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and the fee set forth in 37 CFR 1.17(e) has been timely paid, the finality of the previous Office action has been withdrawn pursuant to 37 CFR 1.114.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 05/29/2026 has been entered.
Response to Arguments
35 U.S.C 103
Applicant’s arguments filed with respect to the rejection(s) of claims 1-5, 7-21 under U.S.C 103 have been fully considered and are persuasive. Therefore, the rejection has been withdrawn. However upon further consideration and in light of Applicant’s amendments, new grounds of rejection are made in view of Ni (U.S Pub # 20190278857).
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 1-3, 7-11, 15, 17 are rejected under 35 U.S.C. 103 as being unpatentable over Ni (U.S Pub # 20190278857) in view of Li (U.S Pub # 20080147637) and in further view of Manavoglu (U.S Pub # 20080154858).
With regards to claim 1, Ni discloses a system comprising: at least one processor; and memory storing instructions that, when executed by the at least one processor, cause the system to perform a set of operations, the set of operations comprising:
receive a query ([0036] receive a query);
generate an initial set of query results ([0037] search results);
provide the query and initial set of query results to a generative large language model ([0037] query machine learning processor may process the query);
receive at least one additional query from the machine learning model , the at least one additional query generated by the machine learning model based on a determination that the initial set of query results does not satisfy an intent associated with the first query, and directed to information not explicitly requested by the first query ([0037] query machine learning processor may identify that the word likely lacks context based on search results returned using the word (e.g., many differing results for a word may indicate a likelihood that the word lacks context, etc.). [0038] Upon identifying that the query should be reformulated, the context machine learning processor 160 may process previously submitted queries 120 and results from the previously submitted queries. [0041] query formulator 165 may reformulate or generate a new query 120 based on the relationships. In an example, the query 120 may be reformulated by generation of a new query by replacing the word of the query 120 with the member of the set of context words. In another example, the query 120 may be reformulated by generation a new query 120 by adding the member of the set of context words to the quer);
execute the at least one additional query ([0041] retrieve query results for reformulated query);
provide the results from the at least one additional query to the generative large language model ([0142] Inputs of the conversational query understanding engine 145 may include: context (e.g., conversation history) which includes previous queries 120 and results 170 which are evaluated by the context machine learning processor 160, and current input query 120 which may be evaluated by the query machine learning processor 150).
Ni does not disclose however Li discloses:
receiving a summary of semantic search engine results from the machine learning model that synthesizes information from the initial set of query results and the results from the at least one additional query ([0078] in another embodiment, a blending of original query result and second query results are sent to the user).
It would have been obvious for one of ordinary skill in the art before the date the current invention was effectively filed to have modified the system of Ni by the system of Li to generate additional queries and sent an aggregated search result of different queries to a user.
One of ordinary skill in the art would have been motivated to make this modification in order to help locate resources that are accessible through the internet (Li [0003]).
Ni does not disclose however Manavoglu discloses:
wherein the summary of the semantic search engine results includes one or more citation links to the one or more underlying data sources for the results from the at least one additional query (Fig. 6 # 652, 654 [0071] clickable link that may reference a site. URL 653 may represent the URL of the site referred to by the clickable link); and
wherein a first section of the summary includes at least one citation link that is generated by the machine learning model and identifies a first underlying data source for a corresponding semantic search engine result ([0071] description 656 may be used in the machine learning document categorization of the site referred to by the link 652, or the machine learning document categorization may analyze the entire content of the site referenced by the link 652),
wherein the at least one citation link enables redirection to the first underlying data source for the corresponding semantic search engine result derived from the at least one query ([0071] If one the users 120A-N, such as the user A 120A, clicks on the link 652, the user A 120A may be forwarded to the site referred to by the link);
providing the summary of the semantic search engine results including the one or more citation links (Fig. 6 [0071] search result summary).
It would have been obvious for one of ordinary skill in the art before the date the current invention was effectively filed to have modified the system of Ni and Li by the system of Manavoglu to generate citation links in a search result summary.
One of ordinary skill in the art would have been motivated to make this modification in order to target data on a site referenced on a page based on a condition (Manavoglu [0004]).
Claims 10 and 17 correspond to claim 1 and are rejected accordingly.
With regards to claim 2, Ni further discloses:
generate one or more alternate queries based upon the first query, and wherein generating the initial set of query results comprised generating alternate query results based upon the one or more additional queries ([0055] provide multiple queries based on the previous).
Claim 21 corresponds to claim 2 and is rejected accordingly.
