Granulation based approximate ontologies capture

Authors:
Taorong Qiu;Xiaoqing Chen;Qing Liu;Houkuan Huang
Affiliations:
School of Computer and Information Technology, Beijing Jiaotong University, Beijing, China and Department of Computer, Nanchang University, Nanchang, Jiangxi, China;School of Computer and Information Technology, Beijing Jiaotong University, Beijing, China and Department of Computer, Nanchang University, Nanchang, Jiangxi, China;Department of Computer, Nanchang University, Nanchang, Jiangxi, China;School of Computer and Information Technology, Beijing Jiaotong University, Beijing, China
Venue:
RSKT'07 Proceedings of the 2nd international conference on Rough sets and knowledge technology
Year:
2007

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Abstract

Ontologies are of vital importance to the successful realization of semantic Web. Currently, the existing concepts in ontologies are not approximate but clear. However, in real application domains many concepts are difficult to define explicitly. In order to fulfill semantic Web, it's not only necessary but also important to study approximate concepts and approximate ontologies generated from the approximate concepts. In this paper, based on the principle of granular computing, a granulation model for representing approximate ontologies was constructed. Then algorithms for capturing approximate concepts and generating approximate ontologies were proposed and illustrated with a real example.