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 .
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and the fee set forth in 37 CFR 1.17(e) has been timely paid, the finality of the previous Office action has been withdrawn pursuant to 37 CFR 1.114.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 11/06/2025 has been entered.
Status of the Claims
Claims 1, 8, 10, 15 have been amended. Claims 1, 3-8 and 10-20 are pending.
Priority
The later-filed application must be an application for a patent for an invention which is also disclosed in the prior application (the parent or original nonprovisional application or provisional application). The disclosure of the invention in the parent application and in the later-filed application must be sufficient to comply with the requirements of 35 U.S.C. 112(a) or the first paragraph of pre-AIA 35 U.S.C. 112, except for the best mode requirement. See Transco Products, Inc. v. Performance Contracting, Inc., 38 F.3d 551, 32 USPQ2d 1077 (Fed. Cir. 1994).
The disclosure of the prior-filed application, Application No. 63/520,266, fails to provide adequate support or enablement in the manner provided by 35 U.S.C. 112(a) or pre-AIA 35 U.S.C. 112, first paragraph for the limitation “substantially reducing the amount of data processing and computational resources required for the second search engine compared to searching the entire document corpus” in the independent claims and thereof do not receive the benefit of the priority filing date. Co-pending applications must provide written description support for the claimed invention under 35 U.S.C. 112(a) (e.g., must provide support to show both possession and enablement of the claimed subject matter such as an algorithm, process, flowchart, or the like for the limitation in order for the earlier priority date to be recognized for the limitation noted above.
Claim Rejections - 35 USC § 112
The following is a quotation of the first paragraph of 35 U.S.C. 112(a):
(a) IN GENERAL.—The specification shall contain a written description of the invention, and of the manner and process of making and using it, in such full, clear, concise, and exact terms as to enable any person skilled in the art to which it pertains, or with which it is most nearly connected, to make and use the same, and shall set forth the best mode contemplated by the inventor or joint inventor of carrying out the invention.
The following is a quotation of the first paragraph of pre-AIA 35 U.S.C. 112:
The specification shall contain a written description of the invention, and of the manner and process of making and using it, in such full, clear, concise, and exact terms as to enable any person skilled in the art to which it pertains, or with which it is most nearly connected, to make and use the same, and shall set forth the best mode contemplated by the inventor of carrying out his invention.
Claims 1, 3-8 and 10-20 are rejected under 35 U.S.C. 112(a) or 35 U.S.C. 112 (pre-AIA ), first paragraph, as failing to comply with the written description requirement. The claim(s) contains subject matter which was not described in the specification in such a way as to reasonably convey to one skilled in the relevant art that the inventor or a joint inventor, or for applications subject to pre-AIA 35 U.S.C. 112, the inventor(s), at the time the application was filed, had possession of the claimed invention.
Independent claims recite limitation – “substantially reducing the amount of data processing and computational resources required for the second search engine compared to searching the entire document corpus.” This limitation is not supported by the specification as originally filed.
In order to perform the comparison a specific mathematical formula requires for such calculations. The specification does not disclose such calculations. Making assumptions in view of the specification does not provide a proper disclose.
The dependent claims further carry the same deficiency and likewise rejected.
The following is a quotation of 35 U.S.C. 112(b):
(b) CONCLUSION.—The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the inventor or a joint inventor regards as the invention.
The following is a quotation of 35 U.S.C. 112 (pre-AIA ), second paragraph:
The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the applicant regards as his invention.
Claims 1, 3-8 and 10-20 are rejected under 35 U.S.C. 112(b) or 35 U.S.C. 112 (pre-AIA ), second paragraph, as failing to set forth the subject matter which the inventor or a joint inventor, or for applications subject to pre-AIA 35 U.S.C. 112, the applicant regards as the invention.
Independent claims 1, 8, 15 recite limitations "the entire", “the amount” and claims 1, 8 further recite - “the sequence” and “the second search engine”. There are insufficient antecedent basis for these limitations in the claim. For the purposes of examining it is assumed it was meant “an entire", “an amount”, “second search engine” and “a sequence.”
