A comparison of schema matching threshold function and ANFIS generated membership function

B. Villányi, P. Martinek
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引用次数: 3

Abstract

Schema matching has the task of identifying semantically related entities in schemas. In the classic approach, a semantic distance is established among schema entities of the input schemas, based on which values the entity pairs are classified as match or non-match by means of a threshold value. This approach is, however, cumbersome in some schema matching related problem, like the accuracy measure maximization and the cutting threshold problem. In our earlier works, we proposed the concept of the schema matching threshold function for such cases. We assumed that the schema matching threshold function is, however, highly related to the concept of fuzzy membership functions. This assumed relation has encouraged us to perform a comparison between the schema matching threshold function and the fuzzy membership function which comparison is the topic of this paper. We used ANFIS for obtaining membership functions which were mapped to adequate threshold functions in order to be able to compare them. The outcome of our comparative analysis was that these mapped function pairs significantly resemble to each other.
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比较了模式匹配阈值函数与ANFIS生成的隶属度函数
模式匹配的任务是识别模式中语义相关的实体。经典的方法是在输入模式的模式实体之间建立语义距离,根据语义距离的值,通过阈值将实体对分类为匹配或不匹配。然而,这种方法在一些与模式匹配相关的问题中比较麻烦,如精度度量最大化和切割阈值问题。在我们早期的工作中,我们提出了模式匹配阈值函数的概念。然而,我们假设模式匹配阈值函数与模糊隶属函数的概念高度相关。这种假设关系促使我们对模式匹配阈值函数和模糊隶属度函数进行比较,而比较正是本文的主题。我们使用ANFIS来获得映射到适当阈值函数的隶属函数,以便能够比较它们。我们比较分析的结果是,这些映射的功能对彼此显着相似。
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