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 .
Status of Claims
This action is in reply to the communications filed on August 18, 2026. The Applicants’ Amendment and Request for Reconsideration has been received and entered.
Claims 1-5, 7-13, and 15-20 are currently pending and have been examined. Claims 1, 7, 9, 15, and 17 have been amended. Claims 6 and 14 have been canceled.
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and the fee set forth in 37 CFR 1.17(e) has been timely paid, the finality of the previous Office action has been withdrawn pursuant to 37 CFR 1.114.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 August 18, 2026, has been entered.
Response to Arguments
Applicants’ arguments regarding the rejection under 35 USC 101 have been fully considered but they are not persuasive. Applicants argue at page 11 of Applicants’ Reply dated August 18, 2026 (hereinafter “Applicants’ Reply”) that the “MPEP and Ex parte Desjardins set forth a two-part test for determining whether a technical improvement is recited in the claims. First, does the disclosure ‘provide sufficient details such that one of ordinary skill in the art would recognize the claimed invention as providing an improvement’…..Second, does the claim itself ‘reflect[] the disclosed improvement in technology.’” Applicants further argue at page 12 of Applicants’ Reply that the disclosed system “computes an improvement” to the technology “by generating a user-specific relevancy threshold for selecting items to include in a search result. The system processes a small fraction of queries under a relaxed relevance threshold and the remaining queries under the ordinary threshold, trains a first model on data collected in one mode and a second model on data collected in the other, and takes the difference between the two model outputs as a sensitivity score for that user.” Applicants further argue at page 13 of Applicants’ Reply that a “person of ordinary skill in the art reading these passages would recognize an improvement in how the content selection stage of a search operates. The value that governs which content items pass the filter changes from a constant fixed in the system configuration to a quantity the system computes at run time from a machine learning output that is conditioned for the particular user. Accordingly, the disclosure provides ‘sufficient details such that one of ordinary skill in the art would recognize the claimed invention as providing an improvement.’” The Examiner respectfully disagrees.
First, the Examiner notes that, as acknowledged by Applicants at page 13 of Applicants’ Reply, the claims recite an alleged “improvement to the search selection process.” However, the Examiner respectfully asserts that this is an improvement to the abstract idea, i.e., the search algorithm—not to any technology.
Per MPEP 2106.05(a), improvements to computer functionality include a modification of conventional Internet hyperlink protocol to dynamically produce a dual-source hybrid webpage; inventive distribution of functionality within a network to filter Internet content; a method of rendering a halftone digital image; a distributed network architecture operating in an unconventional fashion to reduce network congestion while generating networking accounting data records; a memory system having programmable operational characteristics that are configurable based on the type of processor, which can be used with different types of processors without a tradeoff in processor performance; technical details as to how to transmit images over a cellular network or append classification information to digital image data; a particular structure of a server that stores organized digital images; a particular way of programming or designing software to create menus; a method that generates a security profile that identifies both hostile and potentially hostile operations, and can protect the user against both previously unknown viruses and "obfuscated code," which is an improvement over traditional virus scanning; an improved user interface for electronic devices that displays an application summary of unlaunched applications, where the particular data in the summary is selectable by a user to launch the respective application; a specific interface and implementation for navigating complex three-dimensional spreadsheets using techniques unique to computers; and a specific method of restricting software operation within a license.
Per MPEP 2106.05(a), some examples that the courts have said “may not be sufficient to show an improvement in computer-functionality” include generating restaurant menus with functionally claimed features; accelerating a process of analyzing audit log data when the increased speed comes solely from the capabilities of a general-purpose computer; mere automation of manual processes, such as using a generic computer to process an application for financing a purchase; recording, transmitting, and archiving digital images by use of conventional or generic technology in a nascent but well-known environment, without any assertion that the invention reflects an inventive solution to any problem presented by combining a camera and a cellular telephone; affixing a barcode to a mail object in order to more reliably identify the sender and speed up mail processing, without any limitations specifying the technical details of the barcode or how it is generated or processed; instructions to display two sets of information on a computer display in a non-interfering manner, without any limitations specifying how to achieve the desired result; providing historical usage information to users while they are inputting data, in order to improve the quality and organization of information added to a database, because "an improvement to the information stored by a database is not equivalent to an improvement in the database’s functionality”; and arranging transactional information on a graphical user interface in a manner that assists traders in processing information more quickly.
With this guidance in mind, the Examiner respectfully asserts that the claims are not directed to a practical application. First, the stated problem of a relevance score in a search system that is “fixed in prior system configurations [that] do not vary from user to user” as described at page 12 of Applicants’ Reply is not a technical problem. Instead, this is a search results selecting issue, i.e., an issue with the abstract idea itself rather than the underlying technology. In light of the examples discussed above, this appears most similar to providing historical usage information to users while they are inputting data in order to improve the quality and organization of information added to a database. The examples make the distinction between “an improvement to the information stored by a database” and “an improvement to the database’s functionality.” Similarly, the search result selecting system described in the claims improves the quality of the information presented to a user, i.e., results having a higher user-relevancy score, rather than an improvement to the computer’s functionality.
Further, the Examiner respectfully notes that determining user-specific relevancy for search results is mere automation of a mental process that has been performed manually before the advent of the internet. For example, a sales clerk in a store would present different products to a customer based on information about the user, i.e., a customer looking for “dressy shoes” would be shown different shoes depending on the gender of the customer, the customer’s stated price range, additional customer information regarding an occasion for wearing the shoes, etc.
Further, the alleged improvement to the search result selection algorithm appears to stem merely from performing the process on the computer, i.e., mere automation of a mental process, rather than an actual improvement to the technology itself. In fact, there is no difference in the operation of the computer resulting from using the claimed invention and thus no technological improvement. The Examiner has previously identified the computer components (i.e., the processor and the non-transitory computer readable storage medium in claim 17) as generic computer components performing generic computer functions and that they do not integrate the abstract idea into a practical application.
