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Browsing Large Concept Lattices through Tree Extraction and Reduction Methods

Author

Listed:
  • Cassio Melo

    (École Centrale Paris, Paris, France)

  • Bénédicte Le-Grand

    (Centre de Recherche en Informatique, Université Paris 1 Panthéon, Sorbonne, France)

  • Marie-Aude Aufaure

    (Mas Laboratory, École Centrale Paris, Paris, France)

Abstract

Browsing concept lattices from Formal Concept Analysis (FCA) becomes a problem as the number of concepts can grow significantly with the number of objects and attributes. Interpreting the lattice through direct graph-based visualisation of the Hasse diagram rapidly becomes difficult and more synthetic representations are needed. In this work the authors propose an approach to simplify concept lattices by extracting and visualising trees derived from them. The authors further simplify the browse-able trees with two reduction methods: fault-tolerance and concept clustering.

Suggested Citation

  • Cassio Melo & Bénédicte Le-Grand & Marie-Aude Aufaure, 2013. "Browsing Large Concept Lattices through Tree Extraction and Reduction Methods," International Journal of Intelligent Information Technologies (IJIIT), IGI Global, vol. 9(4), pages 16-34, October.
    • Handle: RePEc:igg:jiit00:v:9:y:2013:i:4:p:16-34
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