Detection Algorithm of Semantic Inconsistency for Fuzzy Ontology Merging

Abstract:

Fuzzy ontology can be built to effectively deal with uncertainty and ambiguity for domain knowledge modeling. Merging multiple fuzzy local ontologies may implement semantic integration of multiple data sources and semantic interoperability between heterogeneous systems in distributed environment. In order to solve the problem of semantic inconsistency mappings for fuzzy ontology merging system, we proposed a detection algorithm of semantic inconsistency mapping which includes sub detection methods of circular semantic inconsistency, subclass-of axiom redundancy semantic inconsistency, attribute membership semantic inconsistency and disjoint axioms redundancy semantic inconsistency. With the detection algorithm of semantic inconsistency, we establish fuzzy ontology merging system in experiment.

• Periodical: Applied Mechanics and Materials (Volumes 530-531)
• Pages: 407-412
• DOI: https://doi.org/10.4028/www.scientific.net/AMM.530-531.407
• Online since: February 2014
• Authors: Yong Hong Luo*, Wei Ming Liu
• Keywords: Fuzzy Ontology, Membership Grade, Ontology Merging, Semantic Inconsistency Mapping

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