Further, independent claims 1, 8 recite limitation – “substantially reducing the amount of data processing and computational resources required for the second search engine compared to searching the entire document corpus.” It is not clear what is required by the limitation. I.e. the reduction in the data processing is an end result of limiting the search to the first documents, as processing smaller amount of data logically might require less resources. However, it is not clear if the claim requires – step 1 - performing entire document corpus search, measuring the resources and the amount of data, step 2, performing a search only within the first documents, measuring the resources and the amount of data and - step 3, comparing the amount of data and the computational resources. It seems the limitation is directed to an intended use and end result of performing a search only within the first documents without any clear functionality.
Further the term "substantially" is a relative term which renders the claim indefinite. The specification does not define what substantial reduction is the amount of data processing and computational resources needs to be achieved. Claim 15 recites similar discrepancies. Due to the 35 USC 112 rejections, the claims have been treated on their merits as best understood by the examiner.
The dependent claims further carry the same deficiency and likewise rejected.
Claim Objections
Claims 7 and 14 are objected to because of the following informalities: claims failed to further limit the independent claims and are essentially duplicates of the independent claims. Appropriate correction is required.
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, 3-8, 10-14 is/are rejected under 35 U.S.C. 103 as being unpatentable over Hudetz et al. (US 20240370479) in view of Andreev (US 20150278198) and in further view of Sommer et al. (US 6847966).
Regarding claim 1, Hudetz teaches a computer-implemented method for searching electronic documents, comprising:
receiving a first natural language semantic search query from a user via a user interface ([0053], [0167]-[0168]) to semantically search a document corpus using a vector index of a plurality of semantically embedded text snippets ([0142]-[0143], [0148]), said vector index facilitating efficient retrieval operations by indexing contextual information for the sequence of words in the text snippets ([0180], [0224]);
servicing the first natural language semantic search query to return a first search result ([0194]), the first search result identifying first documents from the document corpus that are determined to be semantically relevant to the semantic search query ([0148], [0239]-[0240]),
wherein the first search result is presented as a plurality of citations, each citation comprising a chunk of text from a semantically relevant snippet (F17:1706-1712, [0158], [0183]);
receiving a second lexical search query from the user via the user interface, the second lexical search query comprising search criteria input by the user ([0048] “perform lexical searching, semantic searching, or a combination of both”, [0082], [0131], [0155], [0239])(see NOTE I); and
servicing the second lexical search query to perform a lexical search of the document corpus, wherein the lexical search is constrained to operate only within the first documents identified in the first search result ([0131], [0147] “drilling down on more specific search questions in follow-up to reviewing previous search results 146”, [0155] “compute a new relevance score over the first set of search results 146 ", [0158] “document corpus returned from the initial result set is analyzed”; “adding an information field with a parameter indicating a type of search, such as "lexical" or "semantic"”, [0131], [0283] “Additional query generator may be configured to form a query based on … any prior query responses”, [0303] “use determined context of the agreement, its abstractive summary and/or responses to prior queries, to generate a response to the additional query”) to return a second search result ([0155], [0197], [0239]) based on a user selection of one or more of the plurality of citations to return a second search result relevant to the second lexical search query ([0318], [0322], note that context information for additional searches that can include citations [0243], [0255], [0262], F22:2202, 2204) (see NOTE II),
thereby substantially reducing the amount of data processing and computational resources required for the second search engine ([0143] “enabling efficient search and retrieval of information”, [0273] “reduce an amount of processing that may need to be performed”)
NOTE I Hudetz teaches the present system provides “improved search tools and algorithms to perform lexical searching, semantic searching, or a combination of both”, which “may use the lexical search generator to perform lexical searching in response to a search query” and “may use the semantic search generator to perform semantic searching in response to a search query” and “generate a first set of lexical search results, and … iterate over the first set of lexical search results to generate a second set of semantic search results. Embodiments are not limited in this context” [0131].
Thus, given that lexical and semantic searches are in response to a search query from the user, it would be obvious to one of ordinary skill in the art that a “combination” of such searches can surely allow for various embodiments, such as semantic search to be the first query and a lexical query to be a second query type searching within the semantic results. He show in various embodiments that the semantic query is the first query, which returns “initial result set” (see [0155], [0158]). Given that lexical and semantic searches are performed within the corpus of documents ([0041] “Lexical searching is a process of searching for a particular word or group of words within a given text or corpus”, [0048] “Semantic search … locating the relevant information within an electronic document” also see [0239]), then it is only obvious that the lexical search can be the “second search query from the user to perform a second type of search the document corpus.”
