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 .
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 claimed invention is directed to an abstract idea without significantly more. Independent claims 1, 13, 20 similarly recite receive a first query indicating a request for one or more document objects and including one or more criteria for selection of the one or more document objects; identify one or more named entities from one or more portions of the first query; generate a second query to obtain the one or more document objects, in response to the one or more named entities being indicative of a context for the first query; obtain the one or more document objects according to the second query; generate a reply to the first query including a description object and the one or more document objects, the description object based on the first query; and cause a user interface to present the reply to the first query and the description object.
The limitations of identify one or more named entities from one or more portions of the first query; generate a second query to obtain the one or more document objects, in response to the one or more named entities being indicative of a context for the first query, as drafted, are processes that, under their broadest reasonable interpretation, cover mental processes but from the recitation of implementing them on generic computer components. That is nothing in the claim elements preclude the steps from practically being performed in the mind. For example, the limitations pertaining to “identify” and “generate” in the context of this claim encompass the user judging name entities of queries and judging a second query. If a claim limitation, under its broadest reasonable interpretation, covers performance of the limitation in the mind but for the recitation of generic computer components, then it falls within the “Mental Processes” grouping of abstract ideas. Accordingly, claims 1, 13, 20 recite an abstract idea (Step 2A, Prong 1).
This judicial exception is not integrated into a practical application. In particular, the claim recites the additional elements of – a system, comprising: one or more processors, coupled with memory, to:; A non-transitory computer readable medium including one or more instructions stored thereon and executable by one or more processors to: receive a first query indicating a request for one or more document objects and including one or more criteria for selection of the one or more document objects; obtain the one or more document objects according to the second query; generate a reply to the first query including a description object and the one or more document objects, the description object based on the first query; and cause a user interface to present the reply to the first query and the description object. The medium, memory, and processors are recited at a high-level of generality (i.e., as generic computer devices performing generic computer functions) and do not meaningfully limit the claim. The additional elements pertaining to “receive”, “obtain”, “generate” and “cause” represent insignificant extra-solution activities to the judicial exception with the “receiving” and “obtaining” being mere data gathering steps. Accordingly, these additional elements, individually and in combination, do not integrate the abstract idea into a practical application because they do not impose any meaningful limits on practicing the abstract idea (Step 2A, Prong 2).
The claims do not include additional elements that are sufficient to amount to significantly more than the judicial exception. As discussed above with respect to integration of the abstract idea into a practical application, The additional elements pertaining to “receive”, “obtain”, “generate” represent insignificant extra-solution activities that are well-understood, routine, and conventional activities previously known to the industry. That is, these limitations represent well-understood, routine, conventional activities in the fields of data processing and/or data storage and retrieval and are merely directed to the well-understood, routine, conventional activity of storing and retrieving information in memory, Versata Dev. Group, Inc. v. SAP Am., Inc., 793 F.3d 1306, 1334, 115 USPQ2d 1681, 1701 (Fed. Cir. 2015). The additional element pertaining to a user interface presenting represents insignificant extra-solution activities that are well-understood, routine, and conventional activities previously known to the industry. That is, these limitations represent well-understood, routine, conventional activities in the fields of data display and/or presentation and are merely directed to the well-understood, routine, conventional activity of presenting offers, OIP Technologies, 788 F.3d at 1363, 115 USPQ2d at 1092-93. Therefore, these limitations, both individually and in combination, fail to amount to an inventive concept because they merely append well-understood, routine, conventional activities previously known to the industry, specified at a high level of generality, to the judicial exception, and thus, do not cause the claim to amount to significantly more than the judicial exception. (Step 2B). Accordingly, claims 1, 13, 20 are not patent eligible.
Claims 2-12, 14-19 depend on claims 1, 13 and include all the limitations of these claims. Therefore, these claims are directed to the same abstract idea and the analysis must proceed to (Step 2A, Prong 2).
Claims 2, 14 similarly recite additional limitations pertaining to generating and presenting a second reply. The additional element pertaining to “generating” represents further mental process steps of judging a second reply. If a claim limitation, under its broadest reasonable interpretation, covers performance of the limitation in the mind but for the recitation of generic computer components, then it falls within the “Mental Processes” grouping of abstract ideas. This additional step is considered an abstract idea (mental process step) and does not integrate the judicial exception into a practical application. The additional limitations pertaining to presenting the second reply do not integrate the abstract idea into a practical application and merely represent insignificant extra-solution activities to the judicial exception and are mere data gathering steps. Accordingly, these additional elements do not integrate the abstract idea into a practical application because they do not impose any meaningful limits on practicing the abstract idea.
