0–1 linear integer programming method for granule knowledge reduction and attribute reduction in concept lattices
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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.
KeywordsConcept lattice Granule knowledge reduction Attribute reduction 0–1 linear integer programming
This work was partially supported by the National Natural Science Foundation of China (GrantNos. 11401469, 11701446) and the Natural Science Foundation of Shanxi Province (2018JM1055) and Natural Science Foundation of Fujian Province (2016J01310).
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