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 .
The instant office action having application number 19/275,588, filed on July 21, 2025, has claims 21-40 pending in this application.
Information Disclosure Statement
The information disclosure statement (IDS) submitted on July 21, 2025. The submission is in compliance with the provisions of 37 CFR 1.97. Accordingly, the information disclosure statement is being considered by the examiner.
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 21–41 are rejected under 35 U.S.C. §101 because the claimed invention is directed to a judicial exception without reciting significantly more.Step 2A, Prong One:
The claim recites “receiving, from a user device, a search modifier input associated with a combined search result set, the combined search result set being generated using two or more search operators, based on a search query and an initial set of weights; determining, using a machine learning (ML) model, an updated set of weights, based on the search modifier input and the search query; modifying a ranking of search results in the combined search result set, based on the updated set of weights, yielding a re-ranked search result set; and transmitting a signal to cause a display of the user device to provide output based on the re-ranked search result set.” These limitations recite mental processes and mathematical concepts because they evaluate information and apply weighting to organize and rank information.Step 2A, Prong Two:The additional elements (user device, ML model, display, transmitting signals) merely use generic computing technology as tools. The claim does not improve search engine architecture, indexing, embedding generation, computer performance, memory utilization, networking, or any other computer technology.Step 2B:The additional elements, individually and as an ordered combination, amount only to well-understood, routine, and conventional computer activities of receiving input, processing information, ranking data, and displaying results. Therefore, the claims lack an inventive concept.
The claim does not include additional elements that are sufficient to amount to significantly more than the judicial exception. The insignificant extra-solution activity identified above, which include the data gathering steps, is recognized by the courts as well-understood, routine, and conventional activity when they are claimed in a merely generic manner (e.g., at a high level of generality) or as insignificant extra-solution activity (See MPEP 2106.05(d)(II)(i) Receiving or transmitting data over a network, e.g., using the Internet to gather data, 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)). The claims are not patent eligible.
Claims 31 and 40 are rejected based on the same rationale as claim 1 above.
Claim 22 is dependent on claim 21 and includes all the limitations of claim 21. Therefore, claim 22 recites the same abstract idea of claim 21. The claim recites the additional limitations of “a category; a filter; or a metadata related to a user search session or a user account.”, which is further elaborating on the abstract idea, and therefore it does not amount to significantly more. Same rationale applies to claim 32.
Claim 23 is dependent on claim 21 and includes all the limitations of claim 21. Therefore, claim 23 recites the same abstract idea of claim 21. The claim recites the additional limitations of “transmitting a signal to cause the display of the user device to provide output based on the combined search result set, wherein the search modifier input is generated based on a user interaction with a displayed search result of the combined search result set.”, which is further elaborating on the abstract idea, and therefore it does not amount to significantly more. Same rationale applies to claim 33.
Claim 24 is dependent on claim 21 and includes all the limitations of claim 21. Therefore, claim 24 recites the same abstract idea of claim 21. The claim recites the additional limitations of “obtaining the combined search result set, the combined search result set having been generated by: querying, by the two or more search operators, embeddings databases to generate two or more initial search result sets having search results and associated scores, based on the search query; combining the two or more initial search result sets, based on a weighted ranking of the two or more initial search result sets, yielding the combined search result set, the weighted ranking obtained based on the initial set of weights and the associated scores for the two or more initial search result sets; and storing the combined search result set and associated scores.”, which is further elaborating on the abstract idea, and therefore it does not amount to significantly more. Same rationale applies to claims 25-28 and 34-38.
Claim 29 is dependent on claim 21 and includes all the limitations of claim 21. Therefore, claim 29 recites the same abstract idea of claim 21. The claim recites the additional limitations of “wherein the ML model has been trained to predict the updated set of weights, based on the search query and the search modifier input.”, which is further elaborating on the abstract idea, and therefore it does not amount to significantly more. Same rationale applies to claim 39.
Claim 30 is dependent on claim 21 and includes all the limitations of claim 21. Therefore, claim 30 recites the same abstract idea of claim 21. The claim recites the additional limitations of “wherein the search result set is a hybrid search result set, and the output is provided as a list of search results.” , which is further elaborating on the abstract idea, and therefore it does not amount to significantly more.