The claims do not include additional elements that are sufficient to amount to significantly more than the judicial exception. As discussed above with respect to integration of the abstract idea into a practical application, the additional elements represent further mental process steps and/or well-understood, routine, conventional activity previously known to the industry. That is, these limitations represent well-understood, routine, conventional activity in the fields of data display and presentation and are merely directed to the well-understood, routine, conventional activity of presenting offers, OIP Technologies, 788 F.3d at 1363, 115 USPQ2d at 1092-93. Therefore, these additional elements do not cause the claim to amount to significantly more than the judicial exception.
Claims 3, 15 similarly recite additional limitations pertaining to augmenting the context. This judicial exception is not integrated into a practical application. The additional elements represent further mental process steps of judging a refinement in the context based on recalled or observed chat history. If a claim limitation, under its broadest reasonable interpretation, covers performance of the limitation in the mind but for the recitation of generic computer components, then it falls within the “Mental Processes” grouping of abstract ideas. This additional step is considered an abstract idea (mental process step) and does not integrate the judicial exception into a practical application.
The claim does not include additional elements that are sufficient to amount to significantly more than the judicial exception. As discussed above with respect to integration of the abstract idea into a practical application, the additional elements represent further mental process steps. Therefore, these additional limitations are not sufficient to amount to significantly more than the judicial exception. Claims 3,15 is not patent eligible.
Claims 4, 16 similarly recite additional limitations pertaining to determining whether the named entities are indicative of the context. This judicial exception is not integrated into a practical application. The additional elements represent further mental process steps of judging whether the name entities are indicative. If a claim limitation, under its broadest reasonable interpretation, covers performance of the limitation in the mind but for the recitation of generic computer components, then it falls within the “Mental Processes” grouping of abstract ideas. This additional step is considered an abstract idea (mental process step) and does not integrate the judicial exception into a practical application.
The claim does not include additional elements that are sufficient to amount to significantly more than the judicial exception. As discussed above with respect to integration of the abstract idea into a practical application, the additional elements represent further mental process steps. Therefore, these additional limitations are not sufficient to amount to significantly more than the judicial exception. Claims 4, 16 are not patent eligible.
Claims 5, 17 similarly recite additional limitations pertaining to the context. This judicial exception is not integrated into a practical application. The additional elements represent further refinement of the mental process steps of the generating of the second query as in the independent claims, and, does not preclude this from being performed mentally. If a claim limitation, under its broadest reasonable interpretation, covers performance of the limitation in the mind but for the recitation of generic computer components, then it falls within the “Mental Processes” grouping of abstract ideas. This additional step is considered an abstract idea (mental process step) and does not integrate the judicial exception into a practical application.
The claim does not include additional elements that are sufficient to amount to significantly more than the judicial exception. As discussed above with respect to integration of the abstract idea into a practical application, the additional elements represent further mental process steps. Therefore, these additional limitations are not sufficient to amount to significantly more than the judicial exception. Claims 5, 17 are not patent eligible.
Claims 6, 18 similarly recite additional limitations pertaining to determining whether a reply indicates a match. This judicial exception is not integrated into a practical application. The additional elements represent further mental process steps of judging whether a reply indicates a match. If a claim limitation, under its broadest reasonable interpretation, covers performance of the limitation in the mind but for the recitation of generic computer components, then it falls within the “Mental Processes” grouping of abstract ideas. This additional step is considered an abstract idea (mental process step) and does not integrate the judicial exception into a practical application.
The claim does not include additional elements that are sufficient to amount to significantly more than the judicial exception. As discussed above with respect to integration of the abstract idea into a practical application, the additional elements represent further mental process steps. Therefore, these additional limitations are not sufficient to amount to significantly more than the judicial exception. Claims 6, 18 are not patent eligible.
Claims 7, 19 similarly recite additional limitations pertaining to a matching indicating obtaining. These additional limitations do not integrate the abstract idea into a practical application and merely represent insignificant extra-solution activities to the judicial exception and are mere data gathering steps. Accordingly, these additional elements do not integrate the abstract idea into a practical application because they do not impose any meaningful limits on practicing the abstract idea.
