Prosecution Insights
Last updated: April 19, 2026
Application No. 18/128,353

AUTOMATICALLY GENERATED PRODUCT RECOMMENDATIONS BASED UPON QUESTIONS AND ANSWERS

Final Rejection §101
Filed
Mar 30, 2023
Examiner
AIRAPETIAN, MILA
Art Unit
3688
Tech Center
3600 — Transportation & Electronic Commerce
Assignee
Amazon Technologies, Inc.
OA Round
2 (Final)
73%
Grant Probability
Favorable
3-4
OA Rounds
2y 11m
To Grant
88%
With Interview

Examiner Intelligence

Grants 73% — above average
73%
Career Allow Rate
699 granted / 959 resolved
+20.9% vs TC avg
Moderate +15% lift
Without
With
+14.7%
Interview Lift
resolved cases with interview
Typical timeline
2y 11m
Avg Prosecution
37 currently pending
Career history
996
Total Applications
across all art units

Statute-Specific Performance

§101
37.6%
-2.4% vs TC avg
§103
34.5%
-5.5% vs TC avg
§102
17.0%
-23.0% vs TC avg
§112
6.4%
-33.6% vs TC avg
Black line = Tech Center average estimate • Based on career data from 959 resolved cases

Office Action

§101
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 . Response to Arguments Applicant's arguments filed with respect to the rejection made under § 101 have been fully considered but they are not persuasive. Applicant argues that the amended claims are directed to specific improvements in computer technology by generating product recommendations through extraction of noun phrases using NLP models and applying a semantic similarity model trained using click data to associate natural language question/answer pairs with product identifiers. Examiner respectfully disagrees. This is a problem at the abstract layer of organizing human activities, not one borne out of technology. The problems noted in Specification do not highlight any failures of modern computers. These are business implementation problems and do not set forth any deficiencies that are particular to computer capabilities or any other technology. "In sum, 'software can make non-abstract improvements to computer technology just as hardware improvements can.' Enfish, 822 F.3d at 1335. But to be directed to a patent-eligible improvement to computer functionality, the claims must be directed to an improvement to the functionality of the computer or network platform itself." Customedia Techs., LLC v. Dish Network Corp., 951 F.3d 1359, 1365 (Fed. Cir. 2020) (emphasis added). Specifically, the amended claims recite “using a Natural Language Processing (NLP) modeling tool including a Neural Network to classify portions of the answer and a semantic segmentation algorithm to identify the candidate noun phrases and dependency relations in noun-phrase words.” However, these additional elements fail to integrate the abstract idea into practical application. They are generic computing components (see at least paragraph 041) that are simply used to perform operations that would otherwise be abstract (see MPEP2106.05(f)). The claimed invention does not improve any particular machine or allow one to perform a new function that it was not previously able to do. Instead, it merely chooses one that is properly scaled. This is analogous to, e.g., choosing an appropriately-sized memory when an application requires more storage or a higher-powered processor that is capable of performing faster calculations when those are necessary. It is still using a generic computing element as a tool to perform an abstract function, without setting forth any technological improvements. "[P]atents that do no more than claim the application of generic machine learning to new data environments, without disclosing improvements to the machine learning models to be applied, are patent ineligible under § 101. Recentive Analytics, Inc. v. Fox. Corp., Fed Cir. No. 2023-2437 (Apr. 18, 2025) (slip op. at 18). These elements are all abstract and when viewed in combination only amount to applying the abstract idea on generic computers. "Examiners evaluate integration into a practical application by: (1) identifying whether there are any additional elements recited in the claim beyond the judicial exception(s); and (2) evaluating those additional elements individually and in combination to determine whether they integrate the exception into a practical application…" MPEP 2106.04(d) II. (emphasis added). Accordingly, the rejection is maintained. 