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Instance-based domain ontological view creation towards semantic integration
Authors:Yunjiao Xue  Hamada H. Ghenniwa  Weiming Shen
Affiliation:1. Lyles School of Civil Engineering, Purdue University, 550 W Stadium Ave, West Lafayette, IN 47907-2051, USA;2. Department of Civil Engineering, Science and Research Branch, Islamic Azad University, Tehran, Iran;3. Islamic Azad University of Shahrood, Tehran, Iran;1. Invicara Pte Ltd., Singapore;2. Georgia Institute of Technology, USA;3. Louisiana State University, USA;2. Division of Orthopedic Surgery, Montreal General Hospital, McGill University, Montreal, Quebec, Canada;3. Department of Biomedical Engineering, Amirkabir University of Technology (Tehran Polytechnic), Tehran, Iran
Abstract:In many domains today there are very limited explicit ontologies established for implementing information systems. Traditional ontology-driven semantic integration approaches cannot be directly applied in integrating these information systems. Usually, the information systems have schemas, a type of formal information model, for their information repositories which to some extent imply the semantics of the information. Each schema actually reflects a specific view of the domain conceptualization. This paper investigates the theoretical foundation of ontologies and extends the traditional ontology concept to the ontological view concept. It proposes to use ontological views to address the challenge of semantic integration. The proposed approach adopts the schemas to create local ontological views, uses data instances of the information systems to discover semantic relationships between the concepts within the ontological views, and builds a domain ontological view based on the discovered equivalence mappings. It applies the hierarchical clustering technique on the data instances and, in the further analysis, uses the clusters to reduce the cost of processing a large amount of data. The matching of concept properties is based on the probability distribution of the data instances. The experimental results have demonstrated the effectiveness of this approach.
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