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A Framework for Semantic-Based Similarity Measures for εLH-Concepts

机译:εlh概念的语义相似措施框架

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Similarity measures for concepts written in Description Logics (DLs) are often devised based on the syntax of concepts or simply by adjusting them to a set of instance data. These measures do not take the semantics of the concepts into account and can thus lead to unintuitive results. It even remains unclear how these measures behave if applied to new domains or new sets of instance data. In this paper we develop a framework for similarity measures for εLH-concept descriptions based on the semantics of the DL εLH. We show that our framework ensures that the measures resulting from instantiations fulfill fundamental properties, such as equivalence invariance, yet the framework provides the flexibility to adjust measures to specifics of the modelled domain.
机译:用描述逻辑(DLS)编写的概念的相似性措施通常根据概念的语法或简单地将它们调整为一组实例数据来设计。这些措施不会考虑概念的语义,从而可以导致无需结果。它甚至仍然尚不清楚这些测量如何运用于新域或新的实例数据集。在本文中,我们基于DLεlh的语义,为εlh概念描述的相似度措施制定了一个框架。我们展示我们的框架确保了实例化符合实例符合基本属性的措施,例如等价不变性,但框架提供了调整对建模域的细节措施的灵活性。

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