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

机译:模式匹配阈值函数和ANFIS生成的隶属函数的比较

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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.
机译:模式匹配的任务是识别模式中与语义相关的实体。在经典方法中,在输入模式的模式实体之间建立语义距离,基于该阈值,将实体对基于哪个值将其分类为匹配或不匹配。但是,这种方法在一些与模式匹配相关的问题上比较麻烦,例如精度度量最大化和切割阈值问题。在我们的早期工作中,我们提出了针对此类情况的模式匹配阈值函数的概念。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。这种假定的关系鼓励我们在模式匹配阈值函数和模糊隶属函数之间进行比较,该比较是本文的主题。我们使用ANFIS来获取隶属度函数,将其映射到足够的阈值函数以进行比较。我们的比较分析的结果是,这些映射的功能对彼此非常相似。

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