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 .
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 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.
Status of Claims
Claims 1-2, 5-9, 12-16, and 19-20 remain pending, and are rejected.
Claims 3-4, 10-11, and 17-18 have been cancelled.
Response to Arguments
Applicant’s arguments filed on 1/12/2026 with regard to the rejection under 35 U.S.C. 101 have been fully considered, but are not persuasive for at least the following rationale:
Applicant’s arguments filed on 1/12/2026 with respect to the rejection under 35 U.S.C. 101 for claims directed to a judicial exception are not persuasive.
Notably, on pages 8-9 of the Applicant’s Remarks, arguments are made that the claims do not recite a judicial exception, and are directed to how a user interface interacts and renders components to improve search and retrieval for a user of an online system, such as by generating or expanding a second list of recommended items below the suggested query when the user clicks or hovers over the suggested query, and are rooted in computer technology. Arguments are made that the claims provide a technical improvement over prior online systems, such as an improved UI for search and retrieval interfaces.
Examiner respectfully disagrees. The body of the claims are not directed to any interface functionalities, but are directed to the steps of determining suggestions of queries for recommended items. The limitations of the claim only recite the interface elements at the end of the claim such as to display the results of the abstract idea on a user interface using generic interface elements to display information. The cited paragraphs of the specification also do not disclose the interface elements with any particular detail, merely disclosing displaying the second list of recommended items in a panel that can be expanded below the suggested query. The generic description of the interface elements show that it is not a particular functionality that improves interface technology, and is not a focus of the claims or the invention. An improved method of displaying the results of the abstract idea only improves the abstract idea itself, and does not provide any changes or technical improvements to a technical field.
In view of the above, the rejection under 35 U.S.C. 101 has been maintained below.
Applicant’s arguments filed on 1/12/2026 with respect to the rejection under 35 U.S.C. 103 have been fully considered, but are moot in light of new grounds of rejection. Applicant’s amendments necessitated 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 1-20 are rejected under 35 U.S.C. 101 because the claims are directed to a judicial exception without significantly more.
Step 1:
Claims 1-7 are directed to a method, which is a process. Claims 8-14 are directed to a non-transitory computer-readable storage medium, which is an article of manufacture. Claim 15-20 are directed to a system, which is an apparatus. Therefore, claims 1-20 are directed to one of the four statutory categories of invention.
Step 2A (Prong 1):
Taking claim 15 as representative, claim 15 sets forth the following limitations reciting the abstract idea of suggesting queries for a user based on an input query or the recommended items:
receiving, an input search query;
generating a list of recommended items as a response to the input query, wherein the list of recommended items retrieved are related to the input query;
presenting the list of recommended items to the user;
generating a prompt for input, the prompt specify at least content of the input query or the list of recommended items, and a request to formulate suggested queries related to the input query or the list of recommended items;
providing the prompt to a model;
receiving a response generated by executing the model on the prompt;
parsing the response from the model to extract a set of suggested queries;
presenting the set of suggested queries adjacent to the list of recommended items as a user is entering the input query;
wherein the second list of recommended items is related to the suggested query and comprises a response to the suggested query.
The recited limitations above set forth the process for suggesting queries for a user based on an input query or recommended items. These limitations amount to certain methods of organizing human activity, including commercial or legal transactions (e.g. agreements in the form of contracts, advertising, marketing or sales activities or behaviors, etc.). The claims are directed to determining queries to suggest based on an input query and the recommended items from that query (see specification [0002] disclosing the searching for a list of items from a provider), which is an advertising and marketing activity. The limitations also amount to mental processes, including observation and evaluation. The claims are directed to using an input query and recommended items in an algorithm (analysis) to determine suggested queries, which are activities of observation and evaluation. Such concepts have been identified by the courts as abstract ideas (see: MPEP 2106.04(a)(2)).
Step 2A (Prong 2):
Examiner acknowledges that representative claim 15 recites additional elements, such as:
a computer processor;
a non-transitory computer-readable storage medium;
a client device;
a search element on a user interface;
machine-learned language model;
responsive to receiving an indication that the user clicked or hovered over a suggested query, generating or expanding a panel UI element below the suggested query and presenting a second list of recommended items with the panel UI element.
Taken individually and as a whole, representative claim 15 does not integrate the recited judicial exception into a practical application of the exception. The additional elements do no more than generally link the use of a judicial exception to a particular technological environment or field of use.
