Abstract
Intelligent question-answering system (IQAS) can help users quickly retrieve the answers to the required questions which is currently a popular research direction of NLP. This paper combines the research of relevant scholars and the analysis of their advantages and disadvantages, and an intelligent question-and-answer system is designed, which can automatically generate a question-and-answer knowledge base based on a given document. It can retrieve the knowledge base and recommend answers automatically, quickly and accurately according to the keywords provided by users. The system realized text semantic understanding and analysis, and its MRR value reached a satisfactory 0.7381. At the same time, the paper extends an automatic answer text generation technology based on Seq2Seq model, which can be a useful supplement to the traditional question-and-answer recommendation generation strategy.
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