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A graph-based approach for resolving incoherent ontology mappings

机译:基于图的解决非相干本体映射的方法

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Ontology mappings are regarded as the semantic bridges that link entities from different yet overlapping ontologies in order to support knowledge sharing and reuse on the Semantic Web. However, mappings can be wrong and result in logical conflicts among ontologies. Such kind of mappings are called incoherent mappings. As an important part of ontology matching, mapping validation aims at detecting the conflicts and restoring the coherence of mappings. In this paper, we propose a graph-based approach which is complete for detecting incoherent mappings among DL-Lite ontologies. The lightweight DL-Lite family of description logics stand out for tractable reasoning and efficient query answering capabilities. Our approach consists of a set of graph construction rules, a graph-based incoherence detection algorithm, and a graph-based incoherence repair algorithm. We propose and formalize three repair principles in an attempt to measure the wrong mappings, where the notion of common closures w.r.t. a mapping arc in the constructed graph is introduced. These principles feature a global removal strategy that is independent of individual ontology matchers. In order to relieve the loss of information among ontologies in the repair process, we further define a mapping revision operator so that common closures related to the removed mappings can be preserved in the graph. We implement the graph-based algorithms and evaluate their performance in a comparison with state-of-the-art systems on real-world ontologies. Experimental results show that our approach can remove more wrong mappings and achieve better repairing results in most of the cases.
机译:本体映射被视为链接来自不同但重叠的本体的实体的语义桥,以支持语义Web上的知识共享和重用。但是,映射可能是错误的,并导致本体之间的逻辑冲突。这种映射称为非相干映射。作为本体匹配的重要组成部分,映射验证的目的是检测冲突并恢复映射的一致性。在本文中,我们提出了一种基于图的方法,该方法可用于检测DL-Lite本体之间的不连贯映射。轻量级的DL-Lite描述逻辑系列以易于处理的推理和高效的查询回答功能而著称。我们的方法包括一组图形构造规则,一个基于图的不相关检测算法和一个基于图的不相关修复算法。为了提出错误的映射,我们提出了三种修复原则并进行了形式化,其中常见的闭包概念是w.r.t.在构造的图形中引入了映射弧。这些原则具有独立于各个本体匹配者的全局删除策略。为了减轻修复过程中本体之间的信息丢失,我们进一步定义了映射修订运算符,以便可以在图中保留与已删除映射有关的通用闭包。我们实现了基于图的算法,并与现实世界中的最新系统进行了比较,评估了它们的性能。实验结果表明,在大多数情况下,我们的方法可以消除更多错误的映射并获得更好的修复结果。

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