摘要
Web服务发现过程本质上是用户请求和服务匹配的过程。传统的UDDI发现技术是通过精确匹配实现的,不能较好地支持基于概率和语义约束的模糊匹配。针对这种情况,在基于现有的OWL-S匹配上,进一步增加了以隶属函数、语义距离、阈值为基础的模糊匹配,形成了两级匹配。并通过对语义表示的服务能力进行模糊聚类,这种机制减少了搜索空间,提高了发现效率及匹配的精度。
The essence of the Web services is the process on matching between the users＇requests and the services. As traditional UDDI discovery technology is achieved by precise matching, it can＇t preferably support the probability and semantic restriction matching, on the basis of the existing OWL-S matching, represents fuzzy matching based on the subjection functions, semantic distances and valve, forming bipod matching. Furthermore, the semantic capacity of services is fuzzily clustered,which decreases searching space and increases the precision.
出处
《计算机技术与发展》
2007年第11期125-127,138,共4页
Computer Technology and Development
基金
湖南省自然科学基金资助项目(05JJ30122)
湖南高校科研项目(04C720)
关键词
匹配
隶属函数
语义距离
模糊聚类
OWL-S
matching
subjection functions
semantic distance
fuzzy clustering
OWL- S