Thus, the rejection under 101 is maintained.
Applicants’ remaining arguments have been fully considered but they have either been addressed above or they are moot in view of the new grounds of rejection.
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 1-5, 7-13, and 15-20 are rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more.
Independent claims 1, 9, and 17 are directed to a method, a computer program product, and a system for providing search results to a user. With respect to claim 1, claim elements accessing a machine learning model, applying the machine learning model, selecting one or more content items, determining a minimum relevance threshold, determining whether a relevance score is greater than the minimum relevance threshold, selecting the content item, and incorporating the selected content items into the set of search results, as drafted, illustrate steps that, under their broadest reasonable interpretation, cover a mental process. That is, nothing in the claim precludes the steps from practically being performed in the mind. Claims 9 and 17 recite similar limitations.
The judicial exception is not integrated into a practical application. In particular, claims 1, 9, and 17 recite receiving/retrieving and sending (transmitting) steps. These limitations are considered to be insignificant extra-solution activity.
Further, claim 17 recites a processor and a non-transitory computer readable storage medium. These elements are recited at a high level of generality, i.e., as generic computer components performing generic computer functions. Accordingly, these additional elements do not integrate the abstract idea into a practical application because they do not impose any meaningful limits on practicing the abstract idea.
The claims do not include additional elements that are sufficient to amount to significantly more than the judicial exception. As discussed above, claims 1, 9, and 17 recite receiving/retrieving and sending (transmitting) steps. Per MPEP 2106.05(d)(II), elements such as receiving or transmitting data over a network, using the Internet to gather data, and storing and retrieving information in memory are considered to be computer functions that are well-understood, routine, and conventional functions. See Versata Dev. Group, Inc. v. SAP Am., Inc., 793 F.3d 1306, 1334, 115 USPG2d 1681, 1701 (Fed. Cir. 2015); OIP Techs., Inc., v. Amazon.com, Inc., 788 F.3d 1359, 1363, 115 USPQ2d 1090, 1093 (Fed. Cir. 2015) (sending messages over a network); buySAFE, Inc. v. Google, Inc., 765 F.3d 1350, 1355, 112 USPQ2d 1093, 1096 (Fed. Cir. 2014) (computer receives and sends information over a network)).
Further, as discussed above, claim 17 recites a processor and a non-transitory computer readable storage medium. These elements are recited at a high level of generality (i.e., as generic computer components performing generic computer functions). Mere instructions to apply an exception using generic computer components cannot provide an inventive concept.
Thus, claims 1, 9, and 17 are directed to the abstract idea.
Claims 2-5, 7-8, 10-13, 15-16, and 18-20 depend from claims 1, 9, and 17. Claims 2, 10, and 18 are directed to a first model, a second model, and determining the sensitivity score as a difference between the outputs of the two models and are further directed to the abstract idea. Claims 3, 11, and 19 are directed to training the first and second model and are further directed to the abstract idea. Claims 4, 12, and 20 are directed to the type of model and are further directed to the abstract idea. Claims 5 and 13 are directed to obtaining additional data and retraining the model and are further directed to the abstract idea. Claims 7 and 15 are directed to the sensitivity score and are further directed to the abstract idea. Claims 8 and 16 are directed to using the stored sensitivity score to select content items and are further directed to the abstract idea. Claims 8 and 16 are further directed to storing the sensitivity score which, as discussed above, is an activity that is considered to be well-understood, routine, and conventional.
Thus, the claims are not patent eligible.
Potentially Allowable Subject Matter
Claims 1-5, 7-13, and 15-20 would be allowable if rewritten or amended to overcome the rejection(s) under 35 U.S.C. 101 set forth in this Office action.
With respect to claim 1, the prior art of record, alone or combined, neither anticipates nor renders obvious, a method comprising receiving a query from a target user; retrieving a set of search results responsive to the query; retrieving a set of content items for inclusion within the set of search results, where each of the set of content items has a relevance score to the query; accessing a machine learning model trained to predict a sensitivity score that predicts a loss in engagement by a user with a set of search results caused by incorporating into the set of search results a content item that is selected without consideration of relevance to the set of search results; applying the machine learning model to user data of the target user to output a sensitivity score for the target user; selecting one or more content items from the set of content items, wherein the selecting is based on the sensitivity score and the relevance scores of the set of content items such that a higher sensitivity score results in selecting content items having greater relevance scores, the selecting comprising: determining a minimum relevance threshold based on the sensitivity score; determining whether a relevance score of a content item is greater than the minimum relevance threshold; and responsive to determining that the relevance score of the content item is greater than the minimum relevance threshold, selecting the content item from the set of content items; incorporating the selected content items into the set of search results; and sending the set of search results with the selected content items for display to the target user, wherein the sending causes a device of the target user to display the set of search results and the selected content items.
With respect to claims 9 and 17, the prior art of record, alone or combined, neither anticipates nor renders obvious a computer program product and a system reciting similar limitations.
In the event the claims are amended, they will be subject to further examination.
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure.
US 2026/0253123 A1 to Vasiete Allas is directed to an online concierge system that “generates a personalized storefront user interface to recommend items for purchase and delivery to a customer” by obtaining “a user identifier for the customer and generates a set of recommended search terms that it predicts will be relevant to the customer. The recommended search terms may be identified at least in part by mapping items previously purchased by the customer to search queries that resulted in purchases of that item across a population of customers of the online concierge system. The online concierge system then executes respective search queries for the each of the set of search terms to generate respective search result sets for each of the recommended search terms.” (See Abstract).
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/Anne M Georgalas/
Primary Examiner, Art Unit 3689