Furthermore, this is also because the claim fails to (i) reflect an improvement in the functioning of a computer, or an improvement to other technology or technical field, (ii) implement a judicial exception with a particular machine, (iii) effect a transformation or reduction of a particular article to a different state or thing, or (iv) apply the judicial exception in some other meaningful way beyond generally linking the use of the judicial exception to a particular technological environment.
While the claims recite a computer processor and non-transitory computer-readable storage medium, these elements are recited with a very high level of generalization. The specification does not provide any particular disclosure to the processor except in paragraph [0085], which merely describes the processor as comprising one or more processors or processing units that perform the steps of instructions. The non-transitory computer-readable storage medium is also disclosed without much description, except that it stores information (specification: [0086]). As such, it is evident that these elements are generic computing components that merely execute the abstract idea, such that it is performed on a computer. The client device is disclosed in specification paragraph [0014] as any personal or mobile computing device, such as a smartphone, tablet, laptop computer, or desktop computer. As such, it is clear the client device merely represents the user within a computing environment, and the user interface is merely functions as any user interface to provide a general link to a computing environment. Paragraph [0036] discloses the machine-learned language model as any of a transformer-based architecture, LSTM, Markov networks, BART, GAN, diffusion models, and the like. Furthermore, the claims do not recite any of the underlying technology of the machine learned models and merely receives an input to provide an output. As such, it is evident that the machine learned models are any generic machine learning model that is merely applied to the abstract idea to provide an output of data.
In view of the above, under Step 2A (Prong 2), representative claim 15 does not integrate the recited exception into a practical application (see: MPEP 2106.04(d)).
Step 2B:
Returning to representative claim 15, taken individually or as a whole, the additional elements of claim 15 do not provide an inventive concept (i.e. whether the additional elements amount to significantly more than the exception itself). As noted above, the additional elements recited in claim 15 are recited in a generic manner with a high level of generality and only serve to implement the abstract idea on a generic computing device. The claims result only in an improved abstract idea itself and do not reflect improvements to the functioning of a computer or another technology or technical field. As discussed above with respect to the integration of the abstract idea into a practical application, the additional elements used to perform the claimed process ultimately amount to no more than the mere instructions to apply the exception using a generic computer and/or no more than a general link to a technological environment.
Even when considered as an ordered combination, the additional elements of claim 15 do not add anything further than when they are considered individually.
In view of the above, claim 15 does not provide an inventive concept under step 2B, and is ineligible for patenting.
Regarding Claim 1 (method): Claim 1 recites at least substantially similar concepts and elements as recited in claim 15 such that similar analysis of the claims would be readily apparent to one of ordinary skill in the art. As such, claims 1 is rejected under at least similar rationale as provided above regarding claim 15.
Regarding Claim 8 (non-transitory computer-readable storage medium): Claim 8 recites at least substantially similar concepts and elements as recited in claim 15 such that similar analysis of the claims would be readily apparent to one of ordinary skill in the art. As such, claims 8 is rejected under at least similar rationale as provided above regarding claim 15.
Dependent claims 2-7, 9-14, and 16-20 recite further complexity to the judicial exception (abstract idea) of claim 15, such as by further defining the algorithm of suggesting queries for a user based on an input query or the recommended items, and do not recite any further additional elements. Thus, each of claims 2-7, 9-14, and 16-20 are held to recite a judicial exception under Step 2A (Prong 1) for at least similar reasons as discussed above.
Under prong 2 of step 2A, the additional elements of dependent claims 2-7, 9-14, and 16-20 also do not integrate the abstract idea into a practical application, considered both individually or as a whole. More specifically, dependent claims 2-7, 9-14, and 16-20 rely on at least similar elements as recited in claim 15. Further additional elements are also acknowledged (e.g., a panel UI element (claim 4); an application programming interface (claim 6); a transformer architecture (claim 7)); however, the additional elements of claims 2-7, 9-14, and 16-20 are recited only at a high level of generality (i.e. as generic computing hardware) such that they amount to nothing more than the mere instructions to implement or apply the abstract idea on generic computing hardware (or, merely uses a computer as a tool to perform an abstract idea). Further, the additional elements do no more than generally link the use of a judicial exception to a particular technological environment or field of use (such as the Internet or computing networks).
Secondly, this is also because the claims fails to (i) reflect an improvement in the functioning of a computer, or an improvement to other technology or technical field, (ii) implement the judicial exception with, or use the judicial exception in conjunction with, a particular machine or manufacture that is integral to the claim, (iii) effect a transformation or reduction of a particular article to a different state or thing, or (iv) applies or uses the judicial exception in some other meaningful way beyond generally linking the use of the judicial exception to a particular technological environment.
Taken individually and as a whole, dependent claims 2-7, 9-14, and 16-20 do not integrate the recited judicial exception into a practical application of the exception under step 2A (prong 2).
Lastly, under step 2B, claims 2-7, 9-14, and 16-20 also fail to result in “significantly more” than the abstract idea under step 2B. The dependent claims recite additional functions that describe the abstract idea and use the computing device to implement the abstract idea, while failing to provide an improvement to the functioning of a computer, another technology, or technical field. The dependent claims fail to confer eligibility under step 2B because the claims merely apply the exception on generic computing hardware and generally link the exception to a technological environment.
Even when viewed as an ordered combination (as a whole), the additional elements of the dependent claims do not add anything further than when they are considered individually.
Taken individually or as an ordered combination, the dependent claims simply convey the abstract idea itself applied on a generic computer and are held to be ineligible under Steps 2B for at least similar rationale as discussed above regarding claim 15. Thus, dependent claims 2-7, 9-14, and 16-20 do not add “significantly more” to the abstract idea.
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 1-2, 6, 8-9, 13, 15-16, and 20 are rejected under 35 U.S.C. 103 as being unpatentable by Wan (US 20210097063 A1) in view of Boteanu (US 11,036,801 B1), and in further view of Bai (US 20170147680 A1).
Regarding Claim 1: Wan discloses a method comprising:
receiving, from a client device, an input search query via a search element on a user interface generated on the client device; (Wan: [0037] – “Search component 136 includes an interface that enables users and/or automatic processes to initiate searches of entity data store 132 or session data store 134 or content system 150 and to retrieve results of those searches. Thus, search component 136 may provide a user interface to allow users of entity system 110 to search entity data store”; Wan: [0084] – “a target query is identified in the session data using a first temporal constraint. An example of an approach for identifying a target query is described above in connection with training data generation component 144, 200. In an embodiment, block 322 includes identifying the target query by determining a query of the at least three search queries that has a most recent timestamp data”).
generating a list of recommended items as a response to the input query, wherein the list of recommended items retrieved are related to the input query; (Wan: [0039] – “Notification component 140 generates and delivers electronic content, such as search results, search recommendations, and notifications, to user accounts of users of entity management system 130. Examples of electronic notifications include synchronous or asynchronous messages, alerts, news feed items, recommendations, listings of search results”
presenting the list of recommended items to the user interface of the client device; (Wan: [0039] – “delivers electronic content, such as search results, search recommendations, and notifications, to user accounts of users of entity management system 130. Examples of electronic notifications include synchronous or asynchronous messages, alerts, news feed items, recommendations, listings of search results”).
generating a prompt for input to a machine-learned language model, the prompt specify at least content of the input query or the list of recommended items, and a request to formulate suggested queries related to the input query or the list of recommended items; (Wan: [0079] – “in response to a search query, the learned model produced by block 306 is used to generate a related query. An example of a mechanism that can be used to generate the related query is shown in FIG. 3F, described below. In an embodiment, block 308 includes using the learned model to generate at least one recommended query that is semantically related to a new query, in response to the new query”).
providing the prompt to a model serving system for execution by the machine-learned language model; (Wan: [0079] – “in response to a search query, the learned model produced by block 306 is used to generate a related query”).
receiving, from the model serving system, a response generated by executing the model machine-learned language model on the prompt; (Wan: [0079] – “in response to a search query, the learned model produced by block 306 is used to generate a related query. An example of a mechanism that can be used to generate the related query is shown in FIG. 3F, described below. In an embodiment, block 308 includes using the learned model to generate at least one recommended query that is semantically related to a new query”; Wan: [0080] – “generating at least one recommended query using the learned model and a vocabulary of words extracted from the at least one search log based on frequency of occurrence of the words in the at least one search log. In an embodiment, block 308 includes generating the at least one recommended query by the learned model iteratively selecting words from the vocabulary according to a probability”).
parsing the response from the model serving system to extract a set of suggested queries; (Wan: [0080]- “generating at least one recommended query using the learned model and a vocabulary of words extracted from the at least one search log based on frequency of occurrence of the words in the at least one search log. In an embodiment, block 308 includes generating the at least one recommended query by the learned model iteratively selecting words from the vocabulary according to a probability”).
