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 .
DETAILED ACTION
Claims 1-20 are presented for examination.
Claims 1, 2, 3, 9, 15 and were amended.
This is a Non-Final Action.
Continued Examination Under 37 CFR 1.114
A request for continued examination under 37 CFR 1.114, including the fee set forth in 37 CFR 1.17(e), was filed in this application after final rejection. Since this application is eligible for continued examination under 37 CFR 1.114, and the fee set forth in 37 CFR 1.17(e) has been timely paid, the finality of the previous Office action has been withdrawn pursuant to 37 CFR 1.114. Applicant's submission filed on 05/26/2026 has been entered.
Response to Arguments
Applicant’s arguments with respect to claim(s) 1-20 have been considered but are moot because the new ground of rejection does not rely on any reference applied in the prior rejection of record for any teaching or matter specifically challenged in the argument.
With respect to abstract idea 101, examiner respectfully disagrees. Specifically, under step 2A, prong 1, claim 1 recites the abstract idea of determining items needed to perform an intended task and identifying item listings for those items. Under Step 2A prong 2, the claim does not integrate the abstract idea into a practical application because the additional elements, including the search engine, search system, classification model, generative AI model, database and user devices are used to classify a query, generate item terms, search listings and displaying results. The claim does not improve the functioning of search engine, classification mode, generative AI model, databases or user device; does not recite a particular technological improvement to AI or search technology. The recited real-world task and physical items merely define the informational content of the query and search results.
Under Step 2B, the additional element, individually or in ordered combination, amount to no more than applying the abstract idea using generic computer components performing generic computer functions, such as, receiving data, classifying data, generating data, search a database and displaying results. The claim therefore does not include additional elements that amount to significantly more than the judicial exception.
Claim Rejections - 35 U.S.C. §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 therefore, subject to the conditions and requirements of this title.
Claims 1-20 are rejected under 35 USC 101 as directed to an abstract idea without significantly more.
With respect to independent claims, 1, 9 and 15, specifically claim 1 recites “determining…”, “responsive to determining the search query is the intent-based query”, “generating, a list of items…”, “identify item listing corresponding to the list of items that can be used in accomplishing the task”. This limitations could be reasonably and practically performed by the human mind, based on the are observation/evaluation steps. Accordingly, the claim recites a mental process, which can be done utilizing pen and paper.
Accordingly, the claim recites an abstract idea.
This judicial exception is not integrated into a practical application. At step 2A, prong two, claim(s) 1, 9 and 15 recites the additional elements of “receiving a search query from a user; “by a classification model of the search system”, “…providing, by the search engine of the search system, the search query to a generative Al model;” “generating by the generative Al model…;” and “executing… generated by the generative AI model as search input to”, “providing… display…;” are elements merely invoking a generic computer environment (processor, database, memory) and basic data-gathering and outputting functions (MPEP 21096.05(f)) using output from a generic AI/classification system hence reciting insignificant extra solution activities.
Accordingly, this additional element does not integrate the abstract idea into a practical application because it does not impose any meaningful limits on practicing the abstract idea. The claim is directed to an abstract idea.
The claims, 1, 9 and 15 at step 2B do not include additional elements that are sufficient to amount to significantly more than the judicial exception. As explained with respect to Step 2A Prong Two, the additional elements as recited in step 2A prong 2 recite conventional computer executing routine data-storage and retrieval operations with utilization of generic AI computer technologic. No elements individually or in combination adds “significantly more” than the abstract idea hence are no more than well-understood, routine and conventional computer functions that merely apply the abstract idea on a generic computer. When viewed as an ordered combination, these additional elements do not integrate the abstract idea into a practical application and do not add significantly more than the abstract idea itself. According, claim 1 is ineligible under 101.
Claims 2-8 are dependent claims and do not recite any additional elements that would amount to significantly more than the abstract idea. Specifically,
Claim 2. With respect to step 2A prong 2 “automatically, and without additional user input, populating a search bar of the search engine with the list of items that can be used in accomplishing the task defined by the search query.” recites additional elements of insignificant extra solution activity of utilizing generic computer actions and merely extra post-processing of data (data presentation (outputting & user selection). With respect to step 2B the recited insignificant extra solution activity is recited at a high level of generality which are well-understood, routine and conventional as taught by the prior art of records.
