摘要： 针对中文是非问句，设计并实现了基于Lucene的问答系统，主要包括问句预处理、索引创建和答案整理三部分。问句预处理部分，引入句法成分权重和命名实体权重改进TextRank算法，得到一种提取问句核心词的方法。在索引创建部分，针对本地的多源数据进行文档融合创建索引，降低数据多样性带来的复杂度。在答案整理部分，对查询索引结果进行答案判决，输出肯定或否定含义的答案。实验结果表明，数据融合能有效减少索引创建耗时，改进TextRank的核心词提取方法准确率明显高于TextRank，系统具有较为不错的性能。

中图分类号： TP391.1
文献标识码： A
DOI： 10.19358/j.issn.2096-5133.2020.11.012
引用格式： 罗东霞，卿粼波，吴晓红. 基于Lucene的中文是非问答系统的设计与实现[J].信息技术与网络安全，2020，39(11)：74-78.

Design and implementation of Chinese yes-no question answering system based on Lucene

Abstract： A Chinese yes-no question answering system based on Lucene around Chinese yes-no questions is designed and implemented，and this system includes three parts：question preprocessing，index creation, and answer sorting. In the first part, introducing the syntactic component weights and named entity weights to improve the TextRank algorithm, a method for extracting the core words of the question sentence is obtained. In the second part, the document fusion is created for the multi-source data to reduce the complexity which is caused by data diversity. In the last section, the query index results are judged by the answer，and then the answers with positive or negative meanings are output. The experimental results show that data fusion can effectively reduce the index creation time, and the accuracy rate of the improved TextRank core word extraction method is significantly higher than TextRank, which means the system has good performance.

Key words : yes-no question answering；Lucene；TextRank；core word extraction