Double Patenting
The nonstatutory double patenting rejection is based on a judicially created doctrine grounded in public policy (a policy reflected in the statute) so as to prevent the unjustified or improper timewise extension of the “right to exclude” granted by a patent and to prevent possible harassment by multiple assignees. A nonstatutory double patenting rejection is appropriate where the conflicting claims are not identical, but at least one examined application claim is not patentably distinct from the reference claim(s) because the examined application claim is either anticipated by, or would have been obvious over, the reference claim(s). See, e.g., In re Berg, 140 F.3d 1428, 46 USPQ2d 1226 (Fed. Cir. 1998); In re Goodman, 11 F.3d 1046, 29 USPQ2d 2010 (Fed. Cir. 1993); In re Longi, 759 F.2d 887, 225 USPQ 645 (Fed. Cir. 1985); In re Van Ornum, 686 F.2d 937, 214 USPQ 761 (CCPA 1982); In re Vogel, 422 F.2d 438, 164 USPQ 619 (CCPA 1970); In re Thorington, 418 F.2d 528, 163 USPQ 644 (CCPA 1969).
A timely filed terminal disclaimer in compliance with 37 CFR 1.321(c) or 1.321(d) may be used to overcome an actual or provisional rejection based on nonstatutory double patenting provided the reference application or patent either is shown to be commonly owned with the examined application, or claims an invention made as a result of activities undertaken within the scope of a joint research agreement. See MPEP § 717.02 for applications subject to examination under the first inventor to file provisions of the AIA as explained in MPEP § 2159. See MPEP § 2146 et seq. for applications not subject to examination under the first inventor to file provisions of the AIA . A terminal disclaimer must be signed in compliance with 37 CFR 1.321(b).
The filing of a terminal disclaimer by itself is not a complete reply to a nonstatutory double patenting (NSDP) rejection. A complete reply requires that the terminal disclaimer be accompanied by a reply requesting reconsideration of the prior Office action. Even where the NSDP rejection is provisional the reply must be complete. See MPEP § 804, subsection I.B.1. For a reply to a non-final Office action, see 37 CFR 1.111(a). For a reply to final Office action, see 37 CFR 1.113(c). A request for reconsideration while not provided for in 37 CFR 1.113(c) may be filed after final for consideration. See MPEP §§ 706.07(e) and 714.13.
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Claims 21-40 are rejected on the ground of nonstatutory double patenting as being unpatentable over claims 1-20 of U.S. Patent No.12393597. Although the claims at issue are not identical, they are not patentably distinct from each other because claims 21-40 under examination are obvious, respectively, by claims 1-20 of the reference Patent. Every limitations in the instant application under examination claims are recited in the conflicting reference patent claims, and the differences or additional limitations between the claims are highlighted below by underlining and bolding all limitations.
Therefore, it would have been obvious to one having ordinary skill in the art before the effective filing date of the claimed invention to modify the independent claim 1, of the instant application to generating, by two or more search operators, two or more corresponding search result sets having search results and associated scores, based on the two or more query embeddings, wherein each of the two or more search operators is associated with a respective one of the two or more embedding generators; yielding a combined search result set, the weighted ranking obtained based on the determined weights and the associated scores for the two or more search result sets. Note, such deviation would not interfere with the functionality of the claims that are already patented, and would achieve the same end result.
Please, see the comparison table below:
Instant Application 19/275,588
Patent No. 12393597
21. (New) A computer-implemented method comprising: receiving, from a user device, a search modifier input associated with a combined search result set, the combined search result set being generated using two or more search operators, based on a search query and an initial set of weights; determining, using a machine learning (ML) model, an updated set of weights, based on the search modifier input and the search query; modifying a ranking of search results in the combined search result set, based on the updated set of weights, yielding a re-ranked search result set; and transmitting a signal to cause a display of the user device to provide output based on the re-ranked search result set.
31. (New) A computer system comprising: a processing unit configured to execute computer-readable instructions to cause the system to: receive, from a user device, a search modifier input associated with a combined search result set, the combined search result set being generated using two or more search operators, based on a search query and an initial set of weights; determine, using a machine learning (ML) model, an updated set of weights, based on the search modifier input and the search query; modify a ranking of search results in the combined search result set, based on the updated set of weights, yielding a re-ranked search result set; and transmit a signal to cause a display of the user device to provide output based on the re-ranked search result set.
