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Toward an Update of a Similarity Measurement for a Better Calculation of the Semantic Distance between Ontology Concepts

机译:朝着更好地计算本体概念之间的语义距离的相似性测量的更新

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Computational models of semantic similarity can be found in many applications, with the aim to give this additional knowledge to reason about their data. The choice of a similarity measure is very crucial for a successful implementation of reasoning. In this work, we present an update of similarity calculation presented by Wu and Palmer which is considered the fastest in terms of generation time of similarity. The results show that the measure provides produced a marked improvement in the relevance of the values produced for the two concepts similarity in ontology.
机译:语义相似性的计算模型可以在许多应用中找到,旨在为这些额外的知识提供给他们的数据。相似度量的选择对于成功实施推理来说是至关重要的。在这项工作中,我们介绍了由吴和帕尔默提到的相似性计算的更新,该帕尔默在生成相似度的时间方面被认为是最快的。结果表明,该措施提供了在本体中两个概念相似性产生的值的相关性的显着改善。

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