The claims do not include additional elements that are sufficient to amount to significantly more than the judicial exception. As discussed above with respect to integration of the abstract idea into a practical application, the additional elements represent well-understood, routine, conventional activity previously known to the industry. That is, these limitations represent well-understood, routine, conventional activity in the fields of data processing and/or data storage and retrieval and are merely directed to the well-understood, routine, conventional activity of storing and retrieving information in memory, Versata Dev. Group, Inc. v. SAP Am., Inc., 793 F.3d 1306, 1334, 115 USPQ2d 1681, 1701 (Fed. Cir. 2015). Therefore, these additional elements do not cause the claim to amount to significantly more than the judicial exception.
Claim 8 recites additional limitations pertaining to generating the reply based on a generative ai processor. This limitation represents insignificant extra-solution activities to the judicial exception. Further, the limitation pertaining to “generating the reply” is recited as being performed using generic computing components at a high level of generality. In this limitation, computing components are used as a tool to perform the generic computer function of (data retrieval/query processing). See MPEP 2106.05(f). This additional step is considered insignificant extra-solution activity and does not integrate the judicial exception into a practical application.
The claim does not include additional elements that are sufficient to amount to significantly more than the judicial exception. As discussed above with respect to integration of the abstract idea into a practical application, the additional elements represent further mental process steps. This additional element was found to be insignificant extra-solution activity in Step 2A, Prong Two, because it was determined to be insignificant limitations as data storage and retrieval. Therefore, these additional limitations are not sufficient to amount to significantly more than the judicial exception. Claim 8 is not patent eligible.
Claim 9 recites additional limitations pertaining to generating an investigative reply based on a generative ai processor. This judicial exception is not integrated into a practical application. The additional elements represent further mental process steps of generating an investigative reply. If a claim limitation, under its broadest reasonable interpretation, covers performance of the limitation in the mind but for the recitation of generic computer components, then it falls within the “Mental Processes” grouping of abstract ideas. Further, the limitation pertaining to “generating an investigative reply” is recited as being performed using generic computing components at a high level of generality. In this limitation, the computer is used to perform an abstract idea, as discussed above in Step 2A, Prong One, such that it amounts t9o no more than mere instructions to apply the exception using a generic computer. See MPEP 2106.05(f). The judicial exception of “generating an investigative reply” is performed “by a generative artificial intelligence processor executed by the one or more processors”. The generative artificial intelligence processor executed by the one or more processors is used to generally apply the abstract idea without placing any limits on how the generative artificial intelligence processor functions. Rather, these limitations only recite the outcome of “generative an investigative reply” and do not include any details about how the “generating” is accomplished. See MPEP 2106.05(f). The recitation of “generative artificial intelligence processor executed by the one or more processors” in the limitations also merely indicates a field of use or technological environment in which the judicial exception is performed. Although the additional element “generative artificial intelligence processor executed by the one or more processors” limits the identified judicial exceptions, this type of limitation merely confines the use of the abstract idea to a particular technological environment (artificial intelligence) and thus fails to add an inventive concept to the claims. See MPEP 2106.05(h). This additional step is considered an abstract idea (mental process step) and does not integrate the judicial exception into a practical application.
The claim does not include additional elements that are sufficient to amount to significantly more than the judicial exception. As discussed above with respect to integration of the abstract idea into a practical application, the additional elements represent further mental process steps. The additional element of “generative artificial intelligence processor executed by the one or more processors” in this limitation is at best mere instructions to “apply” the abstract ideas, which cannot provide an inventive concept. See MPEP 2106.05(f). Therefore, these additional limitations are not sufficient to amount to significantly more than the judicial exception. Claim 9 is not patent eligible.
Claims 10, 11 recite additional limitations pertaining to augmenting the context. This judicial exception is not integrated into a practical application. The additional elements represent further mental process steps of judging a refinement of context. If a claim limitation, under its broadest reasonable interpretation, covers performance of the limitation in the mind but for the recitation of generic computer components, then it falls within the “Mental Processes” grouping of abstract ideas. This additional step is considered an abstract idea (mental process step) and does not integrate the judicial exception into a practical application.
The claim does not include additional elements that are sufficient to amount to significantly more than the judicial exception. As discussed above with respect to integration of the abstract idea into a practical application, the additional elements represent further mental process steps. Therefore, these additional limitations are not sufficient to amount to significantly more than the judicial exception. Claims 10, 11 are not patent eligible.