40. (New) A non-transitory computer-readable medium storing instructions that, when executed by a processing unit of a computing system, cause the computing system to: receive, from a user device, a search modifier input associated with a combined search result set, the combined search result set being generated using two or more search operators, based on a search query and an initial set of weights; determine, using a machine learning (ML) model, an updated set of weights, based on the search modifier input and the search query; modify a ranking of search results in the combined search result set, based on the updated set of weights, yielding a re-ranked search result set; and transmit a signal to cause a display of the user device to provide output based on the re- ranked search result set.
1. A computer-implemented method comprising: receiving, from a user device, a search query; obtaining two or more query embeddings based on the search query, the two or more query embeddings being generated by corresponding two or more embedding generators; generating, by two or more search operators, two or more corresponding search result sets having search results and associated scores, based on the two or more query embeddings, wherein each of the two or more search operators is associated with a respective one of the two or more embedding generators; determining, using a machine learning model, weights for the two or more search result sets, based on the search query and the two or more embedding generators; combining the two or more search result sets, based on a weighted ranking of the two or more search result sets, yielding a combined search result set, the weighted ranking obtained based on the determined weights and the associated scores for the two or more search result sets; and transmitting a signal to cause a display of the user device to provide output based on the combined search result set.
11. A computer system comprising: a processing unit configured to execute computer-readable instructions to cause the system to: receive, from a user device, a search query; obtain two or more query embeddings based on the search query, the two or more query embeddings being generated by corresponding two or more embedding generators; generate, by two or more search operators, two or more corresponding search result sets having search results and associated scores, based on the two or more query embeddings, wherein each of the two or more search operators is associated with a respective one of the two or more embedding generators; determine, using a machine learning model, weights for each of the two or more search result sets, based on the search query and the two or more embedding generators; combine the two or more search result sets based on a weighted ranking of the two or more search result sets, yielding a combined search result set, the weighted ranking obtained based on the determined weights and the associated scores for the two or more search result sets; and transmit a signal to cause a display of the user device to provide output based on the combined search result set.
20. A non-transitory computer-readable medium storing instructions that, when executed by a processing unit of a computing system, cause the computing system to: receive, from a user device, a search query; obtain two or more query embeddings based on the search query, the two or more query embeddings being generated by corresponding two or more embedding generators; generate, by two or more search operators, two or more corresponding search result sets having search results and associated scores, based on the two or more query embeddings, wherein each of the two or more search operators is associated with a respective one of the two or more embedding generators; determine, using a machine learning model, weights for each of the two or more search result sets, based on the search query and the two or more embedding generators; combine the two or more search result sets based on a weighted ranking of the two or more search result sets, yielding a combined search result set, the weighted ranking obtained based on the determined weights and the associated scores for the two or more search result sets; and transmit a signal to cause a display of the user device to provide output based on the combined search result set.
"A later patent claim is not patentably distinct from an earlier patent claim if the later claim is obvious over, or anticipated by, the earlier claim. In re Longi, 759 F.2d at 896, 225 USPQ at 651 (affirming a holding of obviousness-type double patenting because the claims at issue were obvious over claims in four prior art patents); In re Berg, 140 F.3d at 1437, 46 USPQ2d at 1233 (Fed. Cir. 1998) (affirming a holding of obviousness-type double patenting where a patent application claim to a genus is anticipated by a patent claim to a species within that genus). " ELI LILLY AND COMPANY v BARR LABORATORIES, INC., United States Court of Appeals for the Federal Circuit, ON PETITION FOR REHEARING EN BANC (DECIDED: May 30, 2001).
The application claim 21 does not contain specific limitations as shown in the patent claim 1; however, according to In re Goodman, the application claim 21 is generic to the species of information covered by claim 1 of the patent. Thus, the generic invention is anticipated by the species of the patented invention.
The application claim 31 does not contain specific limitations as shown in the patent claim 11; however, according to In re Goodman, the application claim 31 is generic to the species of information covered by claim 11 of the patent. Thus, the generic invention is anticipated by the species of the patented invention.
The application claim 40 does not contain specific limitations as shown in the patent claim 20; however, according to In re Goodman, the application claim 40 is generic to the species of information covered by claim 20 of the patent. Thus, the generic invention is anticipated by the species of the patented invention.
Claim Rejections - 35 USC § 103
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, 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 21-23, 29-33 and 39-40 are rejected under 35 USC 103(a) as being unpatentable over Kulkarni (US 2019/0340256 A1) (hereinafter Kulkarni) in view of Qui et al. (US 10521469 B2) (hereinafter Qui).
