Image123: a "Web1.0+web2.0+semantic web" based image retrieval system
WISS'10 Proceedings of the 2010 international conference on Web information systems engineering
Enhancing Folksonomy-Based Content Retrieval with Semantic Web Technology
International Journal on Semantic Web & Information Systems
| Hi-index | 0.03 |
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.