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Concepts reduction in formal concept analysis with fuzzy setting using Shannon entropy

机译:使用Shannon熵进行模糊设置的形式化概念分析中的概念归约

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摘要

In this paper we propose a method for reducing the number of formal concepts in formal concept analysis of data with fuzzy attributes. We compute the weight of fuzzy formal concepts based on Shannon entropy. Further, the number of fuzzy formal concepts is reduced at chosen granulation of their computed weight. We show that the results obtained from the proposed method are in good agreement with Levenshtein distance method and interval-valued fuzzy formal concepts method but with less computational complexity.
机译:在本文中,我们提出了一种减少带有模糊属性的数据的形式概念分析中形式概念数量的方法。我们基于香农熵计算模糊形式概念的权重。此外,在选择计算形式的权重时,减少了模糊形式概念的数量。我们表明,从所提出的方法获得的结果与Levenshtein距离方法和区间值模糊形式概念方法具有很好的一致性,但是计算复杂度较低。

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