Merge-Based Computation of Minimal Generators

  • Céline Frambourg
  • Petko Valtchev
  • Robert Godin
Part of the Lecture Notes in Computer Science book series (LNCS, volume 3596)


Minimal generators (mingens) of concept intents are valuable elements of the Formal Concept Analysis (FCA) landscape, which are widely used in the database field, for data mining but also for database design purposes. The volatility of many real-world datasets has motivated the study of the evolution in the concept set under various modifications of the initial context. We believe this should be extended to the evolution of mingens. In the present paper, we build up on previous work about the incremental maintenance of the mingen family of a context to investigate the case of lattice merge upon context subposition. We first recall the theory underlying the singleton increment and show how it generalizes to lattice merge. Then we present the design of an effective merge procedure for concepts and mingens together with some preliminary experimental results about its performance.


Equivalence Class Association Rule Minimal Generator Association Rule Mining Concept Lattice 
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 2005

Authors and Affiliations

  • Céline Frambourg
    • 1
  • Petko Valtchev
    • 2
  • Robert Godin
    • 1
  1. 1.Département d’informatiqueUQAMMontréalCanada
  2. 2.DIROUniversité de MontréalMontréalCanada

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