However, to merely obviate such reasoning, Andreev discloses servicing the semantic search query to return a first search result ([0033] “performing semantic searches and clustering search results based on user specified queries”, [0036]) and receiving a second search query from the user to perform a second type of search the document ([0033] “results … clustered by their lexical meanings … allow a user to enter the query and select lexical meanings for one or more words in the selected query … search is performed not only using the words specified in the query, but also the words in specific lexical meanings”, [0072], [0081], [0085]).
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 teachings of Hudetz to search semantic results with a different type of query as disclosed by Andreev. Doing so would allow the user to check all variants of meanings of the searched word or word combination and enables searches of not just words or word forms, but of the lexical meaning (Andreev [0001], [0066]).
NOTE II Once again, Hudetz teaches performing “lexical searching, semantic searching, or a combination of both” a single set of search results 146, which can be returned by either lexical or semantic searching – “semantic search generator to iterate over the first set of lexical search results 146 to generate a second set of semantic search results 146”; “use the lexical search … to perform lexical searching in response to a search query 144 … may use the semantic search … to perform semantic searching in response to a search query 144.”
Thus, there is only a single set or search results – 146 and a single query 144. However, a query 144, which can include subsequent queries 144 (see [0197] “a subsequent search query 144”), can be either one - semantic or lexical (defined by the same number 144), which produces either semantic or lexical search results (defined by the same number 146). It is reasonable and obvious to conclude that the subsequent second query 144 (semantic or lexical) which “iterate over the first set of lexical search results 146” can be either one – semantic or lexical, given that the searching can be “a combination of both.” I.e. the search query 144 (which can be semantic or lexical) iterating, searching over search results 146 (which can be semantic or lexical) obviously and reasonably produces all possible combinations of searchings’ – lexical search over the semantic results and a semantic search over the lexical results.
Therefore, it is reasonable and obvious to conclude that given that the semantic query and the lexical query are defined by the same number 144 and a subsequent search query is defined by the same number 144 (which means the subsequent search query 144 can also be semantic or lexical) and the semantic results and the lexical results are defined by the same number 146, produces all possible combinations of searching and is limiting such searching to only search result 146 (which can be semantic or lexical) and satisfies the limitation – “lexical search is constrained to operate only within the first documents identified in the first search result.”
Still, if Hudetz does not explicitly teach, Sommer discloses search is constrained to operate only within the first documents identified in the first search result to return a second search result (C3L54-67 “A term search is accomplished using the Boolean query to search the inverted index to obtain a filtered subset S of matching documents”, C4L3-15).
Hudetz does not explicitly teach, however Sommer discloses thereby substantially reducing the amount of data processing and computational resources required for the second search engine compared to searching the entire document corpus (C12L5-22, C13L18-20, 35-40, C14L21-30, C15L10-19, C16L27-50, C23L10-40).
It would have been obvious to one of ordinary skill in the art at the time of invention to modify the teachings of He as modified to constrain the second lexical search to the first documents and substantially reducing the amount of data processing as disclosed by Sommer. Doing so provides an efficient and significant search for achieving overall optimized results (Sommer C19L31-35).
Claim 8 recites substantially the same limitations as claim 1, and is rejected for substantially the same reasons.
Regarding claims 3 and 10, Hudetz as modified teaches the method and the medium, further comprises:
providing the first search result to the user in the graphical user interface; and receiving, via user interaction with the graphical user interface, an indication to constrain the second lexical search to the first documents (Hudetz F15-17, [0131], [0147] “drilling down on more specific search questions in follow-up to reviewing previous search results 146”, [0155] “compute a new relevance score over the first set of search results 146 ", [0158] “document corpus returned from the initial result set is analyzed”; “adding an information field with a parameter indicating a type of search, such as "lexical" or "semantic"”, [0131], [0283] “Additional query generator may be configured to form a query based on … any prior query responses”, [0303] “use determined context of the agreement, its abstractive summary and/or responses to prior queries, to generate a response to the additional query”, Andreev [0033], Sommer C12L5-22, C13L18-20, 35-40, C14L21-30, C15L10-19, C16L27-50, C23L10-40).
Regarding claims 4 and 11, Hudetz as modified teaches the method and the medium, further comprising automatically constraining the second lexical search to the first documents (Hudetz F15-17, [0131], Andreev [0033]-[0035], [0079]-[0080], [0084]-[0085], Sommer C12L5-22, C13L18-20, 35-40, C14L21-30, C15L10-19, C16L27-50, C23L10-40).
Regarding claims 5 and 12, Hudetz as modified teaches the method and the medium, wherein servicing the semantic search query comprises:
sending a request to a large language model, the request comprising a prompt to the large language model, the prompt comprising the semantic search query (Hudetz [0137]-[0138], [0159], [0217]-[0236], [0205]);
receiving generative text generated by the large language model in response to the prompt; and including the generative text with the first search result (Hudetz F17:1706-1712, F26-28).
NOTE in analogous art Mukherjee (US 20240354436) likewise teaches claims 5 and 12 in [0046], [0113], [0138], [0146], [0154]-[0155] and further obviates the teaching of Hudetz as modified.
Regarding claims 6 and 13, Hudetz as modified teaches the method and the medium, wherein the request to the large language model includes context to constrain the large language model to the first documents when generating the generative text (Hudetz F13:1308, wherein a “subset” of documents is a constrain, [0155] “compute a new relevance score over the first set of search results 146 ", [0158] “document corpus returned from the initial result set is analyzed”; “adding an information field with a parameter indicating a type of search, such as "lexical" or "semantic"”, [0131], [0283] “Additional query generator may be configured to form a query based on … any prior query responses”, [0303] “use determined context of the agreement, its abstractive summary and/or responses to prior queries, to generate a response to the additional query”).
Regarding claims 7 and 14, Hudetz e as modified teaches the method and the medium, wherein the first search result comprises citations, the citations including chunks of text from the first documents (Hudetz F17:1706-1712, [0158], [0183], Andreev [0063]-[0065]).
Regarding claim 15, Hudetz teaches a computer system proving enhanced search, the computer system comprising:
storage storing: a plurality of snippets, each of the plurality of snippets comprising snippet text extracted from a document in a document corpus and a reference to the document from which the snippet text of that snippet was extracted (F17:1706-1712, [0158], [0183]);
an embedding store comprising a vector index of the plurality of semantically embedded snippets, wherein the vector index facilitates efficient retrieval operations by indexing contextual information for a sequence of words in a respective snippet text ([0142]-[0143], [0148], [0180], [0224]); a processor (F2:104);
a semantic search engine executable to perform semantic searching of the document corpus using the vector index perform semantic searching of the document corpus using the vector index to return a first search result identifying first documents from the document corpus that are determined to be semantically relevant to the semantic search query ([0148], [0194], [0239]-[0240]),
wherein the first search result is presented as a plurality of citations, each citation comprising a chunk of text from a semantically relevant snippet (F17:1706-1712, [0158], [0183]);
a lexical search engine executable to perform lexical searching of the document corpus ([0048] “perform lexical searching, semantic searching, or a combination of both”, [0082], [0131], [0155], [0239])(see NOTE I); and
a user interface, wherein the user interface is executable to receive a user selection of one or more of the plurality of citations from the first search result ([0318], [0322], note that context information for additional searches that can include citations [0243], [0255], [0262], F22:2202, 2204) and is further executable to scope lexical searches by the lexical search engine to operate only within the first documents identified by the user selection of the one or more citations ([0131], [0147] “drilling down on more specific search questions in follow-up to reviewing previous search results 146”, [0155] “compute a new relevance score over the first set of search results 146 ", [0158] “document corpus returned from the initial result set is analyzed”; “adding an information field with a parameter indicating a type of search, such as "lexical" or "semantic"”, [0131], [0283] “Additional query generator may be configured to form a query based on … any prior query responses”, [0303] “use determined context of the agreement, its abstractive summary and/or responses to prior queries, to generate a response to the additional query”)(see NOTE II), thereby substantially reducing the amount of data processing and computational resources required for the lexical search engine ([0143] “enabling efficient search and retrieval of information”, [0273] “reduce an amount of processing that may need to be performed”)
NOTE I Hudetz teaches the present system provides “improved search tools and algorithms to perform lexical searching, semantic searching, or a combination of both”, which “may use the lexical search generator to perform lexical searching in response to a search query” and “may use the semantic search generator to perform semantic searching in response to a search query” and “generate a first set of lexical search results, and … iterate over the first set of lexical search results to generate a second set of semantic search results. Embodiments are not limited in this context” [0131].
