an abstract idea. The claims provide minimal technical structure or components for further consideration either individually or as ordered combinations with the independent claims. As such, additional recited limitations in the dependent claims only refine the identified abstract idea further. Further refinement of an abstract idea does not convert an abstract idea into something concrete.
For example, claim 11 recites executing a trained machine learning model. However, the model is recited at a high level of generality and is not sufficient to amount to significantly more than the judicial exception.
Accordingly, a conclusion that the collecting step is well-understood, routine, conventional activity is supported under Berkheimer Option 2.
See MPEP 2106.05(d)(II) The courts have recognized the following computer functions as well-understood, routine, and conventional functions when they are claimed in a merely generic manner (e.g., at a high level of generality) or as insignificant extra-solution activity.
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. Hoteis.com, L.P., 773 F.3d 1245, 1258, 113 USPQ2d 1097, 1106 (Fed. Cir. 2014) ("Unlike the claims in Ultramercial, the claims at issue here specify how interactions with the Internet are manipulated to yield a desired result-a result that overrides the routine and conventional sequence of events ordinarily triggered by the click of a hyperlink." (emphasis added));
iv. Storing and retrieving information in memory, Versata Dev. Group, Inc. v. SAP Am., Inc., 793 F.3d 1306,1334,115 USPQ2d 1681,1701 (Fed. Cir. 2015); OIP Techs., 788 F.3d at 1363,115 USPQ2d at 1092-93.
The claims are ineligible.
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 1-10,13, 15-18, 20 are rejected under 35 U.S.C. 103 as being unpatentable over Geffert et al. (US 20150127414 A1), in view of Swartz et al. (6672506 B2), in further view of Jones et al. (US 20170132560 A1).
Re-claims 1, 4, Geffert et al. teach --a system for auditing purchases at a store, the system comprising:
(see e.g. [0002]--The invention relates to systems and methods of selective auditing of mobile commerce baskets based on real-time behavior, profile information, event information, and/or other information in self-scan and other self-serve retail systems.)
-- a control circuit configured to:
--receive, […] purchase data corresponding to a plurality of items collected in the store and purchased by a customer in a sales transaction using a point of sale mechanism;
(see e.g. [0011] To facilitate these and other functions, the system may include a computer that receives scan information from a self-scan device that the consumer may use while shopping in a retail location. -- The scan information may identify an item, a price of the item, a location at which the item is located within a retail location, an identity of the retail location, an identity of the customer, and/or other information that describes a shopping trip.
[0032] Returning to FIG. 3, when the shopper has completed scanning items for purchase, terminal 100 is returned back to the scanner dispenser 2 and placed within an appropriate mating recess for communications with the scanner interface 10. When the terminal has implemented an on-board look-up table 116 and memory 114, then the tally list of items scanned is downloaded from the memory 114 to the host computer 4 for further processing.
--assign a score to the sales transaction;
(see e.g. [0014] Whatever the reason for a given item's increased level of risk, item risk profiling instructions may program the computer to determine that an audit is more likely to be triggered if the given item is scanned during a shopping process.
[0017] The shopping information may be used to assess a risk associated with the current shopping trip. For example, a long duration of time in a given aisle without a scan of an item from the given aisle may be deemed risky behavior that increases the likelihood of an audit.
0018] Each of the foregoing risk factors may be quantified and compared against a threshold value such that an audit may be triggered when the threshold value has been reached or exceeded by the quantified risk.
[0071] With respect to the various risk profiling instructions described herein, the terms "risky," "level of risk," and similar terms may refer to a quantifiable level of risk. ---. As such, the quantifiable level of risk may be higher or lower for different items, customers, retail locations, etc., and such riskiness may be used in audit decisions, as described below with respect to audit decision instructions 212.
[0075] Other information described herein may similarly be quantified to a level of risk. In other instances, a user such as a retail manager may configure the quantifiable levels of risk with the duration of time and/or other risk-indicating information described herein.
[0080] In some implementations, the determined level of risk may be converted to a score that is added to the corresponding customer's overall score, which can be used to determine whether to audit the customer,
--a user interface operable on an electronic device associated with the worker, wherein the worker is proximate an exit of the store, wherein the user interface is configured to: --receive the transaction data from the control circuit; and --display instructions to the worker indicating the quantity of items of the sales transaction to be verified.
