Efficient Mining of Association Rules Based on Formal Concept Analysis.
2005.
Lotfi Lakhal and Gerd Stumme.
[doi]
[abstract]
[BibTeX]
Association rules are a popular knowledge discovery technique for
warehouse basket analysis. They indicate which items of the
warehouse are frequently bought together. The problem of association
rule mining has first been stated in 1993. Five years later, several
research groups discovered that this problem has a strong connection
to Formal Concept Analysis (FCA). In this survey, we will first
introduce some basic ideas of this connection along a specific
algorithm, and show how FCA helps in reducing the number
of resulting rules without loss of information, before giving a
general overview over the history and state of the art of applying
FCA for association rule mining.
Generating a Condensed Representation for Association Rules.
Journal Intelligent Information Systems (JIIS), 24(1):29-60, 2005.
Nicolas Pasquier, Rafik Taouil, Yves Bastide, Gerd Stumme and Lotfi Lakhal.
[doi]
[BibTeX]
Efficient Data Mining Based on Formal Concept Analysis.
In: A. Hameurlain, R. Cicchetti and R. Traunmüller, editors,
Database and Expert Systems Applications. Proc. DEXA 2002, volume 2453, series LNCS, pages 534-546.
Springer, Heidelberg, 2002.
G. Stumme.
[doi]
[BibTeX]
Intelligent Structuring and Reducing of Association Rules and with Formal Concept Analysis.
In: F. Baader, G. Brewker and T. Eiter, editors,
KI 2001: Advances in Artificial Intelligence. KI 2001, volume 2174, series LNAI, pages 335-350.
Springer, Heidelberg, 2001.
G. Stumme, R. Taouil, Y. Bastide, N. Pasquier and L. Lakhal.
[doi]
[BibTeX]
Levelwise Search of Frequent Patterns.
In:
Actes des 16ièmes Journées Bases de Données Avancées, pages 307-322.
Blois, France, 2000.
Y. Bastide, R. Taouil, N. Pasquier, G. Stumme and L. Lakhal.
[doi]
[BibTeX]
Mining Frequent Patterns with Counting Inference..
SIGKDD Explorations, Special Issue on Scalable Algorithms, 2(2):71-80, 2000.
Y. Bastide, R. Taouil, N. Pasquier, G. Stumme and L. Lakhal.
[BibTeX]
Mining Minimal Non-Redundant Association Rules Using Frequent Closed Itemsets.
In: J. Lloyd, V. Dahl, U. Furbach, M. Kerber, K.-K. Laus, C. Palamidessi, L. Pereira, Y. Sagiv and P. Stuckey, editors,
Computational Logic -- CL 2000 Proc. CL'00, volume 1861, series LNAI.
Springer, Heidelberg, 2000.
Y. Bastide, N. Pasquier, R. Taouil, G. Stumme and L. Lakhal.
[doi]
[BibTeX]
Approximation of Frequency Queris by Means of Free-Sets.
In:
Principles of Data Mining and Knowledge Discovery, pages 75-85.
2000.
Jean-Francois Boulicaut, Artur Bykowski and Christophe Rigotti.
[doi]
[BibTeX]
Conceptual Knowledge Discovery with Frequent Concept Lattices.
FB4-Preprint 2043, TU Darmstadt, 1999.
G. Stumme.
[doi]
[BibTeX]
Pruning closed itemset lattices for associations rules..
In: M. Bouzeghoub, editor,
Bases de Donn�es Avanc�es.
1998.
Nicolas Pasquier, Yves Bastide, Rafik Taouil and Lotfi Lakhal.
[doi]
[BibTeX]
Pruning closed itemset lattices for associations rules..
In: M. Bouzeghoub, editor,
Bases de Données Avancées.
1998.
Nicolas Pasquier, Yves Bastide, Rafik Taouil and Lotfi Lakhal.
[doi]
[BibTeX]