Claim 3. With respect to step 2A prong 1 “wherein the real-world task is distinct from purchasing an item.” recites abstract idea of mental steps (observation & evaluation), a person can classify a given search query as a task or just a item for purchase.
Claim 4. With respect to step 2A prong 1 “determining that the query is an intent-based query, by a classification model trained to determine words that are characteristic of a user searching for items to perform a task. ” recites abstract idea of mental steps (observation & evaluation), because a human can read a query, analyze the words used, and determine whether it reflects intent to perform a task. The utilization of classification model merely automates that mental evaluation rather than integrating the abstract idea into a practical technological application.
Claim 5. With respect to step 2A prong 2 “providing an option for the user to execute a search for the search query or the search for the list of items corresponding to a task defined by the search query” recites additional elements of insignificant extra solution activity of presenting data for selection from the user in a computing environment, this is nothing but applying a survey to a computing environment. With respect to step 2B the recited insignificant extra solution activity is recited at a high level of generality which are well-understood, routine and conventional as taught by the prior art of records.
Claim 6. With respect to step 2A prong 1 “determining the search query is not a cached query.” recites abstract idea of mental steps (observation & evaluation), a person can determine if a query is a cached query or not.
Claim 7. With respect to step 2A prong 1 “identifying the task defined by the search query.” recites abstract idea of mental steps (observation & evaluation), a person can determine what tasks are needed for a query to be executed.
Claim 8. With respect to step 2A prong 2 “enabling the user to add additional items to the portion of items prior to executing the search.” recites additional elements of insignificant extra solution activity of presenting data for selection from the user in a computing environment, this is nothing but applying a survey to a computing environment. With respect to step 2B the recited insignificant extra solution activity is recited at a high level of generality which are well-understood, routine and conventional as taught by the prior art of records.
Claims 9-20 are similar to claims 1-8 hence rejected similarly.
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 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 of this title, 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, 3, 4, 7-9, 11-15 and 17-20 are rejected under 35 U.S.C. 103 as being unpatentable over Beauchamp et al. (US 2024/0289365) in view of Fenton et al. (US 2021/0073293) further in view of Yerubandi (US 2015/0235292)
1. Beauchamp teaches, A method of leveraging generative artificial intelligence (Al) to identify products for completing a task (Abstract, Paragraph 38 – teaches an AI/LLM search system in a ecommerce/product search context where the search query is used for products sold on a e-commerce platform, Beauchamp), the method comprising:
receiving, at a search engine of a search system, a search query from a user (Paragraph 86 – teaches receiving a search query input, Beauchamp);
providing, by the search engine of the search system, the search query to a generative Al model (Paragraphs 13 & 87 - teaches that the search query is passed to an LLM as input and the computing system sends a prompt to the LLM to generate input enhancement data for the search query, Beauchamp);
generating, by the generative Al model… (Paragraph 87 - teaches that the LLM generates input enhancement data based on the search query input, and that the output may include keywords, synonyms, sentences, images or product description text related to the search query, Beauchamp)
executing, by the search engine of the search system, a database search at least one search on a database of the search system utilizing the list of items generated by the generative Al model to retrieve search results as search inputs (Fig 2: 202, 204, 206 and 208 - teaches performing a search, wherein LLM output/input enhancement data can complement or supplement the search query, Beauchamp).
Beauchamp does not explicitly teach,
determining, by a classification model of the search system, that the search query is an intent-based query that describes a real-world task that the user intends to perform, the real-world task requiring use of at least one physical item to carry out one or more real-world actions associated with completing the real-world task;
responsive to determining the search query is the intent-based query;
…a list of items corresponding to that can be used in accomplishing the task defined by the search query;
…to identify item listings corresponding to the list of items that can be used in accomplishing the task; and
providing, by the search system in response the search query from the user, search results identifying the item listings corresponding to the list of items for display by a user device associated with the user.
