AN ENHANCED SPARQL - BASED FILTERING AND RANKING OF SEMANTIC WEB SERVICES

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 scalability issue, a lightweight process is introduced before the discovery mechanism. This process analyses the user request in order to extract the concepts. Then the service repository is filtered based on the concepts by generating SPARQL queries. The unrelated services are discarded during filtering. This filtering will fairly reduce the input for the discovery process. To avoid discarding relevant services during exact filtering, semantic filtering is performed. During this filtering similar words are found using Word Net. Ontology tree is created for the similar words found, from which the relation between the words are found more clearly. These similar words are also included in the automatically generated SPARQL queries. Seven degrees of matching are possible based on the obtained ontology. Based on these degrees of match the services are ordered and stored in the filtered repository. This can provide better efficiency in mining relevant data from the service repository than exact keyword based filtering. Thus an initial set of relevant services are found before the discovery technique which in turn will improve the performance of the matchmaking process.