Wan does not explicitly teach a method comprising:
presenting the set of suggested queries on the user interface of the client device as a user of the client device is entering the input query in the search element;
presenting one or more suggested queries adjacent to the list of recommended items;
responsive to receiving an indication that the user clicked or hovered over a suggested query, generating or expanding a panel UI element below the suggested query and presenting a second list of recommended items within the panel UI element, wherein the second list of recommended items is related to the suggested query and comprises a response to the suggested query.
Notably, however, Wan does disclose displaying recommended queries adjacent to the search input box and generating a notification in response to the recommended queries, which includes search results (Wan: [0081]; [0039]).
To that accord, Boteanu does teach a method comprising:
presenting the set of suggested queries on the user interface of the client device as a user of the client device is entering the input query in the search element; (Boteanu: col. 18, ln. 58-col. 19, ln. 3 – “auto-completion in the search query is more relevant using query assists, so that when an query is provided for “headphones,” then the search bar suggests “headphones . . . for airplane travel” or plainly, provides an selectable link of “for running” as an available result or for selection. In response to a query for “backpacks,” for instance, the search bar suggests “for parents” or “for hiking” based on these terms appearing in reviews left by customers who previously purchased select items using the query in searches prior to the current search provided. The present method and system supplements other methods of query suggestion, for example based on frequency of usage”; Boteanu: Fig. 4, #420 displaying suggested queries as the input query is being entered).
presenting one or more suggested queries adjacent to the list of recommended items; (Boteanu: col. 16, ln. 58-col 17, ln. 16 – “responsive to a new query that may be determined as associated with a stored query, a query assist menu 420 may be provided. Query assist menu 420 at least modifies the first interface. The query assist menu 420 may also be provided over the popular products of the first interface. In the query assist menu 420, there is area 420A provided for one or more query assists—e.g., “Shoes for Running ‘Sneakerun's sneaker is the lightest running . . . ’ 420B, “Shoes for Hiking” 420C, and “Shoes for Cold Weather Climbing” 420D. The query assist includes selectable links titled with the query and descriptors or portions of descriptors, as explained with respect to FIGS. 2 and 3. In an alternate implementation, an area 416A may be provided in interface 402 with the query assist for the query. On selection of one of the selectable links, the interface is modified (or only area 404 is modified) to display items of the listed items that are associated to a descriptor underlying the selected selectable link. Furthermore, the modification to the interface may be to rearrange or rank the displayed items as most relevant to the selected selectable link. One of ordinary skill would understand that example 400 provides results 410-414 in interface 402 as an example only, but that if the query is not submitted, then the query assist menu 420 may be provided over any prior listing of items or results to invite a selection from the user entering the query”; Boteanu: Fig. 4, #420,418,410 displaying the suggested queries over the search results).
It would have been obvious to one of ordinary skill in the art, before the effective filing date of the claimed invention, to modify the invention of Wan disclosing the system of determining recommended queries using a machine learning model with the presenting suggested queries as the user is entering the input query as taught by Boteanu. One of ordinary skill in the art would have been motivated to do so in order to reduce latency issues of requesting additional pages from the server (Boteanu: col. 1, ln. 15-27).
Wan in view of Boteanu does not explicitly teach responsive to receiving an indication that the user clicked or hovered over a suggested query, generating or expanding a panel UI element below the suggested query and presenting a second list of recommended items within the panel UI element, wherein the second list of recommended items is related to the suggested query and comprises a response to the suggested query.
Notably, however, Wan does disclose displaying recommended queries adjacent to the search input box and generating a notification in response to the recommended queries, which includes search results (Wan: [0081]; [0039]).
To that accord, Bai does teach a method comprising:
responsive to receiving an indication that the user clicked or hovered over a suggested query, generating or expanding a panel UI element below the suggested query and presenting a second list of recommended items within the panel UI element, wherein the second list of recommended items is related to the suggested query and comprises a response to the suggested query. (Bai: [0035] – “The suggestion engine 170 may further allow the user to preview the search results 165 that would be generated by the search engine 160 from a particular query suggestion 163 if the user were to select the user interface element corresponding to the query suggestion 163. For example, if the user hovers a finger above a user interface element, or selects the user interface element for a predetermined duration or with a predetermined force, rather than replace the GUI 175 with search results 165 corresponding to the query suggestion 163 corresponding to the user interface element, the suggestion engine 170 may generate a preview window that displays some or all of the search results 165 to the user in the GUI 175 or other user interface”).
