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Web服务匹配中基于语义距离的概念相似度计算方法的改进
引用本文:徐红艳,方欣,冯勇.Web服务匹配中基于语义距离的概念相似度计算方法的改进[J].计算机应用,2011,31(10):2808-2810.
作者姓名:徐红艳  方欣  冯勇
作者单位:辽宁大学 信息学院, 沈阳 110036
基金项目:教育部人文社会科学研究青年基金资助项目(10YJC630063);中国博士后科学基金资助项目(20100471474);辽宁省自然科学基金资助项目(20102083)
摘    要:在Web服务匹配中,基于语义距离的概念相似度计算方法居于重要的地位。因现有基于语义距离的概念相似度计算方法未考虑语义不对称性和语义密度的影响,导致计算结果不够准确。为提高概念相似度计算的准确性,在现有研究的基础上,通过增加不对称因子和密度因子,对基于语义距离的概念相似度计算方法加以改进。最后通过算例对改进后的方法的可行性进行了验证,经对比分析表明改进后的方法更真实地反映了概念间的语义关系,计算结果更加符合客观实际。

关 键 词:Web服务  本体  概念相似度  语义距离  匹配  
收稿时间:2011-04-06
修稿时间:2011-06-06

Improvement of semantic distance-based concept similarity computation in Web service matching
XU Hong-yan,FANG Xin,FENG Yong.Improvement of semantic distance-based concept similarity computation in Web service matching[J].journal of Computer Applications,2011,31(10):2808-2810.
Authors:XU Hong-yan  FANG Xin  FENG Yong
Affiliation:School of Information, Liaoning University, Shenyang Liaoning 110036, China
Abstract:In Web service matching, the concept similarity computation based on semantic distance plays an important role. Because the influence of semantic asymmetry and semantic density has not been considered in current concept similarity computation based on semantic distance, the computation result is not accurate. To enhance the accuracy of the concept similarity computation, the semantic distance-based concept similarity computation was improved by adding the asymmetry factor and density factor on the basis of the current research. Finally, the feasibility of the improved semantic distance-based concept similarity computation was verified via an example. According to the contrast analysis, the improved semantic distance-based concept similarity computation can reflect semantic relationship between concepts more truly and the computation result is more in line with the objective reality.
Keywords:Web service                                                                                                                          ontology                                                                                                                          concept similarity                                                                                                                          semantic distance                                                                                                                          matching
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