计算机技术与发展2023，Vol.33Issue(12)：8-16,9.DOI:10.3969/j.issn.1673-629X.2023.12.002
问答系统构建及推理研究综述
A Review of Question Answering System Construction and Inference Research
摘要
Abstract
In recent years,the research on question answering system has improved the quality of information extraction,and achieved good results in many fields.The question-answering system constructed by traditional methods cannot meet today's needs,so it has become the mainstream of current research to build a question-answering system to improve retrieval ability by combining deep learning model.In addition,there are more and more multi-hop questions with more and more constraints.The question answering system needs to have certain reasoning ability to deduce more information to find the answer accurately.We discuss two methods of question answering system based on semantic parsing and information retrieval.Both of these methods can deal with simple problems with single constraints effectively,and combined with deep learning model,can solve complex problems with multiple constraints better.In addition,for the question answering with multiple hops in the knowledge base,the question answering reasoning techniques based on graph neural network and reinforcement learning are discussed.These techniques can perform multi-hop reasoning in the knowledge base and complete the question answering task by supplementing the missing information in the question answering.Finally,we summarize the advantages and disadvantages of the two methods,and look forward to the future development of question answering system.关键词
问答系统/语义解析/信息检索/问答推理/深度学习Key words
question-answering system/semantic parsing/information retrieval/question-answering reasoning/deep learning分类
信息技术与安全科学引用本文复制引用
姚奕,尹瑞江,陈朝阳..问答系统构建及推理研究综述[J].计算机技术与发展,2023,33(12):8-16,9.基金项目
国家社科基金军事学项目(公开)(2021-SKJJ-B-06) （公开）