(see e.g. [0104] Asset protection application 130 may determine a quantifiable risk associated with a scanned item, the customer, and/or the retail location. Based on the risk, asset protection application may cause an audit to occur by communicating an audit flag to an audit process, which may include a device used by asset protection personnel on site at the retail location.
[0020] Alert instructions may program the computer to communicate one or more messages to audit personnel (e.g., those who will conduct the audit), asset protection personnel (e.g., security), and/or others. The messages may be communicated via Short Message Service text message, email, voice, checkout terminal, and/or other communication channels. The messages may relate to the audit decision, and may include instructions such as an audit flag that causes an audit to be initiated, instructions to investigate certain things such as whether a disguise item is being used to hide other items)
(as in Geffert et al., Swartz et al. also teach --assign a score to the sales transaction;
(see e.g. [0106] The objective of this auditing policy it to select a probability of performing an audit to minimize the average overall loss. Then once that probability is calculated an audit is performed with that probability.)
and update the purchase data according to a verification of the sales transaction.
[0027] FIG. 4 illustrates a process of making an audit decision based on item profile information that describes a scanned item, according to an implementation of the invention.
[0032] For example, system 100 may prevent the checkout process from occurring and/or communicate an alert to personnel that such an audit should be undertaken, at which time the personnel may perform the audit.
[0056] Item risk profiling instructions 204 may program processor 120 to derive item profile information from observed audit histories, input by users (e.g., retail managers), and/or other sources of item profile information. For example, the propensity of a given item to be involved in a scan error may be determined based on observations that the item was previously associated with a mobile commerce basket that was audited and included a scan error.
The Examiner notes that the item risk profile is built on previous audit information, which is stored in the system.
Geffert et al. do not explicitly teach the following limitations as claimed.
However, Swartz et al. teach
--assign, based on at least the score, a quantity of items to be verified by a worker prior to the customer leaving the store, the quantity comprising a number and selected from any one of a plurality of numbers; and
(see e.g. [0018] performing a statistical determination of how many items of the selected items to check in a shopper's basket;
[0011] After a determination whether a shopper should be audited and, if so, how many items should be selected for audit,.
[0041] After the host computer 4 has used the security criteria as described above in order to ascertain, via the security determination logic means 216, the specific number of items to check for scan accuracy by the cashier or security guard, it proceeds to determine if this shopper is to be re-scanned (audited) or not, and if so, which types of items the cashier or security guard should look for in selecting the items to check.)
-- output transaction data comprising at least a transaction identifier associated with the sales transaction and the quantity of the items to be verified by the worker; and
(see e.g. [0007] -- means for compiling a list of items scanned by said customer, ---said tally list being supplied by a self-checkout device after said self-checkout device is returned to a device containment slot after being used by a shopper, said tally list further comprising a bar code encoded with said items scanned by said shopper, a unique identification record associated with said shopper, and the number of items scanned by said shopper.)
-- the system of claim 1, wherein the instructions displayed to the worker do not specify particular items of the plurality of items to verify.
(see e.g. [0018] In an alternate embodiment, the system may advise the cashier or security guard as to the number of items to check in step J without specifying which items to check.)
Therefore, it would have been obvious to a person of ordinary skill in the art, before the effective filing date of the claimed invention, to modify Geffert et al., and include the steps cited, as taught by Swartz et al., in order to determine whether a given shopper or customer is to be audited on a given shopping trip based upon obtaining a minimum checkout loss for such customer thereby providing an audit policy which is not too intrusive to customers or shoppers, but which is a significant deterrent to theft and unintentional errors. (see e.g. [0120]).
Geffert et al., in view of Swartz et al., do not explicitly teach the following limitations as claimed.
However, Jones et al. teach
--receive, from a machine-learning model, purchase data […]
(see e.g. [0033] In some embodiments, the control unit 210 may include smart logic (e.g., learning function)
[0024] Optionally, instead of receiving information regarding the products 190 from a separate scanner such as the scanning device 130, the control unit 210 may also be electrically coupled to a sensor such as a reader configured to detect and/or read information on the identifying indicia (e.g., a label) 192 located on the products 190 when the electronic inventory management device 120 is placed in direct proximity to a product 190. Such an optional reader may be a radio frequency identification (RFID) reader, an optical reader, a barcode reader, or the like.
[0023] The control unit 210 of the electronic inventory management device 120 is also electrically coupled via a connection 235 to an input/output 240 that can receive signals from and send signals (via a wired or wireless connection) to (e.g., commands, inventory database information), for example, devices local to the retail sales facility 110, or one or more servers remote to the retail sales facility 110.