Claim 12 recites additional limitations pertaining to generating enhancements of documents. This judicial exception is not integrated into a practical application. The additional elements represent further mental process steps of analyzing documents and judging a summarization of the document (in light of [0048] of instant specification). If a claim limitation, under its broadest reasonable interpretation, covers performance of the limitation in the mind but for the recitation of generic computer components, then it falls within the “Mental Processes” grouping of abstract ideas. This additional step is considered an abstract idea (mental process step) and does not integrate the judicial exception into a practical application.
The claim does not include additional elements that are sufficient to amount to significantly more than the judicial exception. As discussed above with respect to integration of the abstract idea into a practical application, the additional elements represent further mental process steps. Therefore, these additional limitations are not sufficient to amount to significantly more than the judicial exception. Claim 12 is not patent eligible.
Claim Rejections - 35 USC § 102
The following is a quotation of the appropriate paragraphs of 35 U.S.C. 102 that form the basis for the rejections under this section made in this Office action:
A person shall be entitled to a patent unless –
(a)(1) the claimed invention was patented, described in a printed publication, or in public use, on sale or otherwise available to the public before the effective filing date of the claimed invention.
Claims 1, 4-8, 10-13, 16-20 are rejected under 35 U.S.C. 102(a)(1) as being anticipated by Le (US 2018/0060387).
Regarding claim 1, Le discloses:
A system, comprising: one or more processors, coupled with memory, to: receive a first query indicating a request for one or more document objects and including one or more criteria for selection of the one or more document objects ([0017], [0066]-[0067] documents as search results [0043] user query received 400 [0078] query terms of query received);
identify one or more named entities from one or more portions of the first query ([0043] query tagging and identifying entities [0078]-[0079] entity matching and identification);
generate a second query to obtain the one or more document objects, in response to the one or more named entities being indicative of a context for the first query ([0062]-[0064] query rewritten);
obtain the one or more document objects according to the second query;
generate a reply to the first query including a description object and the one or more document objects, the description object based on the first query ([0065] Referring back to FIG. 3, the rewritten query may then be passed from the structuring module 320 to a query processor (not pictured) that performs a search on the query and returns search results to the ranking module 350 [0066]-[0067] documents ranked based on, for example, the match of the input query to the information within a document, personal information within the member profile of the searcher or result, and/or information pertaining to the professional network of the searcher or result [0069] reasons or descriptions associated with each of the query results) and the description objects is the reason for the match of the query result;
and cause a user interface to present the reply to the first query and the description object ([0069] a presentation module (not pictured) is configured to present query rewriting recommendations to the user, present search results according to their ranked order, present a reason associated with why the query result is being presented (e.g., such as a shared connection), and present the search results with category-selected highlighting).
As per claim 4, claim 1 is incorporated, Le further discloses:
comprising the one or more processors to: determine, by an orchestration agent processor, whether the one or more named entities are indicative of the context for the first query ([0041]-[0042] query rewriting module [0078] At operation 604, a standardized entity. taxonomy is searched to locate a standardized entity that most closely matches the query term. Then, at operation 606, a confidence score is calculated for the query term--standardized entity pair for the standardized entity that most closely matches the query term).
As per claim 5, claim 1 is incorporated, Le further discloses:
wherein the context is indicative of a set of document objects including the one or more document objects ([0065] the rewritten query may then be passed from the structuring module 320 to a query processor (not pictured) that performs a search on the query and returns search results to the ranking module 350. [0066] the ranking module 350 is configured to rank documents retrieved in response to a search query in an order of relevance based on various factors, including, for example, the match of the input query to the information within a document, personal information within the member profile of the searcher or result, and/or information pertaining to the professional network of the searcher or result).
As per claim 6, claim 1 is incorporated, Le further discloses:
comprising the one or more processors to: determine, by a matchmaking model processor, whether a reply to the second query indicates a match corresponding to the one or more document objects ([0065] the rewritten query may then be passed from the structuring module 320 to a query processor (not pictured) that performs a search on the query and returns search results to the ranking module 350 [0066] the ranking module 350 is configured to rank documents retrieved in response to a search query in an order of relevance based on various factors, including, for example, the match of the input query to the information within a document, personal information within the member profile of the searcher or result, and/or information pertaining to the professional network of the searcher or result..