Thus, given that lexical and semantic searches are in response to a search query from the user, it would be obvious to one of ordinary skill in the art that a “combination” of such searches can surely allow for various embodiments, such as semantic search to be the first query and a lexical query to be a second query type searching within the semantic results. He show in various embodiments that the semantic query is the first query, which returns “initial result set” (see [0155], [0158]). Given that lexical and semantic searches are performed within the corpus of documents ([0041] “Lexical searching is a process of searching for a particular word or group of words within a given text or corpus”, [0048] “Semantic search … locating the relevant information within an electronic document” also see [0239]), then it is only obvious that the lexical search can be the “second search query from the user to perform a second type of search the document corpus.”
However, to merely obviate such reasoning, Andreev discloses servicing the semantic search first ([0033] “performing semantic searches and clustering search results based on user specified queries”, [0036]) and a lexical search engine executable to perform lexical searching of the document corpus as a second search ([0033] “results … clustered by their lexical meanings … allow a user to enter the query and select lexical meanings for one or more words in the selected query … search is performed not only using the words specified in the query, but also the words in specific lexical meanings”, [0072], [0081], [0085]).
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 teachings of Hudetz to first perform a semantic search and perform lexical search as a second search as disclosed by Andreev. Doing so would allow the user to check all variants of meanings of the searched word or word combination and enables searches of not just words or word forms, but of the lexical meaning (Andreev [0001], [0066]).
NOTE II Hudetz teaches iterating over the returned search results (which can be lexical or semantic), searching within the previously returned results and generating additional queries based on the returned results, which construed to be analogous to the limitation “scope lexical searches by the lexical search engine to operate only within the first documents.”
Still, if Hudetz does not explicitly teach, Sommer discloses servicing the second lexical search query to perform a lexical search of the document corpus, wherein the lexical search is constrained to operate only within the first documents identified in the first search result to return a second search result (C3L54-67 “A term search is accomplished using the Boolean query to search the inverted index to obtain a filtered subset S of matching documents”, C4L3-15).
Hudetz does not explicitly teach, however Sommer discloses thereby substantially reducing the amount of data processing and computational resources required for the second search engine compared to searching the entire document corpus (C12L5-22, C13L18-20, 35-40, C14L21-30, C15L10-19, C16L27-50, C23L10-40).
It would have been obvious to one of ordinary skill in the art at the time of invention to modify the teachings of He as modified to constrain the second lexical search to the first documents and substantially reducing the amount of data processing as disclosed by Sommer. Doing so provides an efficient and significant search for achieving overall optimized results (Sommer C19L31-35).
Claims 16-20 and alternatively claims 6-7, 13 is/are rejected under 35 U.S.C. 103 as being unpatentable over Hudetz as modified and in further view of Mukherjee et al. (US 20240354436).
Regarding claim 16, Hudetz as modified teaches the computer system of Claim 15, wherein:
the semantic search engine is executable to: search the vector index using an embedded query string from a first search input to identify, from the plurality of snippets, semantically relevant snippets that are semantically relevant to the first search input (Hudetz [0142]-[0143], [0148], [0180], [0224]); and
return a corresponding semantic search result to the user interface, the corresponding semantic search result comprising document
the user interface is executable to generate a lexical search request to the lexical search engine to perform a corresponding lexical search, the lexical search request comprising search criteria input by a user (Hudetz [0048] “perform lexical searching, semantic searching, or a combination of both”, [0082], [0131], [0155], [0239]) and the document
Hudetz as modified does not explicitly teach, however Mukherjee discloses search result comprising document identifiers ([0087], [0110]).
It would have been obvious to one of ordinary skill in the art at the time of invention to modify the teachings of Hudetz as modified to include document identifiers as disclosed by Mukherjee. Doing so would allow more efficiently locate and access the most similar portions of the set of documents for generating a prompt to the LLM (Mukherjee [0087]).
Regarding claim 17, Hudetz as modified teaches the computer system of Claim 16, wherein the user interface is executable to:
display the corresponding semantic search result to the user (Hudetz F17, Mukherjee F8-9); and
receive, based on a user interaction with the user interface, an indication from the user to scope the corresponding lexical search to the documents identified by the document identifiers from the semantically relevant snippets (Hudetz [0185], [0119], Andreev [0033]-[0035], [0085], Mukherjee [0087], F8:808-818).