Note: Control circuit 210 has smart logic/learning function and communicates retail information to other devices.
--the score associated with a worker, the score comprising historical data of an accuracy of the worker;
(see e.g. [0046] In the exemplary embodiment of FIG. 4, the target ratio (i.e., predetermined threshold of worker accuracy during a preceding bin audit) is 95%.
[0037] In the exemplary method 400 of FIG. 4, the processor control unit 210 of the electronic inventory management device 120 is programmed to analyze the following four exemplary inventory management factors to arrive at a decision of whether to audit the bin 150 or not: amount of time (days) since the last audit of the bin 150; user accuracy percentage of the worker at the retail sales facility 110 during a preceding audit of the bin 150; a total number of products 190 stored in the bin 150; and number of transactions (i.e., binning of products 190 into the bin or picking of products 190 from the bin) that have occurred in the bin 190.
[0033] For example, if the control unit 210 of the electronic inventory management device 120 receives an indication that worker accuracy was significantly higher or lower during the preceding audit of a bin 150, the control unit 210 may adjust the bin audit management factor relating to worker accuracy accordingly. As such, the control unit 210 is configured to set bin audit management factor thresholds based on updated real-time information, thereby increasing the accuracy of the preset thresholds of bin audit management factors for the bins 150 at specific retail sales facilities 110.
[0053] In the example above, if the probability to audit the bin 150 were calculated by the control unit 210 to be not 50%, but higher than the threshold value of 75%, the control unit 210 would arrive at a decision (and transmit an appropriate notification to the scanning device 130 of the user) that the bin 150 should be audited
Jones et al. also teach --assign a score to the sales transaction,
(see e.g. [0041] Probability to audit a bin.
[0052] In one specific example, the control unit 210 of the electronic inventory management device 120 is programmed to have a threshold of 75%, such that the bin audit management factors would lean heavily toward user accuracy and number of transaction, which would reduce the overall number of times a bin 150 was audited. In such a situation, the control unit 210 of the electronic inventory management device 120 is programmed to calculate that, the above equation to determine a probability to audit the bin 150 (i.e., P.sub.Audit=αf(Skus)+βf(A)+γf(T)+δf(R)), α would be low and have a weight of 10%, β would have a weight of 40%, γ would be 10%, and δ would be 40%.)
-- output transaction data comprising at least a transaction identifier associated with the sales transaction and the quantity of the items to be verified by the worker
(see e.g. [0034] In still other embodiments, the control unit 210 may generate an indication to the worker at the retail sales facility 110 that the obtained bin audit management factors support the auditing of the bin 150 in response to a determination that three or more threshold values for the obtained bin audit management factors meet the predetermined threshold value that supports the auditing of the at least one bin. In still other embodiments, the control unit 210 may generate an indication to the worker at the retail sales facility 110 that the obtained bin audit management factors support the auditing of the bin 150 in response to a determination that all of the threshold values for the obtained bin audit management factors meet the predetermined threshold value that supports the auditing of the at least one bin.)
Therefore, it would have been obvious to a person of ordinary skill in the art, before the effective filing date of the claimed invention, to modify Geffert et al., in view of Swartz et al., and include the steps cited, as taught by Jones et al., in order to restrict audits in certain appropriate situations, and also control the number of audits at retail sales facilities (see e.g. [0054])
Re-claim 2, Geffert et al. do not explicitly teach the following limitations as claimed.
However, Swartz et al. teach the system of claim 1, wherein the user interface is further configured to: obtain a transaction identifier associated with the sales transaction from a receipt presented to the worker by the customer; and retrieve the quantity of items of the sales transaction from the transaction data having a matching transaction identifier.
(see e.g. [0050] The cashier or security guard reads from the display at the POS terminal the list of items to check (or from a printed version of the list) and selects the items for checking. The cashier scans the bar code of each item, and if any item scanned is not on the tally list, the cashier or security guard is alerted that the shopper has made an error in scanning. In this case, the retail establishment may opt to re-scan the entire shopping cart, may simply add the item to the tally list, or may take some other act it deems appropriate for the situation. Data indicative of the mis-scanned item is then transmitted from the POS terminal back to the host computer and stored in its security criteria memory 214 for subsequent processing and subsequent criteria determination.)
Therefore, it would have been obvious to a person of ordinary skill in the art, before the effective filing date of the claimed invention, to modify Geffert et al., and include the steps cited, as taught by Swartz et al., for comparing the identity of the items (see e.g. [0010]).
