Reducing the Representation Complexity of Lattice-Based Taxonomies

  • Sergei Kuznetsov
  • Sergei Obiedkov
  • Camille Roth
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4604)


Representing concept lattices constructed from large contexts often results in heavy, complex diagrams that can be impractical to handle and, eventually, to make sense of. In this respect, many concepts could allegedly be dropped from the lattice without impairing its relevance towards a taxonomy description task at a certain level of detail. We propose a method where the notion of stability is introduced to select potentially more pertinent concepts. We present some theoretical properties of stability and discuss several use cases where taxonomy building is an issue.


Stability Index Concept Lattice Formal Context Formal Concept Analysis Epistemic Community 
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-Verlag Berlin Heidelberg 2007

Authors and Affiliations

  • Sergei Kuznetsov
    • 1
  • Sergei Obiedkov
    • 1
    • 2
  • Camille Roth
    • 3
    • 4
  1. 1.Department of Applied Mathematics, Higher School of Economics, MoscowRussia
  2. 2.Moscow Institute of Physics and Technology, MoscowRussia
  3. 3.European Center for Living Technology, VeniceItaly
  4. 4.Department of Sociology, University of Surrey, GuildfordUK

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