|
Lakhal, L. & Stumme, G.
(2005):
Efficient Mining of Association Rules Based on Formal Concept Analysis. LNAI Heidelberg
[Volltext] [Kurzfassung] [BibTeX]
[Endnote]
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.
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author = {Lakhal, Lotfi and Stumme, Gerd},
title = {Efficient Mining of Association Rules Based on Formal Concept Analysis},
editor = {Ganter, Bernhard and Stumme, Gerd and Wille, Rudolf},
booktitle = {Formal Concept Analysis: Foundations and Applications},
series = {LNAI},
publisher = {Springer},
address = {Heidelberg},
year = {2005},
volume = {3626},
pages = {180-195},
url = {http://www.kde.cs.uni-kassel.de/stumme/papers/2005/lakhal2005efficient.pdf},
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abstract = {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.}
}
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%B = Formal Concept Analysis: Foundations and Applications}
%C = Heidelberg
%D = 2005
%I = Springer
%T = Efficient Mining of Association Rules Based on Formal Concept Analysis}
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|
|
Lakhal, L. & Stumme, G.
(2005):
Efficient Mining of Association Rules Based on Formal Concept Analysis. LNAI Heidelberg
[Volltext] [Kurzfassung] [BibTeX]
[Endnote]
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.
@inbook{lakhal2005efficient,
author = {Lakhal, Lotfi and Stumme, Gerd},
title = {Efficient Mining of Association Rules Based on Formal Concept Analysis},
editor = {Ganter, Bernhard and Stumme, Gerd and Wille, Rudolf},
booktitle = {Formal Concept Analysis: Foundations and Applications},
series = {LNAI},
publisher = {Springer},
address = {Heidelberg},
year = {2005},
volume = {3626},
pages = {180-195},
url = {http://www.kde.cs.uni-kassel.de/stumme/papers/2005/lakhal2005efficient.pdf},
keywords = {2005, analysis, association, book, closed, concept, condensed, data, discovery, fca, formal, itegpub, itemsets, kdd, knowledge, l3s, mining, myown, representations, rules},
abstract = {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.}
}
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%C = Heidelberg
%D = 2005
%I = Springer
%T = Efficient Mining of Association Rules Based on Formal Concept Analysis}
%U = http://www.kde.cs.uni-kassel.de/stumme/papers/2005/lakhal2005efficient.pdf
|
| J |
Bastide, Y.; Taouil, R.; Pasquier, N.; Stumme, G. & Lakhal, L.
(2002):
Pascal: un alogorithme d'extraction des motifs fréquents.
In: Technique et Science Informatiques (TSI),
Ausgabe/Number: 1,
Vol. 21,
Erscheinungsjahr/Year: 2002.
Seiten/Pages: 65-95.
[Volltext] [BibTeX]
[Endnote]
@article{bastide02unalogorithme,
author = {Bastide, Y. and Taouil, R. and Pasquier, N. and Stumme, G. and Lakhal, L.},
title = {Pascal: un alogorithme d'extraction des motifs fréquents},
journal = {Technique et Science Informatiques (TSI)},
year = {2002},
volume = {21},
number = {1},
pages = {65-95},
url = {http://www.kde.cs.uni-kassel.de/stumme/papers/2001/TSI01.pdf},
keywords = {2002, analysis, association, closed, concept, condensed, fca, formal, iceberg, itemsets, lattices, myown, pascal, representations, rules, titanic}
}
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%A = Bastide, Y. and Taouil, R. and Pasquier, N. and Stumme, G. and Lakhal, L.
%D = 2002
%T = Pascal: un alogorithme d'extraction des motifs fréquents
%U = http://www.kde.cs.uni-kassel.de/stumme/papers/2001/TSI01.pdf
|
| J |
Stumme, G.; Taouil, R.; Bastide, Y.; Pasqier, N. & Lakhal, L.
(2002):
Computing Iceberg Concept Lattices with Titanic.
In: J. Data and KnowledgeEngineering (DKE),
Ausgabe/Number: 2,
Vol. 42,
Erscheinungsjahr/Year: 2002.
