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Instance-based domain ontological view creation towards semantic integration

机译:基于实例的领域本体视图创建,实现语义集成

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摘要

In many domains today there are very limited explicit ontologies established for implementing information systems. Traditional ontology-driven semantic integration approaches cannot be directly applied in integrating these information systems. Usually, the information systems have schemas, a type of formal information modeL., for their information repositories which to some extent imply the semantics of the information. Each schema actually reflects a specific view of the domain conceptualization. This paper investigates the theoretical foundation of ontologies and extends the traditional ontology concept to the ontological view concept. It proposes to use ontological views to address the challenge of semantic integration. The proposed approach adopts the schemas to create local ontological views, uses data instances of the information systems to discover semantic relationships between the concepts within the ontological views, and builds a domain ontological view based on the discovered equivalence mappings. It applies the hierarchical clustering technique on the data instances and, in the further analysis, uses the clusters to reduce the cost of processing a large amount of data. The matching of concept properties is based on the probability distribution of the data instances. The experimental results have demonstrated the effectiveness of this approach.
机译:今天,在许多领域中,为实施信息系统而建立的显式本体非常有限。传统的本体驱动的语义集成方法不能直接应用于集成这些信息系统。通常,信息系统具有用于其信息存储库的模式,这是形式化信息模式L.,在某种程度上暗示着信息的语义。每个方案实际上反映了域概念化的特定视图。本文研究了本体论的理论基础,并将传统本体论概念扩展到本体论视图概念。它建议使用本体论视图来解决语义集成的挑战。所提出的方法采用模式来创建本地本体视图,使用信息系统的数据实例来发现本体视图内的概念之间的语义关系,并基于所发现的等价映射来构建域本体视图。它在数据实例上应用了分层聚类技术,并在进一步分析中使用了聚类来减少处理大量数据的成本。概念属性的匹配基于数据实例的概率分布。实验结果证明了这种方法的有效性。

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