SAM: Semantic Advanced Matchmaker

As the number of available Web services increase finding appropriate Web services to fulfill a given request becomes an important task. Most of the current solutions and approaches in Web service discovery are limited in the sense that they are strictly defined, and they do not use the full power of semantic and ontological representation. Service matchmaking, which deals with similarity between service definitions, is highly important for an effective discovery. Studies have shown that use of semantic Web technologies improves the efficiency and accuracy of matchmaking process. In this research we focus on one of the most challenging tasks in service discovery and composition: Service matchmaking. We make use of current semantic Web technologies like OWL and OWL-S to describe services and define ontologies. We introduce an efficient matchmaking algorithm based on bipartite graphs. We have seen that bipartite matchmaking has advantages over other approaches in the literature for parameter pairing problem, which deals with finding the semantically matching parameters in a service pair. Our proposed algorithm ranks the services in a candidate set according to their semantic similarity to a certain request. Our matchmaker performs the semantic similarity assignment implementing the following approaches: Subsumption-based similarity, propertylevel similarity, similarity distance annotations and WordNet-based similarity. Our results show that the proposed matchmaker enhances the captured semantic similarity, providing a finegrained approach in semantic matchmaking.