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Dealing with fuzzy ontology integration problem by using constraint satisfaction problem

机译:利用约束满足问题处理模糊本体集成问题

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The problem of fuzzy ontology integration can be divided into two phases: the matching phase between ontologies and conflicting resolution on fuzzy values. This paper focuses on the problems of the matching phase, which currently has exhaustive and heuristic approaches. While the exhaustive method has many matching errors, most of the matched pairs between the two ontologies are detected. The heuristic approach uses the ontology nature to trim the non-homologous pairs which can decrease significantly the number of mismatching pairs, but often skips lots of homologous element pairs. To overcome the disadvantages of the two approaches, we proposed to use the constraint satisfaction problem (CSP) for modeling the ontology matching problem. In particular, we introduce constraints and suggest optimal function to minimize the matching errors. In the experiment, the mismatching pairs between ontologies are significantly reduced by applying CSP for refinement.
机译:模糊本体集成的问题可以分为两个阶段:本体之间的匹配阶段和模糊值的解析冲突。本文着重于匹配阶段的问题,该阶段目前具有详尽且启发式的方法。尽管穷举方法具有许多匹配错误,但是可以检测到两种本体之间的大多数匹配对。启发式方法利用本体的性质来修剪非同源对,这可以显着减少不匹配对的数量,但通常会跳过很多同源元素对。为了克服这两种方法的缺点,我们提出使用约束满足问题(CSP)对本体匹配问题进行建模。特别是,我们引入约束条件并建议最佳功能以最大程度地减小匹配误差。在实验中,通过应用CSP进行精化,可大大减少本体之间的不匹配对。

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