It would have been obvious to one of ordinary skill in the art, before the effective filing date of the claimed invention, to modify the invention of Wan in view of Boteanu disclosing the system of determining recommended queries using a machine learning model with the clicking of a suggested query to generate a second list of recommended items responsive to the suggested query as taught by Bai. One of ordinary skill in the art would have been motivated to do so in order to display the results without replacing the contents of the GUI (Bai: [0048]).
Regarding Claim 2: Wan in view of Boteanu and Bai discloses the limitations of claim 1 above.
Wan does not explicitly teach wherein the set of suggested queries are placed below the list of recommended items or above the list of recommended item on the user interface. Notably, however, Wan does disclose displaying recommended queries adjacent to the search input box (Wan: [0081]).
To that accord, Boteanu does teach presenting one or more suggested queries adjacent to the list of recommended items; (Boteanu: col. 16, ln. 58-col 17, ln. 16 – “responsive to a new query that may be determined as associated with a stored query, a query assist menu 420 may be provided. Query assist menu 420 at least modifies the first interface. The query assist menu 420 may also be provided over the popular products of the first interface. In the query assist menu 420, there is area 420A provided for one or more query assists—e.g., “Shoes for Running ‘Sneakerun's sneaker is the lightest running . . . ’ 420B, “Shoes for Hiking” 420C, and “Shoes for Cold Weather Climbing” 420D. The query assist includes selectable links titled with the query and descriptors or portions of descriptors, as explained with respect to FIGS. 2 and 3. In an alternate implementation, an area 416A may be provided in interface 402 with the query assist for the query. On selection of one of the selectable links, the interface is modified (or only area 404 is modified) to display items of the listed items that are associated to a descriptor underlying the selected selectable link. Furthermore, the modification to the interface may be to rearrange or rank the displayed items as most relevant to the selected selectable link. One of ordinary skill would understand that example 400 provides results 410-414 in interface 402 as an example only, but that if the query is not submitted, then the query assist menu 420 may be provided over any prior listing of items or results to invite a selection from the user entering the query”; Boteanu: Fig. 4, #420,418,410 displaying the suggested queries over the search results).
It would have been obvious to one of ordinary skill in the art, before the effective filing date of the claimed invention, to modify the invention of Wan disclosing the system of determining recommended queries using a machine learning model with the presenting suggested queries below or above the list of recommended items as taught by Boteanu. One of ordinary skill in the art would have been motivated to do so in order to reduce latency issues of requesting additional pages from the server (Boteanu: col. 1, ln. 15-27).
Regarding Claim 6: Wan in view of Boteanu and Bai discloses the limitations of claim 1 above.
Wan further discloses wherein providing the prompt comprises making an application programming interface (API) call to an API of the model serving system. (Wan: [0028] – “Event interface 112 may be implemented as a user interface operable by one or more end users of entity management system 130 and/or as an application program interface (API) through which other components and/or systems may interact with entity management system”).
Regarding Claims 8 and 15: Claims 8 and 15 recite substantially similar limitations as claim 1. Therefore, claims 8 and 15 are rejected under the same rationale as claim 1 above.
Regarding Claims 9 and 16: Claims 9 and 16 recite substantially similar limitations as claim 2. Therefore, claims 9 and 16 are rejected under the same rationale as claim 2 above.
Regarding Claims 13 and 20: Claims 13 and 20 recite substantially similar limitations as claim 6. Therefore, claims 13 and 20 are rejected under the same rationale as claim 6 above.
Claims 5, 12, and 19 are rejected under 35 U.S.C. 103 as being unpatentable by the combination of Wan (US 20210097063 A1), Boteanu (US 11,036,801 B1), and Bai (US 20170147680 A1), in view of Yoon (US 11,748,413 B1).
Regarding Claim 5: The combination of Wan, Boteanu, and Bai discloses the limitations of claim 1 above.
The combination does not explicitly teach a method comprising:
obtaining a second set of suggested queries related to the input query;
generating a dropdown element below the search interface presenting the second set of suggested queries to the user.