However, Fenton teaches,
determining, by a classification model of the search system, that the search query is an intent-based query (Paragraph 120 – teaches intent classifiers, Fenton);
responsive to determining the search query is the intent-based query(Fig 3A:302, 304b, 308b and Paragraph 33 – teaches determining if a search-based query is required, Fenton);
It would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to which said subject matter pertains to incorporate Fenton’s task-intent classification into Beauchamp’s generative-AI search system would improve the search processing for task oriented queries by identifying when the user is not merely searching for a named product but is expressing an intent task requiring
Yerubandi teaches,
…that describes a real-world task that the user intends to perform (Fig 3: 310, 320, 330, 340, 350 – teaches real world tasks user intends to perform, Yerubandi), the real-world task requiring use of at least one physical item to carry out one or more real-world actions associated with completing the real-world task (Fig 4:410, 420 – teaches a real world task and real world physical items to finish the task, Yerubandi);
…a list of items corresponding to that can be used in accomplishing the task defined by the search query (Fig 4:410, 420 – teaches a real world task and real world physical items to finish the task, Yerubandi);
…to identify item listings corresponding to the list of items that can be used in accomplishing the task (Fig 6:620 – teaches determine a plurality of items, Yerubandi); and
providing, by the search system in response the search query from the user, search results identifying the item listings corresponding to the list of items for display by a user device associated with the user (Fig 6:530 – teaches generating a page including the plurality of items, Yerubandi).
It would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to which said subject matter pertains to modify the combination of Beauchamp/Fenton system to include Yerubandi’s project item determination and display functionality. A POSITA would have been motivated to combine the prior arts because it would improve the usefulness and relevance of Beauchamp’s search results for task-oriented queries identified by Fenton by returning listing for the physical items needed to complete the user’s project thereby avoiding the need for the user to individually search for each required item and reducing the risk that the user selects incompatible or incomplete items.
3. The combination of Beauchamp/Fenton/Yerubandi teaches, The method of claim 1, wherein the real-world task is distinct from purchasing an item (Fug 4:410 – the query teaches a real world task “Paint my room” , 420 – teaches distinct items that can be purchased, Yerubandi).
4. The combination of Beauchamp/Fenton/Yerubandi teaches, The method of claim 1, further comprising:
determining that the query is an intent-based query, by a classification model trained to determine words that are characteristic of a user searching for items to perform a task (Paragraphs 5 and 24 – teaches a set of classifiers to identify task intents from user composed content, where each classifier may be trained to detect a particular task intent, Paragraph 68 – further teaches that the classifier may be comprised of a machine learning model (neural networks), Fenton);
determining available items of the portion of items that are available in an inventory; and executing the search for portion of items that are available in the inventory (Paragraph 24 – teaches determining “availability of the item”, Fig 4:420 – based on the search discloses the items and availability of the items, Yerubandi).
7. The combination of Beauchamp/Fenton/Yerubandi teaches, The method of claim 1, further comprising identifying the task defined by the search query (Figs 3 and 4 – teaches a task defined by the search query, Yerubandi).
8. The combination of Beauchamp/Fenton/Yerubandi teaches, The method of claim 1, further comprising enabling the user to add additional items to the portion of items prior to executing the search (Paragraph 37 – recites that based on feedback determining plurality of items, this in view of BRI would teach if a user found a tool useful or suggested another tool to be used for a particular task, which is taken into consideration, thereby suggesting that a item can be added based on previous feedback to the existing searching for tools, Yerubandi).
Claim 9 is similar to claim 1 hence rejected similarly.
Claim 11 is similar to claim 3 hence rejected similarly.
Claim 12 is similar to claim 1 hence rejected similarly, Claim 1 recites “providing the search query to a generic AI model”.
Claim 13 is similar to claim 4 hence rejected similarly.
Claim 14 is similar to claims 4 and 8 hence rejected similarly.
Claim 15 is similar to claim 1 hence rejected similarly.
17. The combination of Beauchamp/Fenton/Yerubandi teaches, The system of claim 15, further comprising receiving, from the user, a selection of the portion of items of the list of items (Fig 4 – explicitly recites that each item can be viewed (and purchased) separately (440) or they can be purchased all (450), Yerubandi).
