计算机工程2013，Vol.39Issue(7)：219-223,5.DOI:10.3969/j.issn.1000-3428.2013.07.049
基于模糊聚类优化的语义Web服务发现
Semantic Web Service Discovery Based on Fuzzy Clustering Optimization
摘要
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.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Key words
domain ontology/ ontology description language/ ontology distance/ fuzzy clustering/ semantic Web service/ service discovery分类
信息技术与安全科学引用本文复制引用
王永明,张英俊,谢斌红,潘理虎,陈立潮..基于模糊聚类优化的语义Web服务发现[J].计算机工程,2013,39(7):219-223,5.基金项目
山西省自然科学基金资助项目(2009011022-1) （2009011022-1）
太原科技大学研究生创新基金资助项目(20111025) （20111025）