Notably, however, Wan does disclose generating a set of query recommendations (Wan: [0040]).
To that accord, Yoon does teach a method comprising:
obtaining a second set of suggested queries related to the input query; (Yoon: claim 2 – “generating code effective to cause a second natural language query suggestion associated with the third search string to be displayed on the display of the user, wherein the second natural language query suggestion is displayed as a second suggested search string for querying the online item catalog”).
generating a dropdown element below the search interface presenting the second set of suggested queries to the user. (Yoon: col. 6, ln. 38-50 – “Query reformulator 142 may search the query index 140 to determine if a natural language query corresponds to the string data generated by query reformulator 142 from various combinations of keywords 144 and/or the input search query. If a natural language query stored in query index 140 corresponds to the input string data, query reformulator 142 may determine whether or not greater than a threshold number of search results (e.g., greater than a threshold number of items) is associated with the natural language query. If so, the natural language query may be sent by query reformulator 142 as one of the suggested queries 150 (e.g., for display in a drop down menu (or output as an audio suggestion and/or output in another manner) on an interface of computing device”).
It would have been obvious to one of ordinary skill in the art, before the effective filing date of the claimed invention, to modify the invention of the combination of Wan, Boteanu, and Bai disclosing the system of determining recommended queries using a machine learning model with the generating of a UI element below the suggested query with the second set of suggested queries and displaying a dropdown element as taught by Yoon. One of ordinary skill in the art would have been motivated to do so in order to provide more accurate queries representative of what the user intends (Yoon: col. 1, ln. 17-31).
Regarding Claims 12 and 19: Claims 12 and 19 recite substantially similar limitations as claim 5. Therefore, claims 12 and 19 are rejected under the same rationale as claim 5 above.
Claims 7 and 14 are rejected under 35 U.S.C. 103 as being unpatentable by the combination of Wan (US 20210097063 A1 , Boteanu (US 11,036,801 B1), and Bai (US 20170147680 A1), in view of Zhao (US 20230133522 A1).
Regarding Claim 7: The combination of Wan, Boteanu, and Bai discloses the limitations of claim 1 above.
The combination does not explicitly teach wherein the machine-learned language model has a transformer architecture including one or more attention layers. Notably, however, Wan does disclose a machine learning model to determine the recommended queries, including various attention layers (Wan: [0100]; see also: [0090]; [0098]). Wan does not explicitly disclose a transformer architecture.
To that accord, Zhao does teach a transformer architecture. (Zhao: [0067] – “FIG. 6 depicts an example 600 of the machine-learning module 122 as incorporating a transformer architecture. A transformer architecture is a type of machine-learning model that employs an attention mechanism to weight significance of each of the items in the sequence for generating an output, e.g., the search result 620. The sequence data 208 is obtained form an entity 602 corresponding to a received search query and describes items 604 of digital content 110 and corresponding queries 606 used to locate the digital content. An embedding module 608 is implemented to generate embedding data 610 using a query-aware embedding layer 612. Transformer layers 614 then process the embedding data 610 to generate transformer output data 616 that is utilized by a predictor layer 618 to generate the search result”).
It would have been obvious to one of ordinary skill in the art, before the effective filing date of the claimed invention, to modify the invention of the combination of Wan, Boteanu, and Bai disclosing the system of determining recommended queries using a machine learning model with the generating of a UI element below the suggested query with the model having a transformer architecture as taught by Zhao. One of ordinary skill in the art would have been motivated to do so in order to weight significance of an entity corresponding to a received search query (Zhao: [0067]).
Regarding Claim 14: Claim 14 recites substantially similar limitations as claim 7. Therefore, claim 14 is rejected under the same rationale as claim 7 above.
Conclusion
Applicant's amendment necessitated the new ground(s) of rejection presented in this Office action. Accordingly, THIS ACTION IS MADE FINAL. See MPEP § 706.07(a). 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.
Any inquiry concerning this communication or earlier communications from the examiner should be directed to TIMOTHY J KANG whose telephone number is (571)272-8069. The examiner can normally be reached Monday - Friday: 7:30 - 5:00.
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If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Maria-Teresa Thein can be reached at 571-272-6764. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
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/T.J.K./Examiner, Art Unit 3689
/VICTORIA E. FRUNZI/Primary Examiner, Art Unit 3689 3/27/2026