Attribute reduction in concept lattice based on discernibility matrix

  • Authors:
  • Wen-Xiu Zhang;Ling Wei;Jian-Jun Qi

  • Affiliations:
  • Faculty of Science, Institute for Information and System Sciences, Xi'an Jiaotong University, Xi'an, P.R. China;,Faculty of Science, Institute for Information and System Sciences, Xi'an Jiaotong University, Xi'an, P.R. China;Institute of Computer Architecture & Network, Xi'an Jiaotong University, Xi'an, P.R. China

  • Venue:
  • RSFDGrC'05 Proceedings of the 10th international conference on Rough Sets, Fuzzy Sets, Data Mining, and Granular Computing - Volume Part II
  • Year:
  • 2005

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Abstract

As an effective tool for knowledge discovery, concept lattice has been successfully applied to various fields. One of the key problems of knowledge discovery is knowledge reduction. This paper studies attribute reduction in concept lattice. Using the idea similar to Skowron and Rauszer's discernibility matrix, the discernibility matrix and function of a concept lattice are defined. Based on discernibility matrix, an approach to attribute reduction in concept lattice is presented, and the characteristics of core attribute are analyzed.