Soft Computing

, Volume 15, Issue 6, pp 1115–1128

Rule acquisition and attribute reduction in real decision formal contexts

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DOI: 10.1007/s00500-010-0578-y

Cite this article as:
Yang, HZ., Yee, L. & Shao, MW. Soft Comput (2011) 15: 1115. doi:10.1007/s00500-010-0578-y

Abstract

Formal Concept Analysis of real set formal contexts is a generalization of classical formal contexts. By dividing the attributes into condition attributes and decision attributes, the notion of real decision formal contexts is introduced. Based on an implication mapping, problems of rule acquisition and attribute reduction of real decision formal contexts are examined. The extraction of “if–then” rules from the real decision formal contexts, and the approach to attribute reduction of the real decision formal contexts are discussed. By the proposed approach, attributes which are non-essential to the maximal s rules or l rules (to be defined later in the text) can be removed. Furthermore, discernibility matrices and discernibility functions for computing the attribute reducts of the real decision formal contexts are constructed to determine all attribute reducts of the real set formal contexts without affecting the results of the acquired maximal s rules or l rules.

Keywords

Attribute reductionConcept latticeFormal concept analysisReal relationRules acquisition

Copyright information

© Springer-Verlag 2010

Authors and Affiliations

  1. 1.Faculty of ScienceXi’an Jiaotong UniversityXi’anPeople’s Republic of China
  2. 2.Department of Geography and Resource Management, Center for Environmental Policy and Resource ManagementUniversity of Hong KongHong KongPeople’s Republic of China
  3. 3.Institute of Space and Earth Information ScienceThe Chinese University of Hong KongHong KongPeople’s Republic of China
  4. 4.College of Information Science and TechnologyShihezi UniversityShiheziPeople’s Republic of China