Publications
Efficient Mining of Association Rules Based on Formal Concept Analysis
Lakhal, L. & Stumme, G.
'Formal Concept Analysis: Foundations and Applications', 3626(), Springer, Heidelberg, 180-195 (2005) [pdf]
Association rules are a popular knowledge discovery technique for
rehouse basket analysis. They indicate which items of the
rehouse are frequently bought together. The problem of association
le mining has first been stated in 1993. Five years later, several
search groups discovered that this problem has a strong connection
Formal Concept Analysis (FCA). In this survey, we will first
troduce some basic ideas of this connection along a specific
gorithm, and show how FCA helps in reducing the number
resulting rules without loss of information, before giving a
neral overview over the history and state of the art of applying
A for association rule mining.
Generating a Condensed Representation for Association Rules
Pasquier, N.; Taouil, R.; Bastide, Y.; Stumme, G. & Lakhal, L.
Journal Intelligent Information Systems (JIIS), 24(1) 29-60 (2005) [pdf]
Efficient Data Mining Based on Formal Concept Analysis
Stumme, G.
Hameurlain, A.; Cicchetti, R. & Traunmüller, R., ed., 'Database and Expert Systems Applications. Proc. DEXA 2002', 2453(), LNCS, Springer, Heidelberg, 534-546 (2002) [pdf]
Intelligent Structuring and Reducing of Association Rules and with Formal Concept Analysis
Stumme, G.; Taouil, R.; Bastide, Y.; Pasquier, N. & Lakhal, L.
Baader, F.; Brewker, G. & Eiter, T., ed., 'KI 2001: Advances in Artificial Intelligence. KI 2001', 2174(), LNAI, Springer, Heidelberg, 335-350 (2001) [pdf]
Levelwise Search of Frequent Patterns
Bastide, Y.; Taouil, R.; Pasquier, N.; Stumme, G. & Lakhal, L.
, 'Actes des 16ièmes Journées Bases de Données Avancées', Blois, France, 307-322 (2000) [pdf]
Mining Frequent Patterns with Counting Inference.
Bastide, Y.; Taouil, R.; Pasquier, N.; Stumme, G. & Lakhal, L.
SIGKDD Explorations, Special Issue on Scalable Algorithms, 2(2) 71-80 (2000)
Mining Minimal Non-Redundant Association Rules Using Frequent Closed Itemsets
Bastide, Y.; Pasquier, N.; Taouil, R.; Stumme, G. & Lakhal, L.
Lloyd, J.; Dahl, V.; Furbach, U.; Kerber, M.; Laus, K.-K.; Palamidessi, C.; Pereira, L.; Sagiv, Y. & Stuckey, P., ed., 'Computational Logic --- CL 2000 Proc. CL'00', 1861(), LNAI, Springer, Heidelberg (2000) [pdf]
Approximation of Frequency Queris by Means of Free-Sets
Boulicaut, J.-F.; Bykowski, A. & Rigotti, C.
, 'Principles of Data Mining and Knowledge Discovery', 75-85 (2000) [pdf]
Conceptual Knowledge Discovery with Frequent Concept Lattices
Stumme, G.
1999, Technical report, TU Darmstadt [pdf]
Pruning closed itemset lattices for associations rules.
Pasquier, N.; Bastide, Y.; Taouil, R. & Lakhal, L.
Bouzeghoub, M., ed., 'Bases de Donn�es Avanc�es' (1998) [pdf]
Pruning closed itemset lattices for associations rules.
Pasquier, N.; Bastide, Y.; Taouil, R. & Lakhal, L.
Bouzeghoub, M., ed., 'Bases de Données Avancées' (1998) [pdf]