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 .
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and the fee set forth in 37 CFR 1.17(e) has been timely paid, the finality of the previous Office action has been withdrawn pursuant to 37 CFR 1.114.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 May 18th, 2026 has been entered.
Response to Amendment
In response to the February 12th, 2026 Office action, claims 1, 7 and 12 were amended, claims 4, 8, 9 and 13 were canceled and claims 16-24 were newly added. Claims 1-3, 5-7, 10-12 and 14-24 are currently pending and stand rejected.
This Office action is Non-Final.
Response to Arguments
Applicant's arguments filed May 6th, 2026 with respect to the 35 USC 101 (see pages 8-10) have been fully considered but they are not persuasive.
Applicant argues that the claims improve artificial-intelligence-based search systems through the use of artificial intelligence models, intent determination, contextual answer generation, and source selection.
The argument is not persuasive. The claims do not recite an improvement to artificial intelligence technology itself. Rather, the claims use an artificial intelligence model as a tool for processing information, classifying information, selecting information, generating answer content, and presenting information. Any improvement is directed to the content or relevance of information provided to users rather than to the functioning of the computer or artificial intelligence model.
Accordingly, the 35 USC 101 rejection of the claims are being sustained.
Applicant's arguments filed May 6th, 2026 with respect to the 35 USC 103 (see pages 10-14), have been fully considered and are persuasive. The 35 USC 103 rejection has been withdrawn.
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 1-3, 5-7, 10-12 and 14-24 are rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more.
Step 1: Statutory Category
Claims 1 and 7 are directed to methods and claim 12 is directed to a non-transitory computer-readable storage medium. Accordingly, the claims fall within a statutory category of invention.
Step 2A, Prong One: Judicial Exception (Abstract Idea)
The claims recite limitations including:
acquiring query data through query-answer interactions;
generating answers to user queries using an artificial intelligence model;
extracting similar queries from query data using an artificial intelligence model;
providing brief search results for similar queries;
providing additional query-answer information in response to user requests;
generating additional answers based upon previously obtained query-answer information;
selecting information sources for answer generation;
generating answers from different information sources to avoid overlap with previously generated answers;
determining whether a query corresponds to a precise-search intent or a generative-search intent using an artificial intelligence model;
selecting and ordering answer generation based on the determined intent; and
presenting answers and related information to users.
These limitations constitute collecting information, analyzing information, classifying information, selecting information, generating information, and presenting information. Such activities are mental processes and methods of organizing human activity and therefore constitute abstract ideas.
For example, the claims evaluate user query information, identify similar query information, classify query intent, select information sources, generate answer content, avoid repetition of previously generated content, and provide the resulting information to users. The focus of the claims is therefore the evaluation, organization, generation, and presentation of information rather than an improvement to computer technology.
Accordingly, the claims remain directed to an abstract idea.
Step 2A, Prong Two: Integration into a Practical Application
The additional elements include a server, terminal, processor, artificial intelligence model, and computer-readable storage medium. These elements are recited at a high level of generality and perform their ordinary and expected functions.
Although the claims recite use of an artificial intelligence model, the claims do not recite any specific artificial intelligence architecture, training process, inference mechanism, retrieval architecture, prompt-generation mechanism, memory-management technique, or other technological improvement to the operation of a computer system or artificial intelligence model.
The recited determination of precise-search intent versus generative-search intent merely classifies information for subsequent processing. Likewise, generating answers from different sources and avoiding overlap with previously generated answers governs the selection and organization of information provided to a user. These limitations improve the content, relevance, or organization of information presented to users rather than the functioning of the computer itself.
Any alleged improvement resides in the informational content of the generated answers and search results rather than in the operation of the underlying technology.
Accordingly, the claims do not integrate the recited abstract idea into a practical application.
As noted above, the Applicant argues that the claims improve artificial-intelligence-based search systems through the use of artificial intelligence models, intent determination, contextual answer generation, and source selection.
The argument is not persuasive. The claims do not recite an improvement to artificial intelligence technology itself. Rather, the claims use an artificial intelligence model as a tool for processing information, classifying information, selecting information, generating answer content, and presenting information. Any improvement is directed to the content or relevance of information provided to users rather than to the functioning of the computer or artificial intelligence model.
Step 2B: Inventive Concept
The claims do not recite an inventive concept sufficient to transform the abstract idea into patent-eligible subject matter.
The additional elements, individually and in combination, merely implement the abstract idea using generic computer components and a generically recited artificial intelligence model performing conventional information-processing functions.
The claims do not recite a specialized computer architecture, unconventional hardware configuration, specific improvement to artificial intelligence technology, or other technological feature amounting to significantly more than the abstract idea itself.
With respect to the remaining dependent claims, these limitations merely narrow the type of data analysis or presentation being performed, but they do not change the character of the claims from abstract information processing. They do not improve the functioning of the computer or another technology; they merely describe which kind of data is analyzed or how information is displayed.
Accordingly, the dependent claims, when considered individually or in combination with their respective independent claims, also fail to amount to significantly more than the abstract idea.
Prior Art Made of Record
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure.
Boué et al. discloses a follow-up question recommender for AI assistant.
Ayed et al. discloses automated generation of programming code through integration with generative artificial intelligence.
Yee et al. discloses metadata driven prompt grounding for generative artificial intelligence applications.
DeWeese et al. disclose adaptation to detected fluctuations in outputs from artificial intelligence models over time.
Cetoli et al. discloses using intent-based rankings to generate large language model responses.
Terry et al. discloses generating and updating machine hybrid deep learning models.
Conclusions/Points of Contacts
Any inquiry concerning this communication or earlier communications from the examiner should be directed to JORGE A CASANOVA whose telephone number is (571)270-3563. The examiner can normally be reached M-F: 9 a.m. to 6 p.m. (EST).
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, Aleksandr Kerzhner can be reached at (571) 270-1760. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
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/JORGE A CASANOVA/Primary Examiner, Art Unit 2165
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