Regarding claim 18, Hudetz as modified teaches the computer system of Claim 17, wherein the corresponding semantic search result comprises a plurality of citations and wherein the indication to scope the corresponding lexical search comprises a selection of one or more citations from the plurality of citations, wherein each of the one or more citations corresponds to one of semantically relevant snippets (Hudetz [0171], [0174], Andreev [0063]-[0065], Mukherjee [0087], F8:808-818).
Regarding claim 19, Hudetz as modified teaches the computer system of Claim 18, wherein the user interface is executable to:
automatically scope the corresponding lexical search to the documents identified by the document identifiers from the semantically relevant snippets (Hudetz F15-17, [0131], [0147] “drilling down on more specific search questions in follow-up to reviewing previous search results 146”, [0155] “compute a new relevance score over the first set of search results 146 ", [0158] “document corpus returned from the initial result set is analyzed”; “adding an information field with a parameter indicating a type of search, such as "lexical" or "semantic"”, [0131], [0283] “Additional query generator may be configured to form a query based on … any prior query responses”, [0303] “use determined context of the agreement, its abstractive summary and/or responses to prior queries, to generate a response to the additional query”, Sommer C12L5-22, C13L18-20, 35-40, C14L21-30, C15L10-19, C16L27-50, C23L10-40 ,Andreev [0033]-[0035], [0079]-[0080], [0084]-[0085], Mukherjee [0045], [0053], [0088], [0091]).
Regarding claim 20, Hudetz as modified teaches the computer system of Claim 16, wherein the corresponding semantic search result comprises generative text generated by a large language model based on the semantically relevant snippets (Hudetz [0137]-[0138], [0159], [0217]-[0236], [0205], Mukherjee [0046], [0113], [0138], [0146], [0154]-[0155]).
Regarding claims 6 and 13, Hudetz as modified teaches the method and the medium, wherein the request to the large language model includes context to constrain the large language model to the first documents when generating the generative text (Hudetz F13:1308, wherein a “subset” of documents is a constrain, [0131], [0147], [0283], [0303]).
Hudetz teaches providing a “a subset of candidate document vectors from the set of candidate document vectors” to the LLM, which obviously constrain the large language model to the first set documents. Alternatively, to further obviate such reasoning Mukherjee teaches request to the large language model includes context to constrain the large language model to the first documents when generating the generative text ([0022] “utilizing one or more LLMs, with references to a set of documents”, [0008] “generate a prompt for the LLM based on portions of a set of documents similar to the user query for enabling natural language searching and response”).
Regarding claims 7 and 14, Mukherjee additionally discloses the method and the medium, wherein the first search result comprises citations, the citations including chunks of text from the first documents (F8:808-818, [0136]).
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 teachings of Hudetz to include constrain the large language model to the first documents and include document citations as disclosed by Mukherjee. Doing so would provide an efficient interactions between the user interfaces and underlying systems and components (Mukherjee [0012]-[0013]).
◊ Claims 1, 8 and 15 is/are alternatively rejected under 35 U.S.C. 103 as being unpatentable over Hudetz et al. (US 20240370479) in view of Andreev (US 20150278198) and in further view of PATHAK et al. (US 20250139136).
Hudetz does not explicitly teach, however PATHAK discloses substantially reducing the amount of data processing and computational resources required for the second search engine compared to searching the entire document corpus [0087].
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 teachings of Hudetz to include reduce the amount of data processing and computational resources required for the second search engine compared to searching the entire document corpus as disclosed by PATHAK. Doing so would enable efficiently and accurately process component queries because its focus of attention is restricted to a consideration of only some and not entire data (PATHAK [0088]).
Response to Arguments
Applicant's arguments, filed 11/06/2025, with respect to the previous rejections under 35 U.S.C. 101 have been fully considered and are persuasive in light of the amendments to independent claims.
Applicant's remaining arguments, in regard to the presently amended claims, are addressed in the updated rejections to the claims above. NOTE also see alternative rejection to the independent claims immediately above.
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure is indicated on PTO-892.
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/POLINA G PEACH/ Primary Examiner, Art Unit 2165 February 9, 2026