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公开(公告)号:US20210149933A1
公开(公告)日:2021-05-20
申请号:US15929364
申请日:2020-04-28
Applicant: salesforce.com, Inc.
Inventor: Son Thanh Chang , Weiping Peng , Na Cheng , Feifei Jiang , Jacob Nathaniel Huffman , Nandini Suresh Kumar , Khoa Le , Christopher Larry
Abstract: Computing systems, database systems, and related methods are provided for recommending values for fields of database objects and dynamically updating a recommended value for a field of a database record in response to updated auxiliary data associated with the database record. One method involves obtaining associated conversational data, segmenting the conversational data, converting each respective segment of conversational data into a numerical representation, generating a combined numerical representation of the conversational data based on the sequence of numerical representations using an aggregation model, generating the recommended value based on the combined numerical representation of the conversational data using a prediction model associated with the field, and autopopulating the field of the case database object with the recommended value.
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公开(公告)号:US20210150146A1
公开(公告)日:2021-05-20
申请号:US16687626
申请日:2019-11-18
Applicant: salesforce.com, inc.
Inventor: Zachary Alexander , Edgar Gerardo Velasco , Victor Winslow Yee , Na Cheng , Khoa Le
IPC: G06F40/30 , G06F16/33 , G06F16/332 , G06N20/00
Abstract: A system is configured to analyze a corpus of historical chat data to identify the list of “best” responses. As such, the user is not required to identify a list of canned responses for input into the system. The described system uses a context word embedding function and response word embedding function to generate context vectors and response vectors corresponding to the corpus of conversation data, and the vectors are represented by a respective context matrix and a response matrix. The system processes these matrices to generate scores for responses, clusters the responses, and identifies the responses corresponding to the best scores for each cluster.
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公开(公告)号:US10997250B2
公开(公告)日:2021-05-04
申请号:US16140418
申请日:2018-09-24
Applicant: salesforce.com, inc.
Inventor: Sitaram Asur , Aditya Sakhuja , Hui S. Fisher , Anjan Goswami , Khoa Le
IPC: G06F16/9032 , G06F9/451 , G06F40/30 , G06F40/295
Abstract: A method is provided for generating a ranked list of candidate responders. In some embodiments, the method includes receiving a question from a user and generating a question feature vector representing an intent of the question and a first skill set inferred from the question. The method also includes for one or more candidate responders, generating a candidate feature vector representing a skill set and questions associated with the respective candidate responder; computing a reputation score based on questions and user feedback associated with the respective candidate responder; and computing, based on the question feature vector, candidate feature vector, and reputation score, a probability score representing a prediction of the quality of an answer that would be provided by the respective candidate responder if the input question were routed to the respective candidate responder. The method further includes generating a ranked list of candidate responders using the computed probability scores.
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公开(公告)号:US11755655B2
公开(公告)日:2023-09-12
申请号:US17239295
申请日:2021-04-23
Applicant: salesforce.com, inc.
Inventor: Sitaram Asur , Aditya Sakhuja , Hui S. Fisher , Anjan Goswami , Khoa Le
IPC: G06F16/9032 , G06F9/451 , G06F40/30 , G06F40/295
CPC classification number: G06F16/90332 , G06F9/453 , G06F40/295 , G06F40/30
Abstract: A method is provided for generating a ranked list of candidate responders. In some embodiments, the method includes receiving a question from a user and generating a question feature vector representing an intent of the question and a first skill set inferred from the question. The method also includes for one or more candidate responders, generating a candidate feature vector representing a skill set and questions associated with the respective candidate responder; computing a reputation score based on questions and user feedback associated with the respective candidate responder; and computing, based on the question feature vector, candidate feature vector, and reputation score, a probability score representing a prediction of the quality of an answer that would be provided by the respective candidate responder if the input question were routed to the respective candidate responder. The method further includes generating a ranked list of candidate responders using the computed probability scores.
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公开(公告)号:US11379671B2
公开(公告)日:2022-07-05
申请号:US16687626
申请日:2019-11-18
Applicant: salesforce.com, inc.
Inventor: Zachary Alexander , Edgar Gerardo Velasco , Victor Winslow Yee , Na Cheng , Khoa Le
IPC: G06F40/30 , G06F16/33 , G06N20/00 , G06F16/332
Abstract: A system is configured to analyze a corpus of historical chat data to identify the list of “best” responses. As such, the user is not required to identify a list of canned responses for input into the system. The described system uses a context word embedding function and response word embedding function to generate context vectors and response vectors corresponding to the corpus of conversation data, and the vectors are represented by a respective context matrix and a response matrix. The system processes these matrices to generate scores for responses, clusters the responses, and identifies the responses corresponding to the best scores for each cluster.
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公开(公告)号:US11314790B2
公开(公告)日:2022-04-26
申请号:US15929364
申请日:2020-04-28
Applicant: salesforce.com, Inc.
Inventor: Son Thanh Chang , Weiping Peng , Na Cheng , Feifei Jiang , Jacob Nathaniel Huffman , Nandini Suresh Kumar , Khoa Le , Christopher Larry
IPC: G06F16/00 , G06N20/00 , G06F16/31 , G06F16/35 , G06F16/34 , H04L51/56 , G06F16/2457 , G06F16/2455 , G06F16/9535
Abstract: Computing systems, database systems, and related methods are provided for recommending values for fields of database objects and dynamically updating a recommended value for a field of a database record in response to updated auxiliary data associated with the database record. One method involves obtaining associated conversational data, segmenting the conversational data, converting each respective segment of conversational data into a numerical representation, generating a combined numerical representation of the conversational data based on the sequence of numerical representations using an aggregation model, generating the recommended value based on the combined numerical representation of the conversational data using a prediction model associated with the field, and autopopulating the field of the case database object with the recommended value.
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