Improving Semantic Web Services Discovery Using SPARQL-Based Repository Filtering

José María García, David Ruiz, Antonio Ruiz-Cortés

Abstract


Semantic Web Services discovery is commonly a heavyweight task, which has scalability issues when the number of services or the ontology complexity increase, because most approaches are based on Description Logics reasoning. As a higher number of services becomes available, there is a need for solutions that improve discovery performance. Our proposal tackles this scalability problem by adding a preprocessing stage based on two SPARQL queries that filter service repositories, discarding service descriptions that do not refer to any functionality or non-functional aspect requested by the user before the actual discovery takes place. This approach fairly reduces the search space for discovery mechanisms, consequently improving the overall performance of this task. Furthermore, this particular solution does not provide yet another discovery mechanism, but it is easily applicable to any of the existing ones, as our prototype evaluation shows. Moreover, proposed queries are automatically generated from service requests, transparently to the user. In order to validate our proposal, this article showcases an application to the OWL-S ontology, in addition to a comprehensive performance analysis that we carried out in order to test and compare the results obtained from proposed filters and current discovery approaches, discussing the benefits of our proposal.


Full Text: PDF
Type of Paper: Research Paper
Keywords: Semantic Web Services, Service Discovery, Scalability, Service Repositories, Semantic Web Query Languages
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