| Concept Approximation between Fuzzy Ontologies |
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| 作者姓名： | LI Yan-hui XU Bao-wen LU Jian-jiang KANG Da-zhou ZHOU Jing-jing |
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| 作者单位： | [1]Department of Computer Science and Engineering, Southeast University, Nanjing 210096, Jiangsu, China [2]Jiangsu Institute of Software Quality, Nanjing 210096, Jiangsu,China [3]State Key Laboratory of Software Engineering, Wuhan University,Wuhan 430072, Hubei, China [4]Institute of Science, The People＇s Liberation Army University of Science and Technology, Nanjing 210007, Jiangsu, China |
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| 摘 要： | 0 IntroductionOnktnoolwolgeydg1]ei so tnh eth bea ssiec moaf nstihcari Wnge ban2]d. re Tuhsienregare concepts ,relations ,instances and axioms in theontologies .Classic ontologies are based on descrip-tionlogics3],whichinterpret conceptsinthe ontol-ogy as sets of instances . However , we often needrepresent uncertainty information in practice,e.g.text and multi media information. The classic ontol-ogies are insufficient to represent such uncertaintyinformation, because it may be uncertain …
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| 关 键 词： | 语义Web 模糊存在论 模糊表达 模糊概念 概念近似 |
| 文章编号： | 1007-1202（2006）01-0073-05 |
| 收稿时间： | 2005-05-20 |
Concept approximation between fuzzy ontologies |
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| LI Yan-hui XU Bao-wen LU Jian-jiang KANG Da-zhou ZHOU Jing-jing.Concept Approximation between Fuzzy Ontologies[J].Wuhan University Journal of Natural Sciences,2006,11(1):73-77. |
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| Authors: | Li Yan-hui Xu Bao-wen Lu Jian-jiang Kang Da-zhou Zhou Jing-jing |
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| Institution: | (1) Department of Computer Science and Engineering, Southeast University, 210096 Nanjing, Jiangsu, China;(2) Jiangsu Institute of Software Quality, 210096 Nanjing, Jiangsu, China;(3) State Key Laboratory of Software Engineering, Wuhan University, 430072 Wuhan, Hubei, China;(4) Institute of Science, The People's Liberation Army University of Science and Technology, 210007 Nanjing, Jiangsu, China |
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| Abstract: | Fuzzy ontologics are efficient tools to handle fuzzy and uncertain knowledge on the semantic web; but there are heterogeneity problems when gaining interoperability among different fuzzy ontologies. This paper uses concept approximation between fuzzy ontologies based on instances to solve the heterogeneity problems. It firstly proposes an instance selection technology based on instance clustering and weighting to unify the fuzzy interpretation of different ontologies and reduce the number of instances to increase the efficiency. Then the paper resolves the problem of computing the approximations of concepts into the problem of computing the least upper approximations of atom concepts. It optimizes the search strategies by extending atom concept sets and defining the least upper bounds of concepts to reduce the searching space of the problem. An efficient algorithm for searching the least upper bounds of concept is given. |
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