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An Incremental Approach for Attribute Reduction in Concept Lattice

机译:概念格属性的约简增量方法

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摘要

One of the key problems of knowledge discovery is knowledge reduction. Concept lattice is an effective tool for data analysis and knowledge processing. The existing works on attribute reduction in concept lattice have mainly been focused on static database. This paper presents an incremental approach to identify reductions from dynamic database. The properties of attributes are discussed within the framework of equivalence classes and the determinant theorem of attribute reduction is presented. Based on the theorem, the reductions can be easily derived. The experimental results validate the effectiveness of the approach.
机译:知识发现的关键问题之一是知识还原。概念格是用于数据分析和知识处理的有效工具。现有的关于概念格属性约简的工作主要集中在静态数据库上。本文提出了一种从动态数据库中识别减少量的增量方法。在等价类的框架内讨论了属性的性质,并提出了属性约简的行列式定理。根据该定理,可以轻松得出约简。实验结果验证了该方法的有效性。

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