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 .
Prosecution Status
Applicant’s amendments filed 2/13/2026 have been received and reviewed. The status of the claims is as follows:
Claims 1-11, 13 are pending and rejected herein.
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.
1. Claims 1-13 are rejected under 35 U.S.C. 101 because the claimed invention is directed to a judicial exception (i.e., a law of nature, a natural phenomenon, or an abstract idea) without significantly more.
Claims 1-13 are directed to determining products to recommend to a customer, including facilitating interaction between customers and businesses, which is considered a commercial interaction. Commercial interactions fall within a subject matter grouping of abstract ideas which the Courts have considered ineligible (Certain methods of organizing human activity). The claims do not integrate the abstract idea into a practical application, and do not include additional elements that provide an inventive concept (are sufficient to amount to significantly more than the abstract idea).
Under step 1 of the Alice/Mayo framework, it must be considered whether the claims are directed to one of the four statutory classes of invention. In the instant case, claims 1-11 recites an apparatus comprising a processor. Claim 12 recites a system comprising an apparatus, which is interpreted to be a processor. Claim 13 recites a non-transitory computer-readable medium. Therefore, the claims are each directed to one of the four statutory categories of invention (apparatus, apparatus, manufacture).
Under step 2A of the Alice/Mayo framework, it must be considered whether the claims are “directed to” an abstract idea. That is, whether the claims recite an abstract idea and fail to integrate the abstract idea into a practical application.
Regarding independent claim 1, the claim sets forth a process in which product recommendations are determined for a customer, including through the facilitation of customer-to-business interaction, in the following limitations:
recognize a first in-store customer who visits a store;
acquire shopping basket information regarding a first product selected as a purchase target by the first in-store customer
extract other products that are purchased along with the first product by another in- store customer who visited the store in the past;
acquire position information in the store of each of the other products;
acquire a movement flow line of the first in-store customer;
determine a place not looked by the first in-store customer in the store based on the movement flow line of the first-in-store customer;
determine a recommended product to be recommended to the first in-store customer, from among the other products, that is displayed at the place not looked by the first in-store customer in the store; and
output an advertisement on the recommended product
.
The above-recited limitations establish a commercial interaction with a customer to make a product recommendation and between a customer and business to aid in the determination of the recommendation. This arrangement amounts to both a sales activity or behavior; and business relations. Such concepts have been considered ineligible certain methods of organizing human activity by the Courts (See MPEP 2106.04(a)).
Claim 1 does recite additional limitations:
a processor configured to
from a video imaged by a camera installed in the store
based on an RF tag attached to the first product;
to a terminal apparatus of the first in-store customer.
These additional elements merely amount to the general application of the abstract idea to a technological environment. The specification makes clear the general-purpose nature of the technological environment (see ¶14). Paragraph 92 indicates that while exemplary general purpose systems may be specific for descriptive purposes, any elements or combinations of elements capable of implementing the claimed invention are acceptable. That is, the technology used to implement the invention is not specific or integral to the claim.
Therefore, considered both individually and as an ordered combination, the additional elements do no more than generally link the use of the abstract idea to a particular technological environment or field of use. That is, given the generality with which the additional limitations are recited, the limitations do not implement the abstract idea with, or use the abstract idea in conjunction with, a particular machine or manufacture that is integral to the claim. Additionally, the claims do not reflect an improvement in the functioning of a computer, or an improvement to other technology or technical field, do not effect a transformation or reduction of a particular article to a different state or thing; and do not apply or use the abstract idea in some other meaningful way beyond generally linking the use of the abstract idea to a particular technological environment, such that the claim as a whole is more than a drafting effort designed to monopolize the abstract idea. Accordingly, the Examiner concludes that the claim fails to integrate the abstract idea into a practical application, and is therefore “directed to” the abstract idea.
Under step 2B of the Alice/Mayo framework, it must finally be considered whether the claim includes any additional element or combination of elements that provide an inventive concept (i.e., whether the additional element or elements are sufficient to amount to significantly more than the abstract idea). In the instant case, as noted above, the additional element merely amounts to a general link of the use of the abstract idea to a particular technological environment. Accordingly, the Examiner asserts that the additional elements, considered both individually, and as an ordered combination, do not provide an inventive concept, and the claim is ineligible for patent.
Independent Claims 12 and 13 are parallel in scope to claim 1 and ineligible for similar reasons.
Regarding Claims 2-11
Claims 2-11 set forth limitations that merely embellish the abstract idea of determining products to recommend to applying a learning model to determine the product recommendation. Such limitations do not integrate the abstract idea into a practical application, and do not provide an inventive concept. Accordingly, the claims do not confer eligibility on the claimed invention and are ineligible for similar reasons to claim 1.
Claim Rejections - 35 USC § 103
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 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.
2. Claims 1, 7, 9-10, 13 are rejected under 35 U.S.C. 103 as being unpatentable over Kawachi et al. (US 20200013105 A1, hereinafter Kawachi) in view of Greenberger et al. (US 20180075427 A1, hereinafter Greenberger).
