基于查询扩展词条加权的文本检索研究  

Research on the Text Retrieval Based on the Weight of the Expanding Query Term

作　　者：张映海[1] 张宇薇[1] 

机构地区：[1]武警广州指挥学院信息技术教研室,广东广州510440

出　　处：《计算机工程与科学》2011年第1期161-165,共5页Computer Engineering & Science

基　　金：国家自然科学基金资助项目(60173060)

摘　　要：本文分析了关键词检索文本,由于其查询词没有扩展导致检全率低;而概念检索文本虽然部分有检索词扩展,但是查询词权重与原查询词没有区分。为此,本文利用词条间的语义相似度,提出一种查询扩展词条权重计算方法——展开减小法,并将查询词以及扩展词经展开减小法计算权重后构建向量空间模型检索文本。实验表明,构建的检索模型检索文本,其综合性能得到极大提高。The text retrieval with keywords is analyzed, and the recall rate is low without the expanding query. And as for the text retrieval with concept, the weights between the expanding query terms and query words are not distinguished. So, a method named？ expansion lessening, which is used for computing the weight of the expanding query term by the dint of words semantic similarity, is proposed. By expansion lessening, the expanding query term and query words are used to construct a？ vector space model for？ text search. Experiments show that the integrated performance of the constructed retrieval model is improved greatly in text search.

关 键 词：扩展词条 权重计算 文本检索 

分 类 号：TP391[自动化与计算机技术—计算机应用技术]