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 .
This communication is in response to Application No. 18/962736, filed on 11/27/2024. Claims 1-20 are currently pending and have been examined. Claims 1-20 have been rejected as 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.
The claims 1-20 are rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more.
Step 1: The claims 1-8 are a method, 9-16 a computer readable medium, and 17-20 are a system. Thus, each independent claim, on its face, is directed to one of the statutory categories of 35 U.S.C. §101.
Step 2A Prong 1: The independent claims (1, 9 and 17, taking claim 1 as a representative claim) recite:
receiving a product ordering request from a user via a computing device,
wherein the request comprises information associated with a product;
upon receiving the request:
obtaining a set of data from a database, wherein the computing device and the database are connected to each other over a network;
initiating monitor of actions of the user with respect to the product in real-time;
performing preprocessing on the set of data to obtain preprocessed data;
determining, based on the preprocessed data, a preference score of the user for the product;
analyzing the actions to obtain an analysis result;
inferring, based on the analysis result, a current preference of the user related to the product;
updating, based on the current preference, the preference score to obtain an updated preference score of the user;
generating, based on the updated preference score, a set of potential product recommendations for the user;
generating, using a diffusion optimized model guided by trajectory alignment, a set of optimized product recommendations for the user based on the set of potential product recommendations;
determining, using a conformal prediction model, a reliability of each of the set of optimized product recommendations based on each optimized product recommendation’s confidence interval;
ranking each of the set of optimized product recommendations based on confidence intervals to generate a ranked list of product recommendations;
initiating, via a graphical user interface (GUI) of a visualizer, display of the ranked list to the user along with each optimized product recommendation’s confidence interval;
after displaying the ranked list:
making a determination that a negative feedback is received, over the GUI, from the user, wherein the negative feedback indicates that the ranked list does not satisfy expectations of the user related to the product;
updating, based on the determination, the ranked list to obtain an updated ranked list of product recommendations; and
initiating, via the GUI, display of the updated ranked list to the user.
These limitations, except for the italicized portions, under their broadest reasonable interpretations, recite certain methods of organizing human activity for managing personal behavior or relationships or interactions between people (including social activities, teaching, and following rules or instructions) as well as commercial or legal interactions (including agreements in the form of contracts; legal obligations; advertising, marketing or sales activities or behaviors; business relations). The claimed invention recites steps for providing an end user with a set of ranked product recommendations and updating the list based on feedback from the end user. The steps under its broadest reasonable interpretation specifically fall under sales activities. The Examiner notes that although the claim limitations are summarized, the analysis regarding subject matter eligibility considers the entirety of the claim and all of the claim elements individually, as a whole, and in ordered combination.
Prong 2: This judicial exception is not integrated into a practical application. In particular, the claims recite the additional elements of:
A non-transitory computer readable medium comprising computer readable program code, which when executed by a computer processor enables the computer processor to perform a method for managing recommendation generation, the method comprising: (claim 9)
A system for managing recommendation generation, the system comprising: a processor comprising circuitry; memory comprising instructions, which when executed perform a method, the method comprising: (claim 17)
receiving a product ordering request from a user via a computing device,
obtaining a set of data from a database, wherein the computing device and the database are connected to each other over a network;
initiating, via a graphical user interface (GUI) of a visualizer, display of the ranked list to the user along with each optimized product recommendation’s confidence interval;
initiating, via the GUI, display of the updated ranked list to the user.
The additional elements of emphasized above are recited at a high-level of generality (i.e., as a generic processor performing a generic computer function of processing data) such that it amounts no more than mere instructions to apply the exception using a generic computer component. The limitations not impose any meaningful limits on practicing the abstract idea, and therefore do not integrate the abstract idea into a practical application – MPEP 2106.05(f).
Accordingly, these additional elements when considered individually or as a whole do not integrate the abstract idea into a practical application because they do not impose any meaningful limits on practicing the abstract idea. The independent claims are directed to an abstract idea.
Step 2B: The claims do not include additional elements that are sufficient to amount to significantly more than the judicial exception. As discussed with respect to Step 2A Prong two, the additional elements in the claims amount to no more than mere instructions to apply the judicial exception using a generic computer component.
Even when considered as an ordered combination, the additional elements of claim 1, 9, and 17 do not add anything that is not already present when they are considered individually. Therefore, under Step 2B, there are no meaningful limitations in claims 1, 9, and 17 that transform the judicial exception into a patent eligible application such that the claims amount to significantly more than the judicial exception itself (see MPEP 2106.05).
As such, independent claims 1, 9, and 17 are ineligible.
Dependent claims 2-8, 10-16, and 18-20 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 the same abstract idea of Independent Claims 1, 9 and 17 without significantly more.
Claim 2 recites wherein a confidence interval of an optimized product recommendation of the set of optimized product recommendations specifies a statistical measure of a reliability of the optimized product recommendation. The limitation merely further limits the abstract idea and does not integrate the judicial exception into a practical application.
Claim 3 recites wherein the actions of the user comprise viewing information related to a second product on a website, adding the second product to a quote, removing a third product from the quote, and initiating a technical support call for the product. The limitation merely further limits the abstract idea and does not integrate the judicial exception into a practical application.
