Soft Computing

, Volume 23, Issue 2, pp 383–391 | Cite as

0–1 linear integer programming method for granule knowledge reduction and attribute reduction in concept lattices

  • Lifeng LiEmail author
  • Dongxiao Zhang


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.


Concept 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).

Compliance with ethical standards

Conflict of interest

The authors declare that they have no conflict of interest.

Ethical approval

This article does not contain any studies with human or animal participants performed by any of the authors.

Informed consent

Informed consent is obtained from all individual participants included in the study.


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Copyright information

© Springer-Verlag GmbH Germany, part of Springer Nature 2018

Authors and Affiliations

  1. 1.School of ScienceXian University of Posts and TelecommunicationsXianChina
  2. 2.Shaanxi Key Laboratory of Network Data Analysis and Intelligent ProcessingXian University of Posts and TelecommunicationsXianChina
  3. 3.School of ScienceJimei UniversityXiamenChina

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