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 .
Status of Claims
This Office Action is in response to the communication filed on 08/18/2025.
Claims 1-2, 10-14 and 16-21 have been amended.
New claim 21 has been added.
5. Claims 1-21 are currently pending and are considered below.
Claim Rejections - 35 USC § 101
6. 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.
7. Claims 1-21 are rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more. Claims 1 and 20, representative claim 1 recites a computer-implemented method, which is a statutory class, comprising:
identifying, by one or more processors of a server computing device, areal time sequence of user actions for a plurality of listings by a specific user within a sliding window of time;
generating, by the one or more processors, a first representation for the sequence of user actions using an encoder component of a personalization module to encode content and position of the sequence of user actions;
generating, by the one or more processors, a second representation for the sequence of user actions using a pretrained representations component of the personalization module to encode listing identifiers of the plurality of listings as a sequence representation of a vector;
generating, by the one or more processors, a third representation for the sequence of user actions using a learned representations component of the personalization module to embed the sequence of user actions in a vector space for a given task;
using, by the one or more processors, the personalization module to combine the first representation, second representation and the third representation to generate a short-term personalized representation for the specific user; and
providing, by the one or more processors, a set of results for display to the specific user based on the short-term personalized representation.
The steps of,
identifying, by one or more processors of a server computing device, areal time sequence of user actions for a plurality of listings by a specific user within a sliding window of time;
generating, by the one or more processors, a first representation for the sequence of user actions using an encoder component of a personalization module to encode content and position of the sequence of user actions;
generating, by the one or more processors, a second representation for the sequence of user actions using a pretrained representations component of the personalization module to encode listing identifiers of the plurality of listings as a sequence representation of a vector;
generating, by the one or more processors, a third representation for the sequence of user actions using a learned representations component of the personalization module to embed the sequence of user actions in a vector space for a given task;
using, by the one or more processors, the personalization module to combine the first representation, second representation and the third representation to generate a short-term personalized representation for the specific user; and
providing, by the one or more processors, a set of results for display to the specific user based on the short-term personalized representation,
as drafted, is a process that , under its broadest reasonable interpretation, covers a method of organizing human activity. Given the broadest reasonable interpretation, the claim recites the method for generating personalized results. The above identified method steps recite commercial interactions such as sales activities and/or tailored personalized marketing relating to displaying the advertising content to users. The sales activities and the tailored/personalized marketing (generating representation for user actions and providing results) include displaying the results to specific user (which can also be considered to invoke a mental process of organizing information).
If a claim limitation, under its broadest reasonable interpretation, covers commercial interaction such as tailored personalized marketing, then it falls within the “certain methods of organizing human activity” grouping of abstract ideas. Accordingly, the claim recites an abstract idea.
This judicial exception is not integrated into a practical application. In particular, the claim recites the additional elements of personalization module, server computing device, one or more processor and one or more memory. The server computing device is recited at a high-level of generality (i.e., as a generic processor performing a generic computer functions of identifying a set of user actions, generating representations , combining the first, second and third representations and providing the results for displaying to the specific user) such that they amount to no more than mere instructions to apply the exception using generic computer components. 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 claim is directed to an abstract idea.
The claim does not include additional elements that are sufficient to amount to significantly more than the judicial exception. As discussed above with respect to integration of the abstract idea into a practical application, the additional elements of
server computing device, one or more processor and one or more memory amount to no more than mere instructions to apply the exception using generic computer components. The additional elements are similar to the additional elements found by courts to be mere instructions to apply an exception because they do no more than merely invoke computers or machinery to perform an existing process such as: a common business method or mathematical algorithm being applied on a general purpose computer (Alice Corp. Pty. Ltd. V. CLS Bank Int’l, 573 US 208, 223; Versata Dev. Group, Inc. v. SAP Am., Inc., 793 F.3d 1306, 1334); providing a user with tailored information like advertisements based on information known about the user such as a location, address, or personal characteristics and a time of day is a fundamental practice long prevalent in our system); In re Morsa, 809 F. App’x 913, 917 (Fed. Cir. 2020); and requiring the use of software to tailor information and provide it to the user on a generic computer, Intellectual Ventures I LLC v. Capital One Bank (USA), 792 F.3d 1363, 1370-71). Mere instructions to apply an exception using a generic computer component cannot provide an inventive concept.
