Abstract
Knowledge reduction is one of the key issues in formal concept analysis, and there have been many studies on this topic. Granule knowledge reduction and attribute reduction are two of the most important knowledge reduction in formal concept analysis. Firstly, theorem to character granule knowledge reduction is given, and granule knowledge reduction method in concept lattices based on 0–1 linear integer programming is proposed in this paper. Then, characterization theorems of three types attributes are obtained in attribute reduction, and attribute reduction method in concept lattices based on 0–1 linear integer programming is proposed.
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