18. The combination of Beauchamp/Fenton/Yerubandi teaches, The system of claim 17, further comprising, based on the selection, executing a search for the selection of the portion of items (Fig 4:440 – teaches view item button, hence when selected, the item page is generated by search/retrieval operation to display the item, Yerubandi).
Claim 19 is similar to claim 8 hence rejected similarly.
Claim 20 is similar to claim 7 hence rejected similarly.
Claims 2, 5 and 16 are rejected under 35 U.S.C. 103 as being unpatentable over Beauchamp et al. (US 2024/0289365) in view of Fenton et al. (US 2021/0073293) and Yerubandi (US 2015/0235292) further in view of Dangwal et al. (US 2024/0045908)
All the limitations of claim 1 are taught above.
2. The combination of Beauchamp/Fenton/Yerubandi teaches, …with the list of items that can be used in accomplishing the task defined by the search query (Fig 4:410 – teaches the query “Paint my room” and then 420 – discloses the list of items to accomplish the task, Yerubandi).
The combination of Beauchamp/Fenton/Yerubandi teaches, does not explicitly teach, automatically, and without additional user input, populating a search bar of the search engine.
However, Dangwal teaches, automatically, and without additional user input, populating a search bar of the search engine (Abstract, Paragraph 64 – teaches autocompleting menu with suggested search queries as the user is inputting text in a search box, Dangwal).
It would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to which said subject matter pertains to modify the combination of Beauchamp/Fenton/Yerubandi system to automatically populate the search bar interface with the list of task related items generated from the user’s intent based query in order to reduce user effort and improve multi intent searching by avoiding the need for the user to manually enter each generated item as a separate search query.
All the limitations of claim 1 are taught above.
5. The combination of Beauchamp/Fenton/Yerubandi does not explicitly teach, providing an option for the user to execute a search for the search query or the search for the list of items corresponding to a task defined by the search query.
However, Dangwal teaches, providing an option for the user to execute a search for the search query or the search for the list of items corresponding to a task defined by the search query (Fig 4 - teaches a list of items corresponding to a task that can be selected for purchase, Yerubandi; in combination with Abstract, Paragraph 64 – teaches autocompleting menu with suggested search queries as the user is inputting text in a search box – thus disclosing that the applicant can choose to execute the original query or the menu suggestions (which can be the list of items when combined with Yerubandi), Dangwal).
It would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to which said subject matter pertains to modify the combination of Beauchamp/Fenton/Yerubandi system to automatically populate the search bar interface with the list of task related items generated from the user’s intent-based query in order to
Claim 16 is similar to claim 5 hence rejected similarly.
Claims 6 and 10 rejected under 35 U.S.C. 103 as being unpatentable over Beauchamp et al. (US 2024/0289365) in view of Fenton et al. (US 2021/0073293) and Yerubandi (US 2015/0235292) further in view of Jiang et al. (US 10,565,255)
All the limitations of claim 1 is taught above.
6. The combination of Beauchamp/Fenton/Yerubandi does not explicitly teach, determining the search query is not a cached query.
However, Jiang teaches, determining the search query is not a cached query (Col 7: lines 25-27 – teaches caching and storing images into local image store; and Col 3: lines 25-32 – teaches a search engine performing a search in content database which includes primary content database and/or auxiliary content database, to identify a list of content items that are related to the keywords.. the combination teaches that when searching the search would perform as cache search before performing a fresh query search, Jiang).
It would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to which said subject matter pertains to allow combination of Beauchamp/Fenton/Yerubandi system to be combined with Jiang’s invention because the combination of Beauchamp/Fenton/Yerubandi system and Jiang are in the same field of endeavor of improving search experience by analyzing user inputs and returning relevant items.
Claim 10 is similar to claim 6 hence rejected similarly.
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure.
Kalns et al. (US 9,081,411) – teaches ecommerce ontology (fig 7).
Any inquiry concerning this communication or earlier communications from the examiner should be directed to AMRESH SINGH whose telephone number is (571)270-3560. The examiner can normally be reached Monday-Friday 8am-5pm.
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If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Ann J. Lo can be reached at (571) 272-9767. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
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/AMRESH SINGH/Primary Examiner, Art Unit 2159
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