计算机应用 ›› 2011, Vol. 31 ›› Issue (10): 2808-2810.DOI: 10.3724/SP.J.1087.2011.02808

• 人工智能 • 上一篇    下一篇

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

徐红艳,方欣,冯勇   

  1. 辽宁大学 信息学院, 沈阳 110036
  • 收稿日期:2011-04-06 修回日期:2011-06-06 发布日期:2011-10-11 出版日期:2011-10-01
  • 通讯作者: 徐红艳
  • 作者简介:徐红艳(1972-),女,辽宁丹东人,副教授,主要研究方向:数据库、Deep Web;方欣(1989-),女,江西抚州人,硕士研究生,主要研究方向:商务智能、语义Web;冯勇(1973-),男,辽宁沈阳人,副教授,博士,主要研究方向:商务智能、语义Web。
  • 基金资助:

    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)

Improvement of semantic distance-based concept similarity computation in Web service matching

XU Hong-yan, FANG Xin, FENG Yong   

  1. School of Information, Liaoning University, Shenyang Liaoning 110036, China
  • Received:2011-04-06 Revised:2011-06-06 Online:2011-10-11 Published:2011-10-01
  • Contact: XU Hong-yan
  • Supported by:

    the Natural Science Foundation of Liaoning Province of China;China Postdoctoral Science Foundation

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

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.

Key words: Web service, ontology, concept similarity, semantic distance, matching

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