As per claim 7, claim 6 is incorporated, Le further discloses:
wherein the match indicates that at least one of a set of document objects is obtained from the memory according to the second query ([0084] multiple hardware modules are configured or instantiated at different times, communications between such hardware modules may be achieved, for example, through the storage and retrieval of information in memory structures to which the multiple hardware modules have access. For example, one hardware module may perform an operation and store the output of that operation in a memory device to which it is communicatively coupled. A further hardware module may then, at a later time, access the memory device to retrieve and process the stored output).
As per claim 8, claim 1 is incorporated, Le further discloses:
comprising the one or more processors to: generate, by a generative artificial intelligence processor executed by the one or more processors, the reply to the first query including the description object and the one or more document objects, in response to the reply to the second query indicating the match ([0065] Referring back to FIG. 3, the rewritten query may then be passed from the structuring module 320 to a query processor (not pictured) that performs a search on the query and returns search results to the ranking module 350 [0066]-[0067] documents ranked based on, for example, the match of the input query to the information within a document, personal information within the member profile of the searcher or result, and/or information pertaining to the professional network of the searcher or result [0069] reasons or descriptions associated with each of the query results [0071] the confidence score is calculated based on machine learning models of two types of training data sets, including past activities of all members from the member activity and behavior database 222 and the profile data of all members from the profile database 218. The confidence score is calculated based on member activity data indicating a percentage of member activity associating the word term to the corresponding standardized entity [0078] At operation 604, a standardized entity. taxonomy is searched to locate a standardized entity that most closely matches the query term. Then, at operation 606, a confidence score is calculated for the query term--standardized entity pair for the standardized entity that most closely matches the query term).
As per claim 10, claim 1 is incorporated, Le further discloses:
comprising the one or more processors to: augment, by an orchestration agent processor, the context according to data indicative of a chat history, in response to the receiving the first query ([0070] the scoring module 330 is configured to determine a confidence score associated with each possible entity of the input query. An input query may have inherent semantic ambiguities and synonyms associated with some of the key words within the query. The confidence score indicates the accuracy with which the system maps each term to a corresponding standardized entity, based on the likelihood that the searcher, under ideal circumstances, would have specified the standardized entity in the query [0071] In an example embodiment, the confidence score is calculated based on machine learning models of two types of training data sets, including past activities of all members from the member activity and behavior database 222 and the profile data of all members from the profile database 218).
As per claim 11, claim 1 is incorporated, Le further discloses:
comprising the one or more processors to: augment, by an orchestration agent processor, the context according to data indicative of a chat history, in response to the identifying the one or more named entities ([0070] the scoring module 330 is configured to determine a confidence score associated with each possible entity of the input query. An input query may have inherent semantic ambiguities and synonyms associated with some of the key words within the query. The confidence score indicates the accuracy with which the system maps each term to a corresponding standardized entity, based on the likelihood that the searcher, under ideal circumstances, would have specified the standardized entity in the query [0071]In an example embodiment, the confidence score is calculated based on machine learning models of two types of training data sets, including past activities of all members from the member activity and behavior database 222 and the profile data of all members from the profile database 218).
As per claim 12, claim 1 is incorporated, Le further discloses:
comprising the one or more processors to: process the one or more document objects; and enhance, using a model trained with machine learning, the one or more document objects ([0067] the ranking module 350 uses a multipass scorer on results documents. At each pass, the search results are filtered and downgraded based on entity-based features from, for example, the tagged raw query 404 and/or the final rewritten query 416 [0070] the scoring module 330 is configured to determine a confidence score associated with each possible entity of the input query [0071] the confidence score is calculated based on machine learning models of two types of training data sets, including past activities of all members from the member activity and behavior database 222 and the profile data of all members from the profile database 218. The confidence score is calculated based on member activity data indicating a percentage of member activity associating the word term to the corresponding standardized entity).