Re-claim 3, Geffert et al. teach --the system of claim 1, further comprising a shopping container configured to store the plurality of items collected and purchased by the customer in the store, wherein the score is associated with the shopping container.
(see e.g. [0037] In this manner, system 100 may predict a frequency of selective audits and/or the identity of mobile commerce baskets that would likely be audited given the audit parameters and/or values.
[0053] For example, the item profile information may indicate that the item is commonly used as a disguise item to hide other items that were not scanned but placed in the mobile commerce basket.)
Re-claim 5, Geffert et al. teach the system of claim 1, wherein the point of sale mechanism comprises at least one of a self-checkout station, a cashier assisted checkout station, and a mobile checkout application for use with an electronic device of the customer.
(see e.g. [0043] Self-scan device 156 may include a consumer's mobile device programmed with a self-scan mobile application used to scan items, a self-scan device provided by a retailer, and/or other device. Computer 110 may obtain the scan information to identify items that have been scanned by the consumer during a current shopping trip.
[0045] In other instances, the customer may pay for the scanned items at self-checkout terminal 158. Regardless of how a consumer may checkout, system 100 may selectively cause an audit to occur.)
[0048] For example, client device 152, self-scan device 156, self-checkout terminal 158, and/or other components may each individually and/or together perform at least some of the functions and operations of asset protection application 130.)
Re-claim 6, Geffert et al. teach the system of claim 1, wherein the control circuit is further configured to output transaction data for each of a plurality of sales transactions to the user interface, wherein the user interface is configured to receive and store the transaction data for each of the plurality of sales transactions.
(see e.g. [0104] Asset protection application 130 may determine a quantifiable risk associated with a scanned item, the customer, and/or the retail location. Based on the risk, asset protection application may cause an audit to occur by communicating an audit flag to an audit process, which may include a device used by asset protection personnel on site at the retail location.
[0020] Alert instructions may program the computer to communicate one or more messages to audit personnel (e.g., those who will conduct the audit), asset protection personnel (e.g., security), and/or others. The messages may be communicated via Short Message Service text message, email, voice, checkout terminal, and/or other communication channels. The messages may relate to the audit decision, and may include instructions such as an audit flag that causes an audit to be initiated, instructions to investigate certain things such as whether a disguise item is being used to hide other items).
Re-claim 7, Geffert et al. teach --the system of claim 1, wherein the control circuit is configured to assign the score based on at least one or more of: a composition of the plurality of items, one or more attributes associated with the store, and one or more attributes associated with the worker.
(see e.g. [0034 [0064] ] In some implementations, system 100 may make the audit decision based on one or more risk factors that, when taken alone or in combination, exceed an audit threshold. The risk factors may relate to an item risk, a customer risk, a retail location risk, and/or other type of risk that indicates a probability that a scan error has or will occur in a given mobile commerce basket).
[0068] A given retail location may in a geographic area that has a high crime rate or otherwise is associated with high rates of scan errors. As such, retail risk profiling instructions 208 may determine that a particular retail location is risky based on the geographic area at which the retail location is located.)
Re-claims 8, 9, 10, Geffert et al. do not explicitly teach the following limitations as claimed.
However, Swartz et al. teach -- the system of claim 1, wherein the score is based at least on a determination that a threshold portion of the plurality of items belongs to a category of items. --The system of claim 8, wherein each category of categories of items is associated with a corresponding quantity of items to be verified by the worker prior to the customer leaving the store.
(see e.g. abstract --A statistical basis for use in a self-scanning checkout system determines how many items to check in a shopper's shopping cart for incorrect or missing scans as well as which particular or types of items to check to determine if they were properly scanned, if the shopper is determined to be audited.
[0049] The shopper may then proceed to an appropriate POS terminal 6, which is manned by a cashier for tender of payment and security checking of the items selected for purchase.
[0041] After the host computer 4 has used the security criteria as described above in order to ascertain, via the security determination logic means 216, the specific number of items to check for scan accuracy by the cashier or security guard, it proceeds to determine if this shopper is to be re-scanned (audited) or not, and if so, which types of items the cashier or security guard should look for in selecting the items to check.)
10. The system of claim 1, wherein the control circuit is configured to assign the quantity of items to be verified based on at least the score and at least one of a time of day, a day of week, a store, and an amount of customer traffic in the store.
