Affiliation:
1. Dalian Maritime University
2. Hebei Polytechnic University
Abstract
With the rapid development of the semantic web, determining the degree of similarity between concepts from same or different ontologies plays an increasing crucial role. In this paper, a new similarity model based on lattice structural information is proposed to evaluate the similarity degree between fuzzy concepts in the framework of fuzzy formal concept analysis. The proposed method preserves more structural information, which can be viewed as another extension and development of de Souza and Davis’s model in fuzzy context.
Publisher
Trans Tech Publications, Ltd.
Reference14 articles.
1. X.J. Wan: Beyond topical similarity: a structural similarity measure for retrieving highly similar documents, Knowledge and Information Systems, 15(2008), pp.55-73.
2. Y. Zhao, W. Halang, X. Wang: Rough ontology mapping in E-Business integratio, Studies in Computational Intelligence, 37(2007), pp.75-93.
3. K. de Souza, J. Davis: Aligning ontologies and evaluating concept similarities, in: On the Move to Meaningful Internet Systems 2004: CoopIS, DOA, and ODBASE, Springer Berlin (2004), pp.1012-1029.
4. G. Stumme, A. Maedche: FCA-MERGE: bottom-up merging of ontologies, in: Proc 7th Intl. Conf. on Artificial Intelligence, Seattle, WA, USA, (2001), pp.1-6.
5. T. Hsieh, K. Tsai, C. Chen et al.: Query-based ontology approach for semantic search, in: 6th International Conference on Machine Learning and Cybernetics, Hongkong, China (2007), pp.2970-2975.