With regards to claim 3, Ni does not disclose however Manavoglu discloses:
wherein the machine learning model is a generative large language model, and wherein the summary is generated by the generative large language model ([0071] describe the sites in the results with machine learning).
It would have been obvious for one of ordinary skill in the art before the date the current invention was effectively filed to have modified the system of Ni and Li by the system of Manavoglu to generate citation links in a search result summary.
One of ordinary skill in the art would have been motivated to make this modification in order to target data on a site referenced on a page based on a condition (Manavoglu [0004]).
Claims 15, 16 and 20 correspond to claim 3 and are rejected accordingly.
With regards to claim 7, Ni further discloses:
determining an intent or a task based upon the received query, wherein the intent or the task is provided to the machine learning model ([[0037] identify context of query).
With regards to claim 8, Ni further discloses:
determine, using the machine learning model, whether additional information is required, wherein the determination is based upon the intent or task ([0039] identify missing context).
With regards to claim 9, Ni further discloses:
wherein the at least one additional query is generated by the generative large language model when it is determined that an additional information is required ([0041] generate new query based on context).
With regards to claim 11, Ni further discloses:
analyzing the query to determine an intent or a task based upon the query, wherein analyzing the query comprises providing the query to at least one of the machine learning model or an alternate machine learning model ([0037] determine query context).
Claims 4-5 are rejected under 35 U.S.C. 103 as being unpatentable over Ni (U.S Pub # 20190278857) in view of Li (U.S Pub # 20080147637) and in further view of Manavoglu (U.S Pub # 20080154858) and Konam (U.S Pub # 20230223016).
With regards to claim 4, Ni does not disclose however Konam discloses:
wherein a format for the summary is determined based upon a type of information included in the summary ([0048] format summary based on identified key terms).
It would have been obvious for one of ordinary skill in the art before the date the current invention was effectively filed to have modified the system of Ni, Li and Manavoglu by the system of Konam to format a summary generated by a large language model.
One of ordinary skill in the art would have been motivated to make this modification in order to form a to analyze and output categorized elements among a transcript (Konam [0004]).
With regards to claim 5, Ni does not disclose however Konam discloses:
wherein a format for the summary is determined based upon a template provided to the generative large language model ([0055] format based on formatting guidelines).
It would have been obvious for one of ordinary skill in the art before the date the current invention was effectively filed to have modified the system of Ni, Li and Li by the system of Konam to format a summary generated by a large language model.
One of ordinary skill in the art would have been motivated to make this modification in order to form a to analyze and output categorized elements among a transcript (Konam [0004]).
Claims 12-14, 18-19 are rejected under 35 U.S.C. 103 as being unpatentable over Ni (U.S Pub # 20190278857) in view of Li (U.S Pub # 20080147637) and in further view of Manavoglu (U.S Pub # 20080154858). and Shabat (U.S Pub # 20240203404).
With regards to claim 12, Ni does not disclose however Shabat discloses:
determining a format for the semantic search engine results, wherein the format is determined based upon the query or the task (Fig. 2 [0047] format for response based on type of information).
It would have been obvious for one of ordinary skill in the art before the date the current invention was effectively filed to have modified the system of Ni, Li and Manavoglu by the system of Shabat to format a response based on received input.
One of ordinary skill in the art would have been motivated to make this modification in order to generate output based on received audio data input (Shabat [0020]).
Claim 18 corresponds to claim 12 and is rejected accordingly.
With regards to claim 13, Ni does not disclose however Shabat discloses:
generating a prompt for the machine learning model, wherein the prompt is generated based upon the format ([0047] intent can also be used as a template for what the automated assistant has said or will say).
It would have been obvious for one of ordinary skill in the art before the date the current invention was effectively filed to have modified the system of Ni, Li and Manavoglu by the system of Shabat to format a response based on received input.
One of ordinary skill in the art would have been motivated to make this modification in order to generate output based on received audio data input (Shabat [0020]).
Claim 19 corresponds to claim 13 and is rejected accordingly.
With regards to claim 14, Ni does not disclose however Shabat discloses:
a template associated with the format, wherein the template defines the format for the semantic search engine results ([0047] intent can also be used as a template for what the automated assistant has said or will say).
It would have been obvious for one of ordinary skill in the art before the date the current invention was effectively filed to have modified the system of Ni, Li and Manavoglu by the system of Shabat to format a response based on received input.
One of ordinary skill in the art would have been motivated to make this modification in order to generate output based on received audio data input (Shabat [0020]).
Conclusion
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/TONY WU/ Primary Examiner, Art Unit 2166
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