基于IO与信息内容的语义Web服务发现

随着web服务数量大幅增长,如何快速准确的发现并满足用户需求的服务已经成为一个亟待解决的问题.现有的基于语义的web服务发现通常使用混合的方法,先在本体层面上进行语义匹配,当语义匹配失败的时候再采取其他的方法(基于关键字的匹配、基于结构分析)来弥补这个缺陷,在补救的过程当中由于现有的方法并未准确的反应两个概念之间的相似性,从而导致web服务的发现的准确率不高.将信息内容语义相似度计算的思想考虑在内,提出了采用基于服务的IO(input, output)语义匹配和基于信息内容语义相似计算相结合的方法,并以owls-tc2.0作为测试集合对该方法进行测试,实验结果表明该方法能有效提高服务发现的准确率.

Method of Combining IO with Information Content for Discovering Semantic Web Services

In recent years, there is an exponential growth of the number of web services in the real world. In the web service research area, the most of concerning problem is how to discover the potential web services to meet users' needs fast and accurately. Nowadays, a lot of discovery methods based on semantic are employing the ontologies of concepts among the parameters of web services interface. With content of concept, when the semantic matching is fail, they take other methods such as keyword-based matching and structure-based analysis to make up for the defect. These methods improve the precision and efficiency in the web service discovery in a certain degree. However, all of these methods dismiss the semantic similarity of Information Content. In this paper, we propose a method which employs a combination of methods based on semantic web service discovery technology and the concept of semantic similarity of the IC. It uses owls-tc 2.0 as a test set. The experiments show that our method is effective to improve the precision of web service discovery.