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 1-20 are rejected under 35 U.S.C. 101 because the claimed invention is directed to non-statutory subject matter (a judicial exception without significantly more). Claims are eligible for patent protection under § 101 if they are in one of the four statutory categories and not directed to a judicial exception to patentability. Alice Corp. v. CLS Bank Int'l, 573 U.S. 208 (2014). Claims 1-20, each considered as a whole and as an ordered combination, are directed to a judicial exception (i.e., a law of nature, a natural phenomenon, or an abstract idea) without significantly more. Claims 1 and 6 recite a method. Claim 15 recites one or more non-transitory computer-readable media. Step 2A, prong 1: Claim 6 recites the abstract idea of recommending products based on answers to questions. This idea is described by the following steps: A method, comprising: receiving a question from a user; receiving an associated answer to the question; extracting n-grams from the generated answer; generating scores for the n-grams using one or both of the question and the answer; ranking the n-grams using the scores; and searching for and selecting products based upon the ranking. Claims 1 and 15 recite equivalent limitations. This idea falls into the certain methods of organizing human activity grouping of abstract ideas as it is directed towards commercial interactions including advertising, marketing or sales activities or behaviors (i.e., recommending products). Step 2A, prong 2: Claims 1, 6 and 15 recite additional elements that fail to integrate the abstract idea into practical application. Claim 15 recites one or more non-transitory, computer-readable media storing instructions that are executable by the one or more processors to cause the computing system to perform operations. However, these elements are generic computing components (see at least paragraph 041) that are simply used to perform operations that would otherwise be abstract (see MPEP2106.05(f)). Claims 1, 6 and 15 additionally recite using a semantic similarity model, an answer generation model and Natural Language Processing model including a Neural Network. However, these elements are recited at a high level of generality and are merely used as tools to perform the process (i.e., ranking the noun phrases) (see MPEP 2106.05(f)). They are not "additional elements" to be analyzed under this part of the framework, and merely serve to add a general link to a technological environment in which the abstract idea/commercial interaction is carried out, and instructions to apply (execute) it. The additional elements do not amount to significantly more for the same reasons they do not integrate the abstract idea into a practical application (i.e., that they merely provide a general link to a particular technological environment and instructions to "apply it"). Step 2B: Claims 1, 6 and 15 fail to recite additional elements that amount to an inventive concept. For the reasons identified with respect to Step 2A, prong 2, claims 1, 6 and 15 fail to recite additional elements that amount to an inventive concept. For example, use of a computer or other machinery in its ordinary capacity for economic or other tasks (e.g., to receive, store, or transmit data) or simply adding a general-purpose computer or computer components after the fact to an abstract idea (e.g., a fundamental economic practice or mathematical equation) does not integrate a judicial exception into a practical application or provide significantly more (see MPEP 2106.05(g)). 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). For example, at least paragraph 31 describes a network system that facilitates a request for services received from a user including a selection of a merchant. Presenting offers and gathering statistics, OIP Techs., 788 F.3d at 1362-63, 115 USPQ2d at 1092-93. For example, at least paragraph 107describes presenting an offer for an add-on order to be added to a primary order. Dependent Claims Step 2A: The limitations of the dependent claims merely set forth further refinements of the abstract idea identified at step 2A—Prong One, without changing the analysis already presented. Additionally, for the same reasons as above, the limitations fail to integrate the abstract idea into a practical application because they use the same general technological environment and instructions to implement the abstract idea as the independent claims identified at step 2A—Prong Two. Dependent Claims Step 2B: The dependent claims merely use the same general technological environment and instructions to implement the abstract idea. These do not amount to significantly more for the same reasons they fail to integrate the abstract idea into a practical application. Moreover, the Specification also indicates this is the routine use of known components for the same reasons presented with respect to the elements in the independent claims above. Thus, when considering the combination of elements and the claimed invention as a whole, the claims are not patent eligible. Allowable Subject Matter Claims 1-20 remain allowable if rewritten or amended to overcome the rejection(s) under 35 U.S.C. 101, set forth in this Office action. The prior art of record neither anticipates nor renders obvious the combination of: receiving, in a server computer, a question from a client computer entered through an input text box in a User Interface (Ul); receiving an answer to the question from an answer generation model; extracting a pool of candidate noun phrases including words from the answer, wherein the extracting of the pool of candidate noun phrases comprises using a Natural Language Processing (NLP) modelling tool including a Neural Network to classify portions of the answer and a semantic segmentation algorithm to identify the candidate noun phrases and dependency relations in noun-phrase words; inputting the question, answer and the candidate noun phrases into a trained semantic similarity model executed by one or more processors; ranking the noun phrases based upon scores generated by the semantic similarity model; for a highest ranked noun phrase, identifying a product associated with the noun phrase from a product database; and generating, for display on the UI, an image of the identified product in association with the noun phrase, wherein the semantic similarity model is trained using click data collected from prior e-commerce searches, as recited in claim 1. The prior art of record neither anticipates nor renders obvious the combination of: receiving, in a server computer, a question from a user interface; receiving an associated answer to the question, wherein the answer is generated by an answer generation model; extracting n-grams from the generated answer, wherein the extracting of n-grams includes performing the extracting using a Natural Language Processing (NLP) modelling tool including a Neural Network; inputting the question, answer and the candidate noun phrases into a trained semantic similarity model executed by one or more processors; generating scores for the n-grams using the trained semantic similarity module that inputs the n-grams and one or both of the question and the answer to generate the scores; ranking the n-grams using the scores; and searching for and selecting products based upon the ranking; and generating, for display on the UI, an image of the identified product in association with the n-grams, as recited in claim 6. The prior art of record neither anticipates nor renders obvious the combination of: generating an answer to a user question using an answer generation model; extracting noun phrases in the answer using a Natural Language Processing (NLP) model including a Neural Network to classify portions of the answer and a semantic segmentation algorithm to identify the candidate noun phrases; inputting the extracted noun phrases and the user question into a trained semantic similarity model to determine a product associated with the noun phrases; and transmitting an image of the determined product in response to the user question for display in association with a corresponding one of the selected noun phrases, as recited in claim 15. Conclusion THIS ACTION IS MADE FINAL. 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 MILA AIRAPETIAN whose telephone number is (571)272-3202. The examiner can normally be reached Monday-Friday 8:30 am-6:00 pm. Examiner interviews are available via telephone, in-person, and video conferencing using a USPTO supplied web-based collaboration tool. To schedule an interview, applicant is encouraged to use the USPTO Automated Interview Request (AIR) at http://www.uspto.gov/interviewpractice. If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Jeffrey A. Smith can be reached at (571) 272-6763. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300. Information regarding the status of published or unpublished applications may be obtained from Patent Center. Unpublished application information in Patent Center is available to registered users. To file and manage patent submissions in Patent Center, visit: https://patentcenter.uspto.gov. Visit https://www.uspto.gov/patents/apply/patent-center for more information about Patent Center and https://www.uspto.gov/patents/docx for information about filing in DOCX format. For additional questions, contact the Electronic Business Center (EBC) at 866-217-9197 (toll-free). If you would like assistance from a USPTO Customer Service Representative, call 800-786-9199 (IN USA OR CANADA) or 571-272-1000. /MILA AIRAPETIAN/Primary Examiner, Art Unit 3688
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Prosecution Timeline

Mar 30, 2023
Application Filed
Jul 21, 2025
Non-Final Rejection — §101
Oct 08, 2025
Response Filed
Oct 08, 2025
Interview Requested
Oct 14, 2025
Examiner Interview Summary
Oct 14, 2025
Applicant Interview (Telephonic)
Nov 14, 2025
Final Rejection — §101 (current)

Precedent Cases

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Study what changed to get past this examiner. Based on 5 most recent grants.

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Prosecution Projections

3-4
Expected OA Rounds
73%
Grant Probability
88%
With Interview (+14.7%)
2y 11m
Median Time to Grant
Moderate
PTA Risk
Based on 959 resolved cases by this examiner. Grant probability derived from career allow rate.

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