Thus, considered as an ordered combination, the additional elements add nothing that is not already present when the steps are considered separately. That is, personalization module, server computing device, one or more processor and one or more memory performing commercial interactions including: generating personalized results by identifying a set of user actions, generating representations , combining the first, second and third representations and providing the results for displaying to the specific user, amount to mere instructions to apply the steps of identifying a set of user actions, generating representations , combining the first, second and third representations and providing the results for displaying to the specific user, amount to mere instructions to apply the personalization module and server computing device to a computer.
Thus, claims 1 and 20 are not eligible.
Dependent claims 2-19 and 21, 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 and 20 without significantly more.
As for dependent claim 2, this claim recites” wherein the sequence of user actions include one or more of search queries, item favorites, listing views, items added to a cart of the specific user, or one or more past purchases.” these claims recite limitations that further define the same abstract idea noted in claim 1. Therefore, they are considered patent ineligible for the reasons given above. The additional limitations of the dependent claims, when considered individually and as an ordered combination, do not amount to significantly more than the abstract idea itself.
As for dependent claim 3, this claim recites “further comprising: inputting the short-term personalized representation into one or more personalized downstream models in order to generate a value; and ranking the set of results based on the value, and wherein the ranked set of results is provided for display to the specific user.”, the steps of inputting the short-termed personal representation and ranking the set results are also directed to certain methods of organizing human activity. Therefore, they are considered patent ineligible for the reasons given above. The additional limitations of the dependent claims, when considered individually and as an ordered combination, do not amount to significantly more than the abstract idea itself.
As for dependent claim 4, this claim recites” wherein the one or more personalized downstream models includes a first model that generates a predicted probability that a particular listing will be clicked.” these claim recite limitation that further define the same abstract idea noted in claim 3. Therefore, they are considered patent ineligible for the reasons given above. The additional limitations of the dependent claims, when considered individually and as an ordered combination, do not amount to significantly more than the abstract idea itself.
As for dependent claim 5, this claim recites” wherein the one or more personalized downstream models further include a second model that generates a predicted conditional probability that a good or service represented by a listing will be purchased.” these claim recite limitation that further define the same abstract idea noted in claim 4, in generating the predicted probability that a particular listing will be clicked. Therefore, they are considered patent ineligible for the reasons given above. The additional limitations of the dependent claims, when considered individually and as an ordered combination, do not amount to significantly more than the abstract idea itself.
As for dependent claim 5, these claims recite “wherein the personalization module is implemented as a Tensorflow Keras layer.” These claim recite limitations that further define the same abstract idea in claim 1. Therefore, they are considered patent ineligible for the reasons given above. The additional limitations of the dependent claims, when considered individually and as an ordered combination, do not amount to significantly more than the abstract idea itself.
As for dependent claim 7, these claims recite “further comprising determining a length of the sliding window based on a location of the specific user.” The steps of determining a length of the sliding window are also directed to certain methods of organizing human activity. Therefore, they are considered patent ineligible for the reasons given above. The additional limitations of the dependent claims, when considered individually and as an ordered combination, do not amount to significantly more than the abstract idea itself.
As for dependent claim 8, these claims recite “further comprising determining a length of the sliding window based on a type of listing selected by the specific user within the sliding window.” The steps of determining a length of the sliding window are also directed to certain methods of organizing human activity. Therefore, they are considered patent ineligible for the reasons given above. The additional limitations of the dependent claims, when considered individually and as an ordered combination, do not amount to significantly more than the abstract idea itself.
As for dependent claims 9-11, these claims recite limitations that further define the same abstract idea noted in claim 1. Therefore, they are considered patent ineligible for the reasons given above. The additional limitations of the dependent claims, when considered individually and as an ordered combination, do not amount to significantly more than the abstract idea itself.