Claim 4 recites wherein the set of data comprises historical sales data of the product, historical user data related to the product, information associated with the product, and profitability information associated with the product. The limitation merely further limits the abstract idea and does not integrate the judicial exception into a practical application.
Claim 5 recites wherein the preprocessing comprises performing feature extraction to extract features from the set of data to be used while generating the set of potential product recommendations. The limitation merely further limits the abstract idea and does not integrate the judicial exception into a practical application.
Claim 6 recites wherein the inferring comprises assigning weights to different types of user actions to infer the current preference of the user. The limitation merely further limits the abstract idea and does not integrate the judicial exception into a practical application.
Claim 7 recites wherein the updated preference score indicates an increased product ordering tendency of the user to order to product, and wherein the product is a second computing device. The limitation merely further limits the abstract idea and does not integrate the judicial exception into a practical application.
Claim 8 recites wherein each of the set of optimized product recommendations is further generated based on a margin maximization objective of a related organization that manufactures the product. The limitation merely further limits the abstract idea and does not integrate the judicial exception into a practical application.
Claims 10-16 and 18-20 recites parallel claim language and are therefore rejected for the same reason above.
For these reasons claims 1-20 are rejected under 35 USC 101.
Subject Matter Free of Prior Art
Claims 1, 9 and 17 are determined to be free of prior art, however the claims remain rejected under 35 USC 101, as set forth above. All dependent claims are also free of prior art by virtue of dependency, but remain rejected under 35 USC 101.
Taking amended claim 1 as a representative claim, the claims are determined to be free of prior art for the reasons set forth below.
Although individually the claimed features could be taught, any combination of references would teach the claimed limitations using a piecemeal analysis, since references would only be combined and deemed obvious based on knowledge gleaned from the applicant's disclosure. Such a reconstruction is improper (i.e., hindsight reasoning). See In re McLaughlin, 443 F.2d 1392, 170 USPQ 209 (CCPA 1971). The examiner emphasizes that it is the interrelationship of the limitations that renders these claims free of the prior art/additional art.
The closest prior art of record is detailed below:
SANTHANAM (US 20160300144) is the closest art of record. The reference discloses generating personalized recommendations from real time data and batch date from user actions on websites. The data is preprocessed and can be merged for analysis according to business rules. [see 0559, 0061, 0029, Figure 3, 0031, 0036,] Further, the data can be filtered in order to provide a recommendation based on what the end user might prefer using machine learning techniques [ 0056 and 0043]. However, the reference does not determine a preference score, use a diffusion optimized model guided by trajectory alignment, use conformal prediction modeling, rank or update ranking of recommendations based on user feedback, as required by the claimed invention.
Jain (US 12380115) discloses displaying final recommendations to an end user in a ranked list of results along with confidence scores (see Col. 5 lines 15-30). Further, Jain discloses providing a feedback option to the end user that is used to re-train the models to improve the recommendations provided in the next iteration (see Col. 5 lines 45-65). However, the reference does not determine a preference score, use a diffusion optimized model guided by trajectory alignment, or use conformal prediction modeling as required by the claimed invention.
Cai (US 20220374962) discloses determining a dynamic preference score and a long term preference score of a user and based on these scores, presenting recommended items to the end user (see Figure 1 and [0073]). However, the reference does not use a diffusion optimized model guided by trajectory alignment, use conformal prediction modeling, rank or update ranking of recommendations based on user feedback, as required by the claimed invention.
Gong (US 20240403728) discloses using conformal prediction techniques for building reliable confidence intervals that include the true value with a specific confidence level (see [0023]). However, the reference does not determine a preference score, use a diffusion optimized model guided by trajectory alignment, or rank or update ranking of recommendations based on user feedback, as required by the claimed invention.
“Aligning Optimization Trajectories with Diffusion Models for Constrained Design Generation” discloses to address these challenges, we introduce Diffusion Optimization Models (DOM) and Trajectory Alignment (TA), a learning framework that demonstrates the efficacy of aligning the sampling trajectory of diffusion models with the optimization trajectory derived from traditional physics-based methods. This alignment ensures that the sampling process remains grounded in the underlying physical principles (see abstract). However, the reference does not determine a preference score, use conformal prediction modeling, rank or update ranking of recommendations based on user feedback, as required by the claimed invention.
While individually the limitations could be taught by piecing together a plurality of references directed to the individual determinations, it was found that no references alone or in combination, neither anticipates, reasonable teaches, nor renders obvious the noted features of Applicant’s invention without improver hindsight reconstruction of applicant’s own invention.
For these reasons claims 1-20 are free of prior art.
Conclusion
Any inquiry concerning this communication or earlier communications from the examiner should be directed to VICTORIA E. FRUNZI whose telephone number is (571)270-1031. The examiner can normally be reached Monday- Friday 7-4 (EST).
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If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Marissa Thein can be reached at (571) 272-6764. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
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VICTORIA E. FRUNZI
Primary Examiner
Art Unit TC 3689
/VICTORIA E. FRUNZI/Primary Examiner, Art Unit 3689 6/3/2026
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