AN IMPROVED LIGHT-WEIGHT MATCHMAKING MECHANISM FOR DISCOVERING OWL-S SERVICES BASED ON SPARQL, BIPARTITE AND NLP APPROACH
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Abstract
Semantic Web services integrate the meaningful content of the Semantic Web with the business logic of Web services and thus enable industries and individuals to access these services. But as the number of available Web services increase, there is a growing demand for a mechanism for effective retrieval of required services. We propose an improved Semantic Web service discovery method for finding OWL-S (Web Ontology Language for Services) services by combining functional similarity matching (using bipartite graph) and textual similarity matching. However, discovering relevant Semantic Web service is a heavyweight task. Performance of service discovery is significantly reduced when the number of services increases. To overcome this issue, a lightweight filtering stage is also introduced before the discovery mechanism. Filtering is performed by semantic-based SPARQL (Simple Protocol and RDF Query Language) query. It will significantly reduce the input for the discovery process. Thus the search space and the time required to find the relevant services will be reduced. The proposed techniques are applied to a sample test collection and experimental results are presented, which demonstrate the effectiveness of the idea. ( Keywords: discovery, filtering, OWL-S, Semantic Web service, SPARQL )
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