Seiten/Pages: 189-222.
[Volltext] [BibTeX]
[Endnote]
@article{stumme02computing,
author = {Stumme, G. and Taouil, R. and Bastide, Y. and Pasqier, N. and Lakhal, L.},
title = {Computing Iceberg Concept Lattices with Titanic},
journal = {J. Data and KnowledgeEngineering (DKE)},
year = {2002},
volume = {42},
number = {2},
pages = {189-222},
url = {http://www.kde.cs.uni-kassel.de/stumme/papers/2002/stumme2002computing.pdf},
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%D = 2002
%T = Computing Iceberg Concept Lattices with Titanic
%U = http://www.kde.cs.uni-kassel.de/stumme/papers/2002/stumme2002computing.pdf
|
| P |
Stumme, G.
(2002):
Efficient Data Mining Based on Formal Concept Analysis.
In: Database and Expert Systems Applications. Proc. DEXA 2002,
Heidelberg.
[Volltext]
[BibTeX][Endnote]
@inproceedings{stumme02efficient,
author = {Stumme, G.},
title = {Efficient Data Mining Based on Formal Concept Analysis},
editor = {Hameurlain, A. and Cicchetti, R. and Traunmüller, R.},
booktitle = {Database and Expert Systems Applications. Proc. DEXA 2002},
series = {LNCS},
publisher = {Springer},
address = {Heidelberg},
year = {2002},
volume = {2453},
pages = {534-546},
url = {http://www.kde.cs.uni-kassel.de/stumme/papers/2002/DEXA02.pdf},
keywords = {2002, association, closed, condensed, data, discovery, fca, itemsets, kdd, knowledge, mining, myown, representations, rules}
}
%0 = inproceedings
%A = Stumme, G.
%B = Database and Expert Systems Applications. Proc. DEXA 2002
%C = Heidelberg
%D = 2002
%I = Springer
%T = Efficient Data Mining Based on Formal Concept Analysis
%U = http://www.kde.cs.uni-kassel.de/stumme/papers/2002/DEXA02.pdf
|
| P |
Stumme, G.; Taouil, R.; Bastide, Y. & Lakhal, L.
(2001):
Conceptual Clustering with Iceberg Concept Lattices.
In: Proc. GI-Fachgruppentreffen Maschinelles Lernen (FGML'01),
Universität Dortmund 763.
[Volltext]
[BibTeX][Endnote]
@inproceedings{stumme01conceptualclustering,
author = {Stumme, G. and Taouil, R. and Bastide, Y. and Lakhal, L.},
title = {Conceptual Clustering with Iceberg Concept Lattices},
editor = {Klinkenberg, R. and Rüping, S. and Fick, A. and Henze, N. and Herzog, C. and Molitor, R. and Schröder, O.},
booktitle = {Proc. GI-Fachgruppentreffen Maschinelles Lernen (FGML'01)},
address = {Universität Dortmund 763},
year = {2001},
url = {http://www.kde.cs.uni-kassel.de/stumme/papers/2001/FGML01.pdf},
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}
%0 = inproceedings
%A = Stumme, G. and Taouil, R. and Bastide, Y. and Lakhal, L.
%B = Proc. GI-Fachgruppentreffen Maschinelles Lernen (FGML'01)
%C = Universität Dortmund 763
%D = 2001
%T = Conceptual Clustering with Iceberg Concept Lattices
%U = http://www.kde.cs.uni-kassel.de/stumme/papers/2001/FGML01.pdf
|
| P |
Stumme, G.; Taouil, R.; Bastide, Y. & Lakhal, L.
(2001):
Conceptual Clustering with Iceberg Concept Lattices.
In: Proc. GI-Fachgruppentreffen Maschinelles Lernen (FGML'01),
Universität Dortmund 763.