Regarding Claim 1
Kawachi discloses an information processing apparatus comprising:
a processor (¶98) configured to:
specify, using information regarding a product selected as a purchase target by an in-store customer who visits a store and a movement flow line of the in-store customer in the store, a recommended product to be recommended to the in-store customer from among products displayed at a place not looked by the in-store customer in the store (¶¶24-33: products selected for recommendation based on exclusion areas determined from customer staying time to be places customer has seen).
extract other products that are purchased along with the first product by another in- store customer who visited the store in the past; (Kawachi: see at least ¶61)
acquire position information in the store of each of the other products (Kawachi: see at least ¶78, fig. 11: position of products to recommend)
acquire a movement flow line of the first in-store customer; (Kawachi: see at least ¶56)
determine a place not looked by the first in-store customer in the store based on the movement flow line of the first-in-store customer; (Kawachi: see at least (¶¶24-33, 39-40, 56: movement flow information of customer used to determine exclusion zones where a customer has seen; areas outside of exclusion zones are determined customer has not seen/looked).
determine a recommended product to be recommended to the first in-store customer, from among the other products, that is displayed at the place not looked by the first in-store customer in the store; (Kawachi: see at least ¶39-40: products within exclusion zones are excluded; products outside exclusion zones (i.e., products outside of places seen by customer) may be recommended)
output an advertisement on the recommended product to a terminal apparatus of the first in-store customer (Kawachi: see at least ¶73-78; fig. 11)
Kawachi does not explicitly disclose, but Greenberger teaches, in a similar environment:
recognize a first in-store customer who visits a store from a video imaged by a camera installed in the store; (Greenberger: see at least ¶24, claims 3, 10, 17)
acquire shopping basket information regarding a first product selected as a purchase target by the first in-store customer based on an RF tag attached to the first product; (Greenberger: see at least ¶12)
It would have been obvious to one of ordinary skill in the art at the time of filing to have modified the invention of Kawachi, with the features of Greenberger, since such a modification would have optimized customer checkout to overcome inconveniences such as a long wait at checkout (Greenberger: see at least ¶2-3).
Regarding Claims 12, 13
Claims 12 and 13 are substantially similar to claim 1 and are rejected on similar grounds.
Regarding Claim 7
Kawachi further discloses:
wherein the processor is configured to: determine the place not looked by the first in-store customer based on a staying time of the first in-store customer or the number of times of staying of the first in-store customer at a place where each product is displayed, acquired based on the movement flow line (Kawachi: see at least abstract, ¶29)
Regarding Claim 9
Kawachi further discloses:
wherein the processor is configured to: determine a plurality of the recommended products with different priorities to be recommended to the first in-store customer (Kawachi: see at least ¶47, 73, fig. 11)
Regarding Claim 10
Kawachi further discloses:
wherein the processor is configured to: give high priority to the recommended product displayed at a predetermined specific place in the store (Kawachi: see at least fig. 5, ¶70-71: prerequisite purchase area)
3. Claims 2-6 are rejected under 35 U.S.C. 103 as being unpatentable over Kawachi in view of Greenberger, as applied above, and further in view of Bradley et al. (US 11710169 B2, hereinafter Bradley).
Regarding Claim 2
While Kawachi in view of Greenberger discloses specifying product recommendations for customers based on shopping basket information and a place not looked, Kawachi in view of Greenberger does not explicitly disclose that such information is “input…to a learning model that learns a behavior in a case where another product is recommended to a customer who selects a certain product as a purchase target, and specify a recommended product that the in-store customer is predicted to show a predetermined behavior in a case of being recommended to the in-store customer, from among the products displayed at the place not looked by the in-store customer”. However, Bradley teaches that it is known to input customer current and past buying behavior in response to recommendations into a learning model in order to train the model to perform subsequent recommendations (see at least column 6, line 52 – column 7, line 23) in a similar in-store product recommendation environment. It would have been obvious to one of ordinary skill in the art at the time of filing to have modified the invention of Kawachi in view of Greenberger, with the input into, training of, and utilization of a learning model, as taught by Bradley, since such a modification would have provided a useful mechanism for automatically recommending an item to a customer while the customer is shopping in a retail store. (Bradley: col. 2, lines 28-46).
