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Query Expansion for Answer Document Retrieval in Chinese Question Answering System

机译:查询答案文档检索中的答案文档检索系统

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In document retrieval, query words expansion is normally based on semantic relation of query words. While using natural language questions to retrieve documents, because of more abundant semantic relation of question than that of query words, the precision can be improved by expanding query according to question characteristics. This paper puts forward a query expansion method for answering document retrieval in Chinese question answering system. The related words of question type are got through analyzing the question-answering pair, and the query are expanded with related words of question type. In order to verify the validity of query expansion method, a similarity computation method for question and document based on minimal match span is implemented. The word frequency and position information of query words and expansion words in the document are taken into consideration. The experiment results show that retrieval performance make substantial improvement using query expansion.
机译:在文档检索中,查询单词扩展通常基于查询词语的语义关系。在利用自然语言问题来检索文档时,由于更丰富的语义关系的问题而不是查询词,可以通过根据问题特性扩展查询来提高精度。本文提出了一种查询扩展方法,用于在中国问题回答系统中回答文档检索。通过分析问答对来实现问题类型的相关词,并且查询以相关问题的相关字扩展。为了验证查询扩展方法的有效性,实现了基于最小匹配跨度的问题和文档的相似性计算方法。考虑了文档中查询词和扩展词的字频率和位置信息。实验结果表明,检索性能使用查询扩展进行了大量改进。

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