Semantic Web Dog Food

Presented at: 6th International and 2nd Asian Semantic Web Conference (ISWC2007+ASWC2007)

by Rachanee Ungrangsi, Chutiporn Anutariya, Vilas Wuwongse

Automatic knowledge reuse for Semantic Web applications imposes several challenges on ontology search. Existing ontology retrieval systems merely return a lengthy list of relevant single ontologies, which may not completely cover the specified user requirements. Therefore, there arises an increasing demand for a tool or algorithm with a mechanism to check concept adequacy of existing ontologies with respect to a user query, and then recommend a single or combination of ontologies which can entirely fulfill the requirements. Thus, this paper develops an algorithm, namely combiSQORE to determine whether the available collection of ontologies is able to completely satisfy a submitted query and return a single or combinative ontology that guarantees query coverage. In addition, it ranks the returned answers based on their conceptual closeness and query coverage. The experimental results show that the proposed algorithm is simple, efficient and effective.

combiSQORE: An Ontology Combination Algorithm was presented at this event.

Keywords: Data management, Ontology (computer science), Ontology (Computer Science), Ontology alignment, Ontology Alignment, Semantic Web

Resource URI on the dog food server: http://data.semanticweb.org/conference/iswc-aswc/2007/tracks/research/papers/561
Same as: http://revyu.com/things/iswc-aswc-2007-research-paper-561-combisqore-an

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