As for dependent claim 12, these claims recite “wherein the encoder component is implemented as an importable Keras layer which encodes sequences of listings.” The steps of encoding sequences of listings are also directed to certain methods of organizing human activity. Therefore, they are considered patent ineligible for the reasons given above. The additional limitations of the dependent claims, when considered individually and as an ordered combination, do not amount to significantly more than the abstract idea itself.
As for dependent claim 13, these claims recite “wherein the pretrained representations component is configured to encode sequences of user actions within the sliding window.” The steps of encoding sequences of user actions are also directed to certain methods of organizing human activity. Therefore, they are considered patent ineligible for the reasons given above. The additional limitations of the dependent claims, when considered individually and as an ordered combination, do not amount to significantly more than the abstract idea itself.
As for dependent claim 14, these claims recite “wherein the pretrained representations component is configured to encode sequences of search queries within the sliding window as text representations.” The steps of encoding sequences of search queries are also directed to certain methods of organizing human activity. Therefore, they are considered patent ineligible for the reasons given above. The additional limitations of the dependent claims, when considered individually and as an ordered combination, do not amount to significantly more than the abstract idea itself.
As for dependent claim 15, these claims recite “wherein the text representations are Skip-gram text representations.” this claim recites limitation that further define the same abstract idea noted in claim 14. Therefore, they are considered patent ineligible for the reasons given above. The additional limitations of the dependent claims, when considered individually and as an ordered combination, do not amount to significantly more than the abstract idea itself.
As for dependent claims 16-18, these claims recite limitations that further define the same abstract idea noted in claim 1. The steps of encoding sequences of listing identifiers within the sliding window are also directed to certain methods of organizing human activity. Therefore, they are considered patent ineligible for the reasons given above. The additional limitations of the dependent claims, when considered individually and as an ordered combination, do not amount to significantly more than the abstract idea itself.
As for dependent claim 19, this claim recites “wherein the learned representations component is configured as a look-up table.” this claim recites limitation that further define the same abstract idea noted in claim 1. Therefore, they are considered patent ineligible for the reasons given above. The additional limitations of the dependent claims, when considered individually and as an ordered combination, do not amount to significantly more than the abstract idea itself.
As for dependent claim 21, this claim recite “wherein the given task relates to one of clicks or purchases”, this claim recite limitations that further define the same abstract idea noted in claim 21. Therefore, it is considered patent ineligible for the reasons given above. The additional limitations of the dependent claims, when considered individually and as an ordered combination, do not amount to significantly more than the abstract idea itself.
Claims 1-21 are therefore not drawn to eligible subject matter as they are directed to an abstract idea without significantly more.
Response to Arguments
8. Applicant’s arguments filled on 08/18/2025, with respect to the rejection of the amended claims 1-20 under 35 U.S.C. 102/103(a) have been fully considered and are persuasive. The rejection of claims 1-20 under 35 U.S.C. 102/103(a) have been withdrawn.
9. The previous claims were determined to be obvious under the combination of Markman et al. (U.S. Pub. No. 2020/0372090), Chen (U.S. Pub. No. 2021/0144251), Hoffman et al. (U.S. Pub. No. 2018/0174070) and Choudhary (U.S. Pub. No. 2023/0342022).
10. Markman teaches at operation 1020, the recommendation system 216 identifies a plurality of online postings for which the user has performed at least one of a plurality of online actions within a particular sliding window of time defining a most recent time period (see at least paragraphs 0057 and 0075).
11. Chen teaches the at least one processor is configured to cause the system to perform operations including: performing, based on a dialogue request, a smart dialogue communication with a requester terminal device associated with a requester, the dialogue request being associated with an incoming call request initiated by the requester via the requester terminal device; obtaining incoming voice messages associated with the smart dialogue communication; converting the incoming voice messages into incoming text messages; determining event keywords by performing semantic analysis on the incoming text messages; generating schedule information based on the event keywords; and transmitting the schedule information to a responder terminal device associated with the incoming call request for display (see at least paragraphs 0019 and 0058).
12. Hoffman teaches user representations are mapped from content manipulation applications to online content services to generate recommendations in the online content services. Online content services include social media services, collaborative creative services such as Behance®, and other Web- based services that allow users to purchase, post, view, or otherwise access online content from one or more online sources (see at least paragraph 0023).
