SAWSDL-iMatcher: A customizable and effective Semantic Web Service matchmaker

As the number of publicly available services grows, discovering proper services becomes an important issue and has attracted amount of attempts. This paper presents a new customizable and effective matchmaker, called SAWSDL-iMatcher. It supports a matchmaking mechanism, named iXQuery, which extends XQuery with various similarity joins for SAWSDL service discovery. Using SAWSDL-iMatcher, users can flexibly customize their preferred matching strategies according to different application requirements. SAWSDL-iMatcher currently supports several matching strategies, including syntactic and semantic matching strategies as well as several statistical-model-based matching strategies which can effectively aggregate similarity values from matching on various types of service description information such as service name, description text, and semantic annotation. Besides, we propose a semantic matching strategy to measure the similarity among SAWSDL semantic annotations. These matching strategies have been evaluated in SAWSDL-iMatcher on SAWSDL-TC2 and Jena Geography Dataset (JGD). The evaluation shows that different matching strategies are suitable for different tasks and contexts, which implies the necessity of a customizable matchmaker. In addition, it also provides evidence for the claim that the effectiveness of SAWSDL service matching can be significantly improved by statistical-model-based matching strategies. Our matchmaker is competitive with other matchmakers on benchmark tests at S3 contest 2009.