Regarding claim 13, Le discloses:
A method, comprising: receiving, by one or more processors coupled with memory, a first query indicating a request for one or more document objects and including one or more criteria for selection of the one or more document objects ([0017], [0066]-[0067] documents as search results [0043] user query received 400 [0078] query terms of query received);
identifying, by the one or more processors, one or more named entities from one or more portions of the first query ([0043] query tagging and identifying entities [0078]-[0079] entity matching and identification);
generating, by the one or more processors, a second query to obtain the one or more document objects, in response to the one or more named entities being indicative of a context for the first query ([0062]-[0064] query rewritten);
obtaining, by the one or more processors, the one or more document objects according to the second query; generating, by the one or more processors, a reply to the first query including a description object and the one or more document objects, the description object based on the first query ([0065] Referring back to FIG. 3, the rewritten query may then be passed from the structuring module 320 to a query processor (not pictured) that performs a search on the query and returns search results to the ranking module 350 [0066]-[0067] documents ranked based on, for example, the match of the input query to the information within a document, personal information within the member profile of the searcher or result, and/or information pertaining to the professional network of the searcher or result [0069] reasons or descriptions associated with each of the query results) and the description objects is the reason for the match of the query result;
and causing, by the one or more processors, a user interface to present the reply to the first query and the description object ([0069] a presentation module (not pictured) is configured to present query rewriting recommendations to the user, present search results according to their ranked order, present a reason associated with why the query result is being presented (e.g., such as a shared connection), and present the search results with category-selected highlighting).
Regarding claim 20, Le discloses:
A non-transitory computer readable medium including one or more instructions stored thereon and executable by one or more processors to: receive a first query indicating a request for one or more document objects and including one or more criteria for selection of the one or more document objects ([0017], [0066]-[0067] documents as search results [0043] user query received 400 [0078] query terms of query received);
identify one or more named entities from one or more portions of the first query ([0043] query tagging and identifying entities [0078]-[0079] entity matching and identification);
generate a second query to obtain the one or more document objects, in response to the one or more named entities being indicative of a context for the first query ([0062]-[0064] query rewritten);
obtain the one or more document objects according to the second query; generate a reply to the first query including a description object and the one or more document objects, the description object based on the first query ([0065] Referring back to FIG. 3, the rewritten query may then be passed from the structuring module 320 to a query processor (not pictured) that performs a search on the query and returns search results to the ranking module 350 [0066]-[0067] documents ranked based on, for example, the match of the input query to the information within a document, personal information within the member profile of the searcher or result, and/or information pertaining to the professional network of the searcher or result [0069] reasons or descriptions associated with each of the query results) and the description objects is the reason for the match of the query result;
and cause a user interface to present the reply to the first query and the description object ([0069] a presentation module (not pictured) is configured to present query rewriting recommendations to the user, present search results according to their ranked order, present a reason associated with why the query result is being presented (e.g., such as a shared connection), and present the search results with category-selected highlighting).
Claims 16-19 recite similar claim limitations as the system of claims 4-7, except that they set forth the claimed invention as a method and, as such, they are rejected for the same reasons as applied hereinabove.
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 of this title, 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 2-3, 9, 14-15 are rejected under 35 U.S.C. 103 as being unpatentable over Le (US 2018/0060387) in view of Zhu (US 2018/0232376).
As per claim 2, claim 1 is incorporated, Le fails to disclose “comprising the one or more processors to: generate, by a generative artificial intelligence processor, a second reply to the first query indicating a request for information indicative of the context, in response to the one or more named entities not being indicative of the context; and cause the user interface to present the second reply”
However, Zhu teaches the above limitation ([0021] the query and document structurer 114 is operative to mine various collections of data and perform machine learning techniques on the various collections of data for analyzing and extracting entities from unstructured text [0029] according to one aspect, the dialog manager 112 analyzes entities 204 identified and extracted from the documents 120 a-d that are missing in the query 202. According to an example, the dialog manager 112 is operative to formulate a question 210 to ask the user 102 to clarify whether the entity 204 in the document 120 matches the user's intent. Based on the user's response 212, the dialog manager 112 is further operative to adjust the confidence score 208 of each document 120 until the candidate pool 206 is comprised of documents having confidence scores 208 satisfying a certain threshold value, [0041]-[0043] clarifying questions and entity refinement, Fig. 2C).
Therefore, it would have been obvious to one of ordinary skill in the art prior to the effective filing date of the claimed invention to incorporate the teaching of Zhu into the teaching of Le because the references similarly disclose query refinement and document search and retrieval. Consequently, one of ordinary skill in the art would be motivated to further modify the system as in Le to further include the entity and query context refinement as in Zhu for “improving the functionality of a virtual assistant system by applying a conversation strategy to a user query to engage the user for gathering information needed to fulfill the query, and thus to deliver a relevant solution to the user” and “the functionality of the user's device is improved by the present disclosure in at least that an improved user experience is provided that enables the user to efficiently receive a relevant solution without having to repeat a query when editing query data” (Zhu, [0003]).
