TY - JOUR
AU - Pasquier, Nicolas
AU - Taouil, Rafik
AU - Bastide, Yves
AU - Stumme, Gerd
AU - Lakhal, Lotfi
T1 - Generating a Condensed Representation for Association Rules
JO - Journal Intelligent Information Systems (JIIS)
PY - 2005/
VL - 24
IS - 1
SP - 29
EP - 60
UR - http://www.kde.cs.uni-kassel.de/stumme/papers/2005/pasquier2005generating.pdf
DO -
KW - concept
KW - discovery
KW - 2005
KW - association
KW - OntologyHandbook
KW - l3s
KW - analysis
KW - kdd
KW - itemset
KW - myown
KW - rule
KW - data
KW - knowledge
KW - closed
KW - formal
KW - rules
KW - itegpub
KW - condensed
KW - fca
KW - sets
KW - representations
KW - mining
L1 -
SN -
N1 - alpha
N1 -
AB -
ER -
TY - JOUR
AU - Pasquier, Nicolas
AU - Taouil, Rafik
AU - Bastide, Yves
AU - Stumme, Gerd
AU - Lakhal, Lotfi
T1 - Generating a Condensed Representation for Association Rules
JO - Journal Intelligent Information Systems (JIIS)
PY - 2005/
VL - 24
IS - 1
SP - 29
EP - 60
UR - http://www.kde.cs.uni-kassel.de/stumme/papers/2005/pasquier2005generating.pdf
DO -
KW - concept
KW - discovery
KW - 2005
KW - association
KW - OntologyHandbook
KW - l3s
KW - analysis
KW - kdd
KW - itemset
KW - myown
KW - rule
KW - data
KW - knowledge
KW - closed
KW - formal
KW - rules
KW - itegpub
KW - condensed
KW - fca
KW - sets
KW - representations
KW - mining
L1 -
SN -
N1 - Publications of Gerd Stumme
N1 -
AB -
ER -
TY - JOUR
AU - Stumme, Gerd
AU - Taouil, Rafik
AU - Bastide, Yves
AU - Pasquier, Nicolas
AU - Lakhal, Lotfi
T1 - Computing iceberg concept lattices with TITANIC
JO - Data & Knowledge Engineering
PY - 2002/08
VL - 42
IS - 2
SP - 189
EP - 222
UR - http://portal.acm.org/citation.cfm?id=606457
DO - 10.1016/S0169-023X(02)00057-5
KW - titanic
KW - concept
KW - iceberg
KW - fca
KW - kdd
KW - computing
L1 -
SN -
N1 -
N1 -
AB - 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.
ER -
TY - JOUR
AU - Stumme, Gerd
AU - Taouil, Rafik
AU - Bastide, Yves
AU - Pasquier, Nicolas
AU - Lakhal, Lotfi
T1 - Computing iceberg concept lattices with TITANIC
JO - Data & Knowledge Engineering
PY - 2002/08
VL - 42
IS - 2
SP - 189
EP - 222
UR - http://portal.acm.org/citation.cfm?id=606457
DO - 10.1016/S0169-023X(02)00057-5
KW - lattice
KW - titanic
KW - concept
KW - formal
KW - iceberg
KW - analysis
KW - fca
L1 -
SN -
N1 -
N1 -
AB - 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.
ER -
TY - CONF
AU - Pasquier, Nicolas
AU - Bastide, Yves
AU - Taouil, Rafik
AU - Lakhal, Lotfi
A2 - Bouzeghoub, Mokrane
T1 - Pruning closed itemset lattices for associations rules.
T2 - Bases de Donn�es Avanc�es
PB -
C1 -
PY - 1998/
CY -
VL -
IS -
SP -
EP -
UR - http://dblp.uni-trier.de/db/conf/bda/bda98.html#PasquierBTL98
DO -
KW - rules
KW - closed
KW - concept
KW - formal
KW - association
KW - OntologyHandbook
KW - FCA
KW - analysis
KW - fca
KW - itemset
KW - mining
L1 -
SN -
N1 -
N1 -
AB -
ER -
TY - CONF
AU - Pasquier, Nicolas
AU - Bastide, Yves
AU - Taouil, Rafik
AU - Lakhal, Lotfi
A2 - Bouzeghoub, Mokrane
T1 - Pruning closed itemset lattices for associations rules.
T2 - Bases de Données Avancées
PB -
C1 -
PY - 1998/
CY -
VL -
IS -
SP -
EP -
UR - http://dblp.uni-trier.de/db/conf/bda/bda98.html#PasquierBTL98
DO -
KW - rules
KW - closed
KW - concept
KW - formal
KW - association
KW - analysis
KW - fca
KW - itemset
KW - mining
L1 -
SN -
N1 -
N1 -
AB -
ER -