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Formal Concept Analysis for Knowledge Discovery and Data Mining: The New Challenges

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Concept Lattices (ICFCA 2004)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 2961))

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Abstract

Data mining (DM) is the extraction of regularities from raw data, which are further transformed within the wider process of knowledge discovery in databases (KDD) into non-trivial facts intended to support decision making. Formal concept analysis (FCA) offers an appropriate framework for KDD, whereby our focus here is on its potential for DM support. A variety of mining methods powered by FCA have been published and the figures grow steadily, especially in the association rule mining (ARM) field. However, an analysis of current ARM practices suggests the impact of FCA has not reached its limits, i.e., appropriate FCA-based techniques could successfully apply in a larger set of situations. As a first step in the projected FCA expansion, we discuss the existing ARM methods, provide a set of guidelines for the design of novel ones, and list some open algorithmic issues on the FCA side. As an illustration, we propose two on-line methods computing the minimal generators of a closure system.

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Author information

Authors and Affiliations

  1. DIRO, Université de Montréal, Montréal (Qc), Canada

    Petko Valtchev

  2. Département d’informatique et d’ingénierie, UQO, Gatineau (Qc), Canada

    Rokia Missaoui

  3. Département d’informatique, UQAM, Montréal (Qc), Canada

    Robert Godin

Authors
  1. Petko Valtchev
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  2. Rokia Missaoui
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  3. Robert Godin
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Editor information

Editors and Affiliations

  1. School of Information Systems and Technology, University of Wollongong, Northfields Ave, NSW 2522, Wollongong, Australia

    Peter Eklund

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Valtchev, P., Missaoui, R., Godin, R. (2004). Formal Concept Analysis for Knowledge Discovery and Data Mining: The New Challenges. In: Eklund, P. (eds) Concept Lattices. ICFCA 2004. Lecture Notes in Computer Science(), vol 2961. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-24651-0_30

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  • DOI: https://doi.org/10.1007/978-3-540-24651-0_30

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-21043-6

  • Online ISBN: 978-3-540-24651-0

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