基于知网的语义相关度计算  

Semantic Relevancy Computing Based on Hownet

作　　者：许云[1] 樊孝忠[1] 张锋[1] 

机构地区：[1]北京理工大学信息科学技术学院计算机科学工程系,北京100081

出　　处：《北京理工大学学报》2005年第5期411-414,共4页Transactions of Beijing Institute of Technology

基　　金：云南省信息技术基金资助项目(2002IT03)

摘　　要：为解决句法分析中的结构性歧义,引入了语义相关度计算.基于语义相似度计算及知网的语义信息,提出了语义相关度计算方法;利用知网的义原纵向与横向关系及实例信息计算不同词性的相关度.在计算义原距离时,考虑了义原之间的解释关系,对义原的距离进行修正.根据相似度的对称性,计算实例的影响因素提高了相关度的准确率.实验结果表明,使用该计算方法得出的语义相关度结果更加合理.Semantic relevancy computation is used to solve structural disambiguity in parsing syntactic. Semantic relevancy computation based on Hownet is proposed, based on semantic similarity computation. The method can compute the relevancy of different POS words using resources of Hownet, such as the examples, the relationship of horizontal and vertical primarily. Consider the explanatory relations of the two primarily to amend the primary distance, when computing the primary distance. According to the symmetry of semantic similarity, the result of relevancy is improved by computing the effect factor of examples. Experimental results show that the results are satisfactory.

关 键 词：语义相关度 知网 自然语言处理 

分 类 号：TP391[自动化与计算机技术—计算机应用技术]