基于概念语义同义扩展的文本检索研究  

Research on Text Retrieval Based on Concept Semantic Synonymy Expansion

作　　者：张映海[1] 

机构地区：[1]武警广州指挥学院计算机教研室,广州510440

出　　处：《计算机与数字工程》2008年第4期68-71,共4页Computer & Digital Engineering

摘　　要：对TF-IDF分析后,提出一种已有关键词的文本的词条权重计算方法(TKSM),并以此构造基于概念语义同义扩展的文本检索模型(CSSERM)。实验表明,该模型的综合性能优于关键词检索模型,但精确率较关键词模型稍有降低。为此,构造基于概念同义扩展的文本检索模型与关键词模型结合的检索模型,两者的结合比例调整适当,能平衡检索系统的准确率与召回率,获得更好的检索效果。After analyzing TF- IDF, a method, named as TKSM （Text Keywords Synonymy Merger）, for terms weight computation based on text keywords synonymous merger is proposed. In virtue of TKSM, a model, named as CSSERM （ Concept Semantic Synonymy Expansion Retrieval Model）, of text retrieval based on concept semantic synonymous expansion is constructed. Experiments show that the tradeoff performance of CSSERM is super to keywords retrieval model （KRM）, but CSSERM has a little lower precision. Therefore, based on the combination of CSSERM and KRM, a Combination Retrieval Model （CRM） is presented in which the combinative parameters can be adjusted to balance the precision and recall rate for achieving a better retrieval result.

关 键 词：概念 同义扩展 文本检索 词条权重 

分 类 号：TP391[自动化与计算机技术—计算机应用技术]