Title
Improving semantic web services discovery using SPARQL-based repository filtering
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 Logic 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.
Year
DOI
Venue
2012
10.1016/j.websem.2012.07.002
J. Web Sem.
Keywords
Field
DocType
actual discovery,current discovery approach,comprehensive performance analysis,semantic web services discovery,discovery mechanism,improving semantic web service,discarding service description,filter service repository,service request,overall performance,sparql-based repository,discovery performance,description logic,search space,scalability,service discovery
Ontology,Data mining,Information retrieval,Semantic Web Stack,Computer science,Description logic,SPARQL,OWL-S,Social Semantic Web,Service discovery,Database,Scalability
Journal
Volume
Issue
ISSN
17
C
1570-8268
Citations 
PageRank 
References 
23
1.03
37
Authors
3
Name
Order
Citations
PageRank
José María García11158.83
David Ruiz2703.50
Antonio Ruiz-Cortés3124450.26