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SQORE : an ontology retrieval framework for the next generation Web
Author(s) -
Ungrangsi R.,
Anutariya C.,
Wuwongse V.
Publication year - 2009
Publication title -
concurrency and computation: practice and experience
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.309
H-Index - 67
eISSN - 1532-0634
pISSN - 1532-0626
DOI - 10.1002/cpe.1385
Subject(s) - computer science , information retrieval , ontology , upper ontology , ontology based data integration , owl s , ontology alignment , suggested upper merged ontology , ranking (information retrieval) , ontology inference layer , semantic similarity , semantic web , semantic web stack , philosophy , epistemology
In order to resolve semantic issues in the Semantic Web and in the Semantic Knowledge Grid, tools for retrieving a suitable ontology from an ontology database are essential. However, existing approaches to ontology retrieval base their search mechanisms solely on keyword matching and return a lengthy list of relevant ontologies that may not satisfy user requirements. Users, therefore, are not equipped with expressive means to structurally and semantically describe their ontology needs. To tackle this problem, this paper develops a framework for Semantic Query based Ontology Retrieval, namely, SQORE. It enables precise formulation of a semantic query in order to best capture a user's ontology requirements, which include not only the desired class and property names, but also their relations and restrictions. SQORE employs the XML Declarative Description theory as its theoretical foundation for modeling ontology databases and evaluating semantic queries. Moreover, similarity score is formally defined as a key metric for ranking the resulting ontologies based on their conceptual closeness, their query coverage and their compactness with respect to the given query. A Web‐based prototype system is developed as a proof of concept, and experiments are conducted to evaluate the effectiveness of the SQORE framework. Experimental results indicate that SQORE yields better results and better rankings compared with existing systems. Copyright © 2009 John Wiley & Sons, Ltd.