13. Choudhary teaches A TensorFlow’s Keras sequential model used with dense layers (see at least paragraphs 0075, 0117 and 0123-0124).
14. Koohmarey et al. (U.S. Pub. No. 2024/0106694) discloses at 302, parameters associated with a plurality of alerts are obtained. In some embodiments, the parameters include values of specified alert fields. The specified alert fields are typically a subset of all available alert fields. Examples of alert fields include various metrics (e.g., latency, saturation, number of errors), service (e.g., a specific service product provided to end users, such as a specific software program or entertainment content item), IT resource (e.g., a specific computing component, such as a specific server rack), and so forth. In various embodiments, field values are vectorized in preparation for clustering. Vectorization refers to conversion of data in a non-numerical format (e.g., text) to a set of numerical values that can be mapped to a point in a vector space. Various vectorization approaches can be utilized. For example, a word vectorization technique such as continuous bag of words (CBOW), skip gram, or another technique that creates numerical representations of words can be utilized to generate numerical representations of text in alert fields (see at least paragraph 0031).
15. Although these references teach or suggest some part of the independent claims, these references do not teach or suggest the amended claims, identifying, by one or more processors of a server computing device, areal time sequence of user actions for a plurality of listings by a specific user within a sliding window of time; generating, by the one or more processors, a first representation for the sequence of user actions using an encoder component of a personalization module to encode content and position of the sequence of user actions; generating, by the one or more processors, a second representation for the sequence of user actions using a pretrained representations component of the personalization module to encode listing identifiers of the plurality of listings as a sequence representation of a vector; generating, by the one or more processors, a third representation for the sequence of user actions using a learned representations component of the personalization module to embed the sequence of user actions in a vector space for a given task.
16. Applicant's arguments filed 08/18/2025 with respect to the rejection of claims 1-21 under 35 U.S.C. 101 have been fully considered but they are not persuasive.
17. Applicant argues that “…TU]nder Prong Two, a claim that recites a judicial exception is not directed to that judicial exception, if the claim as a whole integrates the recited judicial exception into a practical application of that exception.” MPEP 2106.04(ID(A)(2). “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.” MPEP 2106.04(d)(II)…”; Remarks pages 6-10
18. Examiner notes that the applicant's arguments with regards to the 35 USC 101 rejection are not convincing. The only " additional elements" in the claims as amended are personalization module, server computing device, one or more processor and one or more memory. Every other limitation in the claims as amended appear to be part of the abstract idea itself. As such, when considering the claims as a whole, the claims merely apply an abstract idea using a general-purpose computer with generic computer components which is insufficient to transform an abstract idea into a practical application under Step 2a, Prong 2 and/or insufficient to be considered significantly more under Step 2b. The rejection has been maintained.
18. Applicant argues that “…Regarding Step 2B, “The second part of the A/ice/Mayo test is often referred to as a search for an inventive concept.” MPEP § 2106.05(1). “Evaluating additional elements to determine whether they amount to an inventive concept requires considering them both individually and in combination to ensure that they amount to significantly more than the judicial exception…” Remarks pages 11-12
19. Examiner notes that In order to overcome a 35 USC 101 rejection under Step 2b it is the “additional elements” that must be considered “significantly more”. Additional elements are defined as those elements outside of the identified abstract idea itself. In the instant case, the only “additional elements” found in the claim are server computing device, which is merely a general-purpose computer upon which the abstract idea is being applied. Thus, the additional elements cannot be considered significantly more than the abstract idea. The purported improvement of the technology of using real time sequences of user actions to provide “a set of results for display to the specific used based on the short-tern personalized representation” for that specific user in the manner claimed is part of the abstract idea itself and, as such, cannot be considered “significantly more” than the abstract idea under Step 2b. Thus, the rejection has been maintained.
Conclusion
20. 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.
21. Any inquiry concerning this communication or earlier communications from the examiner should be directed to MARILYN G MACASIANO whose telephone number is (571)270-5205. The examiner can normally be reached Monday-Friday 12:00-9:00 pm.
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/MARILYN G MACASIANO/Primary Examiner, Art Unit 3622 12/11/2025
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