作者投稿和查稿 主编审稿 专家审稿 编委审稿 远程编辑

计算机工程 ›› 2013, Vol. 39 ›› Issue (7): 219-223. doi: 10.3969/j.issn.1000-3428.2013.07.049

• 人工智能及识别技术 • 上一篇    下一篇

基于模糊聚类优化的语义Web服务发现

王永明,张英俊,谢斌红,潘理虎,陈立潮   

  1. (太原科技大学计算机科学与技术学院,太原 030024)
  • 收稿日期:2012-07-09 出版日期:2013-07-15 发布日期:2013-07-12
  • 作者简介:王永明(1985-),男,硕士研究生,主研方向:智能控制,自动推理;张英俊,教授级高级工程师;谢斌红,副教授、 硕士;潘理虎,副教授、博士;陈立潮,教授
  • 基金资助:
    山西省自然科学基金资助项目(2009011022-1);太原科技大学研究生创新基金资助项目(20111025)

Semantic Web Service Discovery Based on Fuzzy Clustering Optimization

WANG Yong-ming, ZHANG Ying-jun, XIE Bin-hong, PAN Li-hu, CHEN Li-chao   

  1. (Institute of Computer Science and Technology, Taiyuan University of Science and Technology, Taiyuan 030024, China)
  • Received:2012-07-09 Online:2013-07-15 Published:2013-07-12

摘要: 语义Web服务发现机制在发现服务时的准确率较低。为解决该问题,提出一种基于模糊聚类优化的语义Web服务发现方法。采用改进的模糊C-均值(FCM)聚类算法,实现对服务聚类预处理,在模糊聚类时,综合考虑服务的输入、输出、前提、效果 4个功能性参数,并扩展已有的服务匹配机制,在匹配时,将服务的4个功能性参数全部作为服务相似度的计算因子。实验结果 表明,在模糊聚类稳定的条件下,该方法的服务平均查全率为79.6%,平均查准率为85.9%,均高于未采用聚类处理和只采用 输入/输出参数的FCM聚类处理方法。

关键词: 领域本体, 本体描述语言, 本体距离, 模糊聚类, 语义Web服务, 服务发现

Abstract: Aiming at the problem of low efficiency for semantic Web service discovery mechanism in finding service, this paper proposes a novel method based on fuzzy clustering for optimizing semantic Web service discovery. It adopts the modified Fuzzy C-means(FCM) clustering algorithm to realize the cluster preprocessing of services. When clustering services, it can comprehensively consider the input, output, premise and the effect of service as the clustering parameters. This paper expands existing services matching mechanism. When matching services, it can take four functional parameters of service as its factors for similarity calculation. Experimental results show that under in fuzzy clustering stable conditions, the method of service average recall rate of 79.6%, and the average prospective rate of 85.9%, higher than the clustering process and only using Input/Output(I/O) parameters FCM method of clustering processing.

Key words: domain ontology, ontology description language, ontology distance, fuzzy clustering, semantic Web service, service discovery

中图分类号: