Pasquier, Nicolas and Taouil, Rafik and Bastide, Yves and Stumme, Gerd and Lakhal, Lotfi
Generating a Condensed Representation for Association Rules
Journal Intelligent Information Systems (JIIS)
Kluwer Academic Publishers
2005
24
29-60
1
http://www.kde.cs.uni-kassel.de/stumme/papers/2005/pasquier2005generating.pdf
concept, discovery, 2005, association, OntologyHandbook, l3s, analysis, kdd, itemset, myown, rule, data, knowledge, closed, formal, rules, itegpub, condensed, fca, sets, representations, mining
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Pasquier, Nicolas and Taouil, Rafik and Bastide, Yves and Stumme, Gerd and Lakhal, Lotfi
Generating a Condensed Representation for Association Rules
Journal Intelligent Information Systems (JIIS)
Kluwer Academic Publishers
2005
24
29-60
1
http://www.kde.cs.uni-kassel.de/stumme/papers/2005/pasquier2005generating.pdf
concept, discovery, 2005, association, OntologyHandbook, l3s, analysis, kdd, itemset, myown, rule, data, knowledge, closed, formal, rules, itegpub, condensed, fca, sets, representations, mining
Publications of Gerd Stumme
Stumme, Gerd and Taouil, Rafik and Bastide, Yves and Pasquier, Nicolas and Lakhal, Lotfi
Computing iceberg concept lattices with TITANIC
Data & Knowledge Engineering
Elsevier Science Publishers B. V.
2002
42
189–222
2
Amsterdam, The Netherlands, The Netherlands
We introduce the notion of iceberg concept lattices
and show their use in knowledge discovery in
databases. Iceberg lattices are a conceptual
clustering method, which is well suited for analyzing
very large databases. They also serve as a condensed
representation of frequent itemsets, as starting
point for computing bases of association rules, and
as a visualization method for association rules.
Iceberg concept lattices are based on the theory of
Formal Concept Analysis, a mathematical theory with
applications in data analysis, information retrieval,
and knowledge discovery. We present a new algorithm
called TITANIC for computing (iceberg) concept
lattices. It is based on data mining techniques with
a level-wise approach. In fact, TITANIC can be used
for a more general problem: Computing arbitrary
closure systems when the closure operator comes along
with a so-called weight function. The use of weight
functions for computing closure systems has not been
discussed in the literature up to now. Applications
providing such a weight function include association
rule mining, functional dependencies in databases,
conceptual clustering, and ontology engineering. The
algorithm is experimentally evaluated and compared
with Ganter's Next-Closure algorithm. The evaluation
shows an important gain in efficiency, especially for
weakly correlated data.
http://portal.acm.org/citation.cfm?id=606457
10.1016/S0169-023X(02)00057-5
titanic, itegpub, icfca, l3s, fca, myown, citedBy:doerfel2012publication