As per claim 3, claim 1 is incorporated, Le fails to disclose “comprising the one or more processors to: augment, by a generative artificial intelligence processor, the context according to data indicative of a chat history, in response to the one or more named entities not being indicative of the context”
However, Zhu teaches the above limitation ([0021] the query and document structurer 114 is operative to mine various collections of data and perform machine learning techniques on the various collections of data for analyzing and extracting entities from unstructured text [0029] according to one aspect, the dialog manager 112 analyzes entities 204 identified and extracted from the documents 120 a-d that are missing in the query 202. According to an example, the dialog manager 112 is operative to formulate a question 210 to ask the user 102 to clarify whether the entity 204 in the document 120 matches the user's intent. Based on the user's response 212, the dialog manager 112 is further operative to adjust the confidence score 208 of each document 120 until the candidate pool 206 is comprised of documents having confidence scores 208 satisfying a certain threshold value, [0041]-[0043] clarifying questions and entity refinement) and the chat history is the chat between the user and the system as shown in Fig. 2C.
Therefore, it would have been obvious to one of ordinary skill in the art prior to the effective filing date of the claimed invention to incorporate the teaching of Zhu into the teaching of Le because the references similarly disclose query refinement and document search and retrieval. Consequently, one of ordinary skill in the art would be motivated to further modify the system as in Le to further include the entity and query context refinement as in Zhu for “improving the functionality of a virtual assistant system by applying a conversation strategy to a user query to engage the user for gathering information needed to fulfill the query, and thus to deliver a relevant solution to the user” and “the functionality of the user's device is improved by the present disclosure in at least that an improved user experience is provided that enables the user to efficiently receive a relevant solution without having to repeat a query when editing query data” (Zhu, [0003]).
As per claim 9, claim 6 is incorporated, Le fails to disclose “comprising the one or more processors to: generate, by a generative artificial intelligence processor executed by the one or more processors, an investigative reply to the first query including a request structured to identify the context, in response to the reply to the second query not indicating the match”
However, Zhu teaches the above limitation ([0021] the query and document structurer 114 is operative to mine various collections of data and perform machine learning techniques on the various collections of data for analyzing and extracting entities from unstructured text [0029] according to one aspect, the dialog manager 112 analyzes entities 204 identified and extracted from the documents 120 a-d that are missing in the query 202. According to an example, the dialog manager 112 is operative to formulate a question 210 to ask the user 102 to clarify whether the entity 204 in the document 120 matches the user's intent. Based on the user's response 212, the dialog manager 112 is further operative to adjust the confidence score 208 of each document 120 until the candidate pool 206 is comprised of documents having confidence scores 208 satisfying a certain threshold value, [0041]-[0043] clarifying questions and entity refinement) and Fig. 2C shows the clarifying questions response to context not matching user’s intent.
Therefore, it would have been obvious to one of ordinary skill in the art prior to the effective filing date of the claimed invention to incorporate the teaching of Zhu into the teaching of Le because the references similarly disclose query refinement and document search and retrieval. Consequently, one of ordinary skill in the art would be motivated to further modify the system as in Le to further include the entity and query context refinement as in Zhu for “improving the functionality of a virtual assistant system by applying a conversation strategy to a user query to engage the user for gathering information needed to fulfill the query, and thus to deliver a relevant solution to the user” and “the functionality of the user's device is improved by the present disclosure in at least that an improved user experience is provided that enables the user to efficiently receive a relevant solution without having to repeat a query when editing query data” (Zhu, [0003]).
Claims 14, 15 recite similar claim limitations as the system of claims 2, 3, except that they set forth the claimed invention as a method and, as such, they are rejected for the same reasons as applied hereinabove.
Pertinent Prior Art
The following prior art made of record and not relied upon is considered pertinent to applicant's disclosure:
Yang (US 2024/0257206) discloses search result generation using named entity recognition;
Li (US 2017/0140059) discloses knowledge-based entity detection and disambiguation;
Cumby (US 2014/0095466) discloses entity assessment and ranking.
Conclusion
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/WILLIAM P BARTLETT/
Primary Examiner, Art Unit 2169
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