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公开(公告)号:US20210390260A1
公开(公告)日:2021-12-16
申请号:US17119323
申请日:2020-12-11
Inventor: Hongjian SHI , Wenbin JIANG , Xinwei FENG , Miao YU , Huanyu ZHOU , Meng Tian , Xueqian Wu , Xunchao Song
Abstract: The present disclosure discloses a method, apparatus, device, and storage medium for matching semantics, relates to the technical fields of knowledge graph, natural language processing, and deep learning. The method may include: acquiring a first text and a second text; acquiring language knowledge related to the first text and the second text; determining a target embedding vector based on the first text, the second text, and the language knowledge; and determining a semantic matching result of the first text and the second text, based on the target embedding vector.
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公开(公告)号:US20200050671A1
公开(公告)日:2020-02-13
申请号:US16538589
申请日:2019-08-12
Inventor: Xinwei FENG , Xunchao SONG , Miao YU , Huanyu ZHOU , Shaoshun KANG
Abstract: Embodiments of the present disclosure provide a query processing method and an apparatus, a server and a storage medium. The method includes: determining a word vector representation of a query sequence and an entity vector representation of the query sequence respectively based on respective words and respective entities included in the query sequence; determining a word vector representation of a paragraph and an entity vector representation of the paragraph respectively based on respective words and respective entities included in the paragraph; and determining a similarity between the query sequence and the paragraph according to the word vector representation of the query sequence, the entity vector representation of the query sequence, the word vector representation of the paragraph, and the entity vector representation of the paragraph.
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3.
公开(公告)号:US20210319335A1
公开(公告)日:2021-10-14
申请号:US17037612
申请日:2020-09-29
Inventor: Wenbin JIANG , Huanyu ZHOU , Meng TIAN , Ying LI , Xinwei FENG , Xunchao SONG , Pengcheng YUAN , Yajuan LYU , Yong ZHU
Abstract: The present disclosure discloses a question analysis method, a device, a knowledge base question answering system and an electronic equipment. The method includes: analyzing a question to obtain N linearized sequences, N being an integer greater than 1; converting the N linearized sequences into N network topology maps; separately calculating a semantic matching degree of each of the N network topology maps to the question; and selecting a network topology map having a highest semantic matching degree to the question as a query graph of the question from the N network topology maps. According to the technology of the present disclosure, the query graph of the question can be obtained more accurately, and the accuracy of the question to the query graph is improved, thereby improving the accuracy of question analysis.
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4.
公开(公告)号:US20210216722A1
公开(公告)日:2021-07-15
申请号:US17149226
申请日:2021-01-14
Inventor: Songtai DAI , Xinwei FENG , Miao YU , Huanyu ZHOU , Xunchao SONG , Pengcheng YUAN
IPC: G06F40/30 , G06F40/295 , G06F16/35
Abstract: A method for processing a sematic description of a text entity is proposed. The method includes: acquiring a plurality of target texts containing a main entity, and extracting related entities describing the main entity from each target text; acquiring a sub-relation vector of a pair of the main entity and each related entity in each target text; calculating a similarity distance of the main entity between different target texts based on the sub-relation vector; and determining a semantic similarity of the main entity descripted in different target texts based on the similarity distance.
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5.
公开(公告)号:US20210011921A1
公开(公告)日:2021-01-14
申请号:US16812062
申请日:2020-03-06
Inventor: Songtai DAI , Xinwei FENG , Miao YU , Huanyu ZHOU , Xunchao SONG , Pengcheng YUAN
IPC: G06F16/2457 , G06N20/00 , G09B7/02
Abstract: A method for obtaining an answer to a question is provided. The method may include: acquiring a question; determining at least a part of articles in a preset article database as candidate articles, and determining first scores of the candidate articles respectively, the first score of any of the candidate articles representing a matching degree between the candidate article and the question; determining at least a part of texts in each of the candidate articles as candidate texts, and determining second scores of the candidate texts respectively, the second score of any of the candidate texts representing a matching degree between the candidate text and the question; and determining at least a part of the candidate texts as the answer based on a score set of each of the candidate texts, the score set of any of the candidate texts including the second score and the first score.
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