Regarding Claim 3
Kawachi in view of Greenberger does not explicitly disclose, but Bradley teaches in a similar environment:
wherein the learning model learns a relationship between information regarding the customer who selects the certain product as the purchase target and the behavior in a case where the another product is recommended, and the processor is configured to: further input information regarding the in-store customer to the learning model and determine the recommended product based on the information regarding the in-store customer (Bradley: see at least column 6, line 52 – column 7, line 23: customer purchases (i.e., response to product recommendations) used to train learning model and update recommendation algorithm)
It would have been obvious to one of ordinary skill in the art at the time of filing to have modified the invention of Kawachi in view of Greenberger, with the input into and training of a learning model, as taught by Bradley, since such a modification would have provided a useful mechanism for automatically recommending an item to a customer while the customer is shopping in a retail store. (Bradley: col. 2, lines 28-46)
Regarding Claim 4
Kawachi in view of Greenberger further discloses:
the processor is configured to: determine a product likely to be purchased by the in-store customer from among the products displayed at the place not looked by the in-store customer using the information regarding the product selected as the purchase target by the in-store customer and the movement flow line of the in-store customer, (Kawachi: ¶48-53: product purchase probability used to specify products to recommend)
Kawachi in view of Greenberger does not explicitly disclose, but Bradley teaches in a similar environment:
input information regarding the product likely to be purchased by the in-store customer as the products displayed at the place not looked by the in-store customer, to the learning model (Bradley: see at least column 6, line 52 – column 7, line 23)
It would have been obvious to one of ordinary skill in the art at the time of filing to have modified the invention of Kawachi in view of Greenberger, with the input into a learning model of products likely to be purchased by an in-store customer, as taught by Bradley, since such a modification would have provided a useful mechanism for automatically recommending an item to a customer while the customer is shopping in a retail store. (Bradley: col. 2, lines 28-46)
Regarding Claim 5
Kawachi in view of Greenberger discloses:
wherein the processor is configured to: determine the product likely to be purchased by the in-store customer further using information regarding sales of the products in the store (Kawachi: ¶55)
Regarding Claim 6
Kawachi in view of Greenberger does not explicitly disclose, but Bradley teaches in a similar environment:
wherein the processor is configured to: make the learning model learn a behavior result of the in-store customer in a case where the recommended product is recommended to the in-store customer, as training data (Bradley: see at least column 6, line 52 – column 7, line 23: customer purchases (i.e., response to product recommendations) used to train learning model and update recommendation algorithm)
It would have been obvious to one of ordinary skill in the art at the time of filing to have modified the invention of Kawachi in view of Greenberger, with the input into and training of a learning model, as taught by Bradley, since such a modification would have provided a useful mechanism for automatically recommending an item to a customer while the customer is shopping in a retail store. (Bradley: col. 2, lines 28-46)
4. Claims 8, 11 are rejected under 35 U.S.C. 103 as being unpatentable over Kawachi in view of Greenberger, as applied above, and further in view of Li et al. (US 20150112838 A1, hereinafter Li).
Regarding Claim 8
Kawachi in view of Greenberger does not explicitly disclose, but Li teaches in a similar environment:
wherein the processor is configured to: acquire a current position of the in-store customer in the store and determine, as the recommended product, a product displayed at a place near the current position of the in-store customer from among the other products displayed at the place not looked by the in-store customer (Li: see at least ¶45)
It would have been obvious to one of ordinary skill in the art at the time of filing to have modified the invention of Kawachi in view of Greenberger with the specifying a recommended product near the acquired current position of an in-store customer, as taught by Li, since such a modification would have significantly improved a user's in-store retail shopping experience by automatically providing relevant and timely product information. (Li: ¶10)
Regarding Claim 11
Kawachi in view of Greenberger does not explicitly disclose, but Li teaches in a similar environment:
wherein the processor is configured to: give high priority higher to the recommended product specified using information regarding a product selected later among the other products selected as the purchase target by the in-store customer (Li: see at least ¶45)
It would have been obvious to one of ordinary skill in the art at the time of filing to have modified the invention of Kawachi in view of Greenberger with prioritizing a recommended product based on a later selected target product, as taught by Li, since such a modification would have significantly improved a user's in-store retail shopping experience by automatically providing relevant and timely product information. (Li: ¶10)
Response to Arguments
Applicant’s arguments with respect to the 35 USC 101 rejection have been fully considered, but they are not persuasive. Applicant asserts:
Claim 1 does not merely recite a sales activity or business relationship. Rather, it is directed to a specific, machine-implemented process that integrates multiple physical sensing systems within a retail environment.
Importantly, the recommended product is not determined based solely on commercial logic or purchase correlation. Instead, the recommendation is constrained by spatial analysis derived from physical movement data within the store, including determination of a place not looked based on the customer's movement flow line and selection of products displayed at that specific location. Thus, Claim 1 is not directed to a fundamental economic practice or a method of organizing human activity. (Step 2A, Prong 1: NO)
Overall, Claim 1 uses integrated sensing data and spatial filtering to dynamically control the output of in-store advertising in a technologically specific manner within a physical retail environment. (Step 2A, Prong 2: YES)
In response, the Examiner asserts that thought the claims set forth some technical limitations, those limitations amount to the generic application of the abstract idea to a known technological environment. The claims merely set forth know devices used in a retail environment to identify a customer and products. These devices are not used beyond their normal and ordinary capacity, and therefore do not amount to significantly more than the abstract idea. Accordingly, the claims are held to be ineligible.
Applicant’s arguments with respect to the prior art rejections of the claims have been fully considered, but they are moot in light of the new grounds of rejection. The Examiner directs applicant to the rejection above, where additional citations within Kawachi have been provided to show its disclosure of certain newly-added claim elements, and Greenberger has been cited to cure Kawachi’s deficiencies.
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 MICHAEL A MISIASZEK whose telephone number is (571)272-6961. The examiner can normally be reached Monday-Thursday. 8:00 AM - 5:30 PM.
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If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Jeffrey Smith can be reached at 571272-6763. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
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/MICHAEL MISIASZEK/Primary Examiner, Art Unit 3688
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