Query Expansion Based on Semantics and Statistics in Chinese Question Answering System

作     者：JIA Keliang PANG Xiuling LI Zhinuo FAN Xiaozhong 

作者机构：School of Information Management Shandong Economic University Jinan 250014 Shandong China Department of Educational Science and Technology Weifang University Weifang 261061 Shandong China School of Computer Science and Technology Beijing Institute of Technology Beijing 100081 China 

出 版 物：《Wuhan University Journal of Natural Sciences》 (武汉大学学报（自然科学英文版）)

年 卷 期：2008年第13卷第4期

页      面：505-508页

学科分类：081203[工学-计算机应用技术] 08[工学] 0835[工学-软件工程] 0812[工学-计算机科学与技术（可授工学、理学学位）] 

基　　金：the Specialized Research Program Fund the Doctoral Program of Higher Education of China (20050007023) the Natural Science Foundation of Shandong Province(Y2004G04) 

主　　题：Chinese question answering system query expansion relevance feedback semantic similarity semantic relevancy 

摘      要：In Chinese question answering system, because there is more semantic relation in questions than that in query words, the precision can be improved by expanding query while using natural language questions to retrieve documents. This paper proposes a new approach to query expansion based on semantics and statistics Firstly automatic relevance feedback method is used to generate a candidate expansion word set. Then the expanded query words are selected from the set based on the semantic similarity and seman- tic relevancy between the candidate words and the original words. Experiments show the new approach is effective for Web retrieval and out-performs the conventional expansion approaches.