Swartz et al. (see e.g. [0041] Factors to consider in determining which items to look for from among the shoppers purchases include the following: [0045] 4. Time of day/day of week/date of year: Statistical analysis of pilferage of certain types of items as it may be linked to the time of day, day of week or date of year may be factored into the determination.
Therefore, it would have been obvious to a person of ordinary skill in the art, before the effective filing date of the claimed invention, to modify Geffert et al., and include the steps cited, as taught by Swartz et al., in order to determine which types of items to look for in selecting the items to check (see e.g. [0010]).
Re-claim 13, Geffert et al., in view of Swartz et al., do not explicitly teach the limitations as claimed.
However, Jones et al. teach the system of claim 1, wherein the score is based at least on one or more attributes associated with the worker, and wherein the one or more attributes associated with the worker is based at least on whether the worker has erroneously flagged one or more sales transactions in one or more previous verifications as including at least one unpaid item.
(see e.g. abstract ---Based on whether the value of one or more of the bin audit management factors meets a predetermined threshold value that supports the auditing of a bin, an indication to a worker at the retail sales facility is generated as to whether that bin is to be audited or not.
[0019] By way of example, information regarding worker accuracy during previous bin audits may be received by the electronic inventory management device 120 from a server located at a product distribution center or a server at a regional data center.)
[0039] he inventory management database 140, the control unit 210 of the electronic inventory management device 120 may generate an indication to the worker at the retail sales facility 110 not to audit the bin but to take current count of the products 120 (step 470). In some embodiments, the indication to the worker of whether to audit a bin 150 may be in the form of a list of bins 150 to be audited, and the bins 150 determined (e.g., by the control unit 210 of the electronic inventory management device 120) to not be audited do not appear on such a list.
Therefore, it would have been obvious to a person of ordinary skill in the art, before the effective filing date of the claimed invention, to modify Geffert et al., in view of Swartz et al., and substitute the audit of the bins for the audit of the transaction, as taught by Jones et al., in order to determine whether the bin 150 is to be audited by a worker at the retail sales facility (see e.g. [0027]).
Additionally, it is noted that KSR forecloses the argument that a specific teaching, suggestion, or motivation is required to support a finding of obviousness. Under KSR, a claim would have been obvious if the claimed elements were known in the prior art and one skilled in the art could have combined the elements as claimed by known methods with no change in their respective functions, and the combination would have yielded nothing more than predictable results to one of ordinary skill in the art at the time of the invention. Furthermore, under KSR, a claim would have been obvious if a particular known technique was recognized as part of the ordinary capabilities of one skilled in the art. Thus the claimed subject matter likely would have been obvious under KSR.
Claim 15 recites similar limitations as claim 1 and is therefore rejected under the same arts and rationale.
Claim 16 recites similar limitations as claim 8 and is therefore rejected under the same arts and rationale.
Claim 17 recites similar limitations as claim 9 and is therefore rejected under the same arts and rationale.
Claim 18 recites similar limitations as claim 10 and is therefore rejected under the same arts and rationale.
Claim 20 recites similar limitations as claim 13 and is therefore rejected under the same arts and rationale.
Claims 11, 12, 19 are rejected under 35 U.S.C. 103 as being unpatentable over Geffert et al. (US 20150127414 A1), in view of Swartz et al. (6672506 B2), in view of Jones et al. (US 20170132560 A1), and further in view of Cifarelli et al. (US 20220188827 A1)
Re-claim 11, Geffert et al., in view of Swartz et al., in view of Jones et al., do not explicitly teach the limitations as claimed.
However, Cifarelli et al. teach --the system of claim 1, wherein the control circuit is configured to assign the score by executing a trained machine learning model.
[0013] As fraud is detected, the features for the transaction are provided to a continuously trained machine-learning model/algorithm so that the machine-learning algorithm can learn to accurately produce fraud scores and/or identify frauds occurring in real time.
Therefore, it would have been obvious to a person of ordinary skill in the art, before the effective filing date of the claimed invention, to modify Geffert et al., in view of Swartz et al., in view of Jones et al., and include the steps cited, as taught by Cifarelli et al so that the machine-learning algorithm can learn to accurately produce fraud scores and/or identify frauds occurring in real time (see e.g. [0013]).
Re-claim 12, Geffert et al. do not explicitly teach the limitations as claimed.
However, Swartz et al. anticipate the system of claim 11, wherein the trained machine learning model is configured to automatically assess fairness in the assignment of the score through an analysis of the assigned score and corresponding demographic types associated with customers in the store.
