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Application-oriented Purely Semantic Precision And Recall For Ontology Mapping Evaluation

机译:面向应用的纯语义精度和本体映射评估调用

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摘要

To evaluate and compare various ontology mapping algorithms, it is indispensable to apply them to a group of test ontology pairs and compare the results (named mappings, also known as alignments) with some reference. Currently, the most widely used criteria are precision and recall. However, they do not always work well while facing objects with semantics, like ontologies and alignments, because they only consider "exact" correspondences but ignore "close" ones. Some new measures have been proposed to solve the problem. However, they have their own limitations, and do not rely purely on the semantics of ontologies and alignments. A framework for purely semantic precision and recall of ontology mapping is proposed in this paper, which can guarantee that the measures are purely semantic. Then a group of application-oriented measures are proposed to instantiate the framework. In some examples these measures are compared with former ones.
机译:为了评估和比较各种本体映射算法,必不可少的是将它们应用于一组测试本体对,并将结果(称为映射,也称为比对)与某些参考进行比较。当前,最广泛使用的标准是精度和召回率。但是,当面对带有语义的对象(如本体和对齐方式)时,它们并不总是很好用,因为它们仅考虑“精确”对应,而忽略“紧密”对应。已经提出了一些解决该问题的新措施。但是,它们有其自身的局限性,并且不完全依赖于本体论和对齐方式的语义。提出了一种纯语义精度和本体映射回忆的框架,可以保证度量是纯语义的。然后提出了一组面向应用的措施来实例化该框架。在某些示例中,将这些措施与以前的措施进行了比较。

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