A Global–Local Attentive Relation Detection Model for Knowledge-Based Question Answering

IEEE Transactions on Artificial Intelligence(2021)

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摘要
Knowledge-based question answering (KBQA) is an essential but challenging task for artificial intelligence and natural language processing. A key challenge pertains to the design of effective algorithms for relation detection. Conventional methods model questions and candidate relations separately through the knowledge bases (KBs) without considering the rich word-level interactions between them. ...
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关键词
Task analysis,Knowledge discovery,Semantics,Knowledge based systems,Convolutional neural networks,Detectors,Knowledge representation
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