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Unsupervised Concept Learning Using Rough Concept Analysis

  • Tu Bao Ho
Conference paper
Part of the Studies in Classification, Data Analysis, and Knowledge Organization book series (STUDIES CLASS)

Summary

Formal concept analysis (Wille, 1982) offers an algebraic tool for representing and analyzing formal concepts, and the rough set theory (Pawlak, 1982) offers an alternative tool to deal with vagueness and uncertainty. Rough concept analysis (Kent, 1994) is an attempt to synthesize common features of these two theories. In this work we develop a method for unsupervised concept learning in the framework of rough concept analysis that aims at finding and using concepts with their approximations.

Keywords

Concept Analysis Formal Concept Concept Lattice Formal Context Formal Concept Analysis 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer Japan 1998

Authors and Affiliations

  • Tu Bao Ho
    • 1
  1. 1.Japan Advanced Institute of Science and TechnologyTatsunokuchi, IshikawaJapan

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