As per claims 21, 31 and 40, Kulkarni discloses receiving, from a user device, a search modifier input associated with a combined search result set [receives search queries and displays via a user interface, search results representing a set of the records based on the search queries, abstract], the combined search result set being generated using two or more search operators [A search request 140 specifies certain search criteria, for example, search terms, logical operators specifying relations between search terms, paragraph 29], based on a search query and an initial set of weights [Schemes for weighting features, by search request, may be saved in the object store 160 or search logs store 270 as models. The training set for the models that will be used is a subset of the overall data set that is representative of the data to be ranked, including positive and negative examples of the ranking of objects on which the model is being trained, paragraph 61]; determining, using a machine learning (ML) model, an updated set of weights, based on the search modifier input and the search query [The search page displaying the search results may automatically update as search terms change, paragraph 118]; modifying a ranking of search results in the combined search result set, based on the updated set of weights, yielding a re-ranked search result set [The local ranking module 350 may re-rank search results or candidate objects received from the online system based on information available at the client device, for example, implicit user interactions., paragraph 103]; and transmitting a signal to cause a display of the user device to provide output based on the re-ranked search result set [The local ranking module 350 may re-rank search results or candidate objects received from the online system based on information available at the client device; The client device 110 displays 590 the second subset of records according to the ranked order, paragraph 103]. However Kulkarni does not explicitly disclose set of weights. On the other hand Qiu discloses set of weights [The combining unit 3014 is configured to separately combine, according to a calculation result of the weight calculating unit 3013, M.sub.q candidate words whose weights r.sub.I(ω.sub.I.sub.k.sup.i) are the largest in the candidate word set W.sub.I.sub.k with the initial keyword q, to obtain M.sub.q anchor concepts and form an anchor concept set C.sub.q,, col. 16, line 40]. Before the effective filing date of the claimed invention, it would have been obvious to one of ordinary skill in the art to combine ranking the candidate objects based on mode of input of the individual search query terms so as to provide user visibility into the effect of search query terms on the partial search query results as disclosed by Kulkarni with the calculating weight value of degree of correlation between anchor text concepts as taught by Qiu to enable accurately ordering search results, therefore relatively conforming search intention of a user.
As per claims 22 and 32, Kulkarni discloses wherein the search modifier input corresponds to at least one of: a category; a filter; or a metadata related to a user search session or a user account.
As per claims 23 and 33, Kulkarni discloses transmitting a signal to cause the display of the user device to provide output based on the combined search result set, wherein the search modifier input is generated based on a user interaction with a displayed search result of the combined search result set [input indicates the mechanism used by a user via the user interface to enter a particular search query term, for example, by performing a cut-and-paste operation, by performing a drag and drop operation, or by typing individual letters via the keyboard, paragraph 66].
As per claims 29 and 39, Kulkarni discloses wherein the ML model has been trained to predict the updated set of weights, based on the search query and the search modifier input [predicted search query terms may be presented to the user, for example, in a drop down list to allow the user to select for adding to the partial search query, paragraph 22].
As per claim 30, Kulkarni discloses wherein the search result set is a hybrid search result set, and the output is provided as a list of search results [Semantic tagging represents identifying the semantic concepts of a word or phrase. The query understanding module 205 may determine that in the example query, “curry” represents a person's name, “warriors” represents a sports team name, and “san francisco” represents a location, paragraph 77].
Allowable Subject Matter
Claims 24-28 and 34-38 are objected to as being dependent upon a rejected base claim, but would be allowable if overcome the 101 rejection above and rewritten in independent form including all of the limitations of the base claim and any intervening claims.
The primary reason for objecting to claims 24-28 and 34-38 is because the cited prior arts do not teach or suggest “obtaining the combined search result set, the combined search result set having been generated by: querying, by the two or more search operators, embeddings databases to generate two or more initial search result sets having search results and associated scores, based on the search query; combining the two or more initial search result sets, based on a weighted ranking of the two or more initial search result sets, yielding the combined search result set, the weighted ranking obtained based on the initial set of weights and the associated scores for the two or more initial search result sets; and storing the combined search result set and associated scores.”
Conclusion
Any inquiry concerning this communication or earlier communications from the examiner should be directed to NOOSHA ARJOMANDI whose telephone number is (571)272-9784. The examiner can normally be reached on (571)272-9784.
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July 8, 2026
/NOOSHA ARJOMANDI/Primary Examiner, Art Unit 2166
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