Part of the book series:Advances in Intelligent and Soft Computing ((AINSC,volume 62))
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Abstract
Ontologies now play an important role for many knowledge-intensive applications for which they provide a way to describe and structure the information on the web. Fuzzy ontologies extend the representation ability of traditional ontologies to handle fuzzy concepts. However, heterogeneity between ontologies still need to be solve, as current ontology mapping technologies are not sufficient for fuzzy ontologies. For the task of detecting and retrieving relevant ontologies, this paper proposes an approach to measure concept similarity between fuzzy ontologies. It applies the fuzzy sets to represent fuzzy concepts, and evaluates the concept similarity by their common characters of linguistics, fuzzy set, super-concepts, sub-concepts, instances and properties.
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Authors and Affiliations
College of Computer Science and Technology, Harbin Engineering University, Harbin, 150001, China
Wang Ying, Zhang Ru-bo & Lai Ji-bao
- Wang Ying
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- Zhang Ru-bo
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- Lai Ji-bao
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Editors and Affiliations
Guangzhou University, China
Bingyuan Cao
Chongqing University of Science and Technology, Chongqing, PR China
Tai-Fu Li
Hainan Normal University, Hainan, PR China
Cheng-Yi Zhang
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Ying, W., Ru-bo, Z., Ji-bao, L. (2009). Measuring Concept Similarity between Fuzzy Ontologies. In: Cao, B., Li, TF., Zhang, CY. (eds) Fuzzy Information and Engineering Volume 2. Advances in Intelligent and Soft Computing, vol 62. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-03664-4_18
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