[0017] In FIG. 1, the present methodology determines how many items to check for a given shopper transaction as well as which particular items to check for that shopper, using the following input criteria which may be considered, alone or in varying combinations: store location and demographics B (check more items in stores located in areas with a high risk of pilferage);
[0087] There are many possible models that could be used to represent this probabilistically.
[0118] Essentially, a Neural Network is used to learn patterns and relationships in data. The data here can be information about the customer and the output can be whether or not the customer is to be audited.)
NOTE: Assessing fairness based on demography is subject to interpretation. Swartz et al. teach checking more items in demographic areas with high risk of pilferage, which can be considered a fair assessment.
Therefore, it would have been obvious to a person of ordinary skill in the art, before the effective filing date of the claimed invention, to modify Geffert et al., and include the steps cited, as taught by Swartz et al., in order to develop a better auditing policy by using rules that model the real world more completely. (see e.g. [0054]).
Claim 19 recites similar limitations as claim 11 and is therefore rejected under the same arts and rationale.
Claim 14 is rejected under 35 U.S.C. 103 as being unpatentable over Geffert et al. (US 20150127414 A1), in view of Swartz et al. (6672506 B2), in further view of Jones et al. (US 20170132560 A1), In view of Official Notice (as evidenced by Swartz et al. and HAYASHI et al. (US 20230091825 A1)).
Re-claim 14, Geffert et al., in view of Swartz et al., in view of Jones et al., do not explicitly teach the system of claim 1, wherein the user interface is configured to: receive scan data corresponding to each of the quantity of items from a scanner of the electronic device; determine whether the scan data of each of the items matches ones of the plurality of items purchased by the customer in the sales transaction; output and display, in an event the scan data of the quantity of items matches with the plurality of items, a first notification to the worker via the user interface that the sales transaction is verified; and output and display, in an event the scan data of at least one item does not match the plurality of items, a second notification to the worker via the user interface that an item has not been paid for by the customer.
However, Official Notice is taken that it is old and well known that during an exit audit, workers can be notified multiple times on the status of the audit and instructed to perform certain actions or no action at all. For example Swartz et al. teach communicating audit actions to the cashier or security guard based on the audit results (No Audit, Limited Audit (e.g. check 10% of items), Full Audit (4)). See e.g. Swartz et al. (see e.g. [0050], [0080. 0081].
HAYASHI et al. teach displaying a first notification and a second notification on the attendant’s terminal notifying the attendant of a status of a target commodity. (see e.g. [0120], [0135], 0145].
Sending multiple notification to the worker based on the action to be taken is old and well known.
Response to Arguments
Applicant’s arguments with respect to claims 1-20 have been considered but are moot.
Applicant’s argument:
Because the present invention leverages worker accuracy attributes to update an improved machine-learning model, the present invention reduces the impact on computing hardware and allows faster processing to occur for a given hardware configuration.
Examiner’s response:
The Examiner disagrees. The improvements to the current invention are directed to the abstract idea itself. The claims do not improve the machine learning model. The quality of the data is improved, but not the way the model functions.
Relying on a computer to perform routine tasks more quickly or more accurately is insufficient to render a claim patent eligible. See Alice, (use of a computer to create electronic records, track multiple transactions, and issue simultaneous instructions" is not an inventive concept);
Applicant’s argument:
However, nothing in the cited portions of Geffert appears to disclose that the score is "associated with a worker, the score comprising historical data of an accuracy of the worker." Swartz appears silent on the features. Therefore, amended claim 1 is patentable over Geffert and Swartz. -- . Jones does not cure and is not cited to cure the critical deficiencies of Geffert and Swartz, discussed above.
Examiner’s response:
The argued limitation is taught by Jones et al..
Jones teaches “calculating the probability to audit a bin and arriving at a decision of whether a bin is to be audited can include an accuracy percentage of a worker at the retail sales facility during a preceding audit of the bin. (see e.g. [0011], [0052]).
Please note: Applicant has not properly traversed the Official Notice. Therefore, the common knowledge or well-known in the art statement above is taken to be admitted prior art and the Official Notice is maintained and is final. Please see MPEP 2144.03.
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure. A) Dheeraj (US 20230027855 A1) -- PREDICTIVE RESCAN SERVICE
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/LUNA CHAMPAGNE/Primary Examiner, Art Unit 3627 January 29, 2026