[Volltext]
[BibTeX][Endnote]
@inproceedings{stumme01conceptualclustering,
author = {Stumme, G. and Taouil, R. and Bastide, Y. and Lakhal, L.},
title = {Conceptual Clustering with Iceberg Concept Lattices},
editor = {Klinkenberg, R. and Rüping, S. and Fick, A. and Henze, N. and Herzog, C. and Molitor, R. and Schröder, O.},
booktitle = {Proc. GI-Fachgruppentreffen Maschinelles Lernen (FGML'01)},
address = {Universität Dortmund 763},
year = {2001},
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%0 = inproceedings
%A = Stumme, G. and Taouil, R. and Bastide, Y. and Lakhal, L.
%B = Proc. GI-Fachgruppentreffen Maschinelles Lernen (FGML'01)
%C = Universität Dortmund 763
%D = 2001
%T = Conceptual Clustering with Iceberg Concept Lattices
%U = http://www.kde.cs.uni-kassel.de/stumme/papers/2001/FGML01.pdf
|
| P |
Stumme, G.; Taouil, R.; Bastide, Y.; Pasquier, N. & Lakhal, L.
(2001):
Intelligent Structuring and Reducing of Association Rules and with Formal Concept Analysis.
In: KI 2001: Advances in Artificial Intelligence. KI 2001,
Heidelberg.
[Volltext]
[BibTeX][Endnote]
@inproceedings{stumme01intelligent,
author = {Stumme, G. and Taouil, R. and Bastide, Y. and Pasquier, N. and Lakhal, L.},
title = {Intelligent Structuring and Reducing of Association Rules and with Formal Concept Analysis},
editor = {Baader, F. and Brewker, G. and Eiter, T.},
booktitle = {KI 2001: Advances in Artificial Intelligence. KI 2001},
series = {LNAI},
publisher = {Springer},
address = {Heidelberg},
year = {2001},
volume = {2174},
pages = {335-350},
url = {http://www.kde.cs.uni-kassel.de/stumme/papers/2001/KI01.pdf},
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}
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%B = KI 2001: Advances in Artificial Intelligence. KI 2001
%C = Heidelberg
%D = 2001
%I = Springer
%T = Intelligent Structuring and Reducing of Association Rules and with Formal Concept Analysis
%U = http://www.kde.cs.uni-kassel.de/stumme/papers/2001/KI01.pdf
|
| P |
Bastide, Y.; Taouil, R.; Pasquier, N.; Stumme, G. & Lakhal, L.
(2000):
Levelwise Search of Frequent Patterns.
In: Actes des 16ièmes Journées Bases de Données Avancées,
France.
[Volltext]
[BibTeX][Endnote]
@inproceedings{bastide00levelwise,
author = {Bastide, Y. and Taouil, R. and Pasquier, N. and Stumme, G. and Lakhal, L.},
title = {Levelwise Search of Frequent Patterns},
booktitle = {Actes des 16ièmes Journées Bases de Données Avancées},
publisher = {Blois},
address = {France},
year = {2000},
pages = {307-322},
url = {http://www.kde.cs.uni-kassel.de/stumme/papers/2000/BDA00.pdf},
keywords = {2000, algorithm, algorithms, analysis, association, closed, concept, condensed, data, discovery, fca, formal, frequent, itemsets, kdd, knowledge, mining, myown, representations, rules}
}
%0 = inproceedings
%A = Bastide, Y. and Taouil, R. and Pasquier, N. and Stumme, G. and Lakhal, L.
%B = Actes des 16ièmes Journées Bases de Données Avancées
%C = France
%D = 2000
%I = Blois
%T = Levelwise Search of Frequent Patterns
%U = http://www.kde.cs.uni-kassel.de/stumme/papers/2000/BDA00.pdf
|
| J |
Bastide, Y.; Taouil, R.; Pasquier, N.; Stumme, G. & Lakhal, L.
(2000):
Mining Frequent Patterns with Counting Inference..
In: SIGKDD Explorations, Special Issue on Scalable Algorithms,
Ausgabe/Number: 2,
Vol. 2,
Erscheinungsjahr/Year: 2000.
Seiten/Pages: 71-80.
[BibTeX]
[Endnote]
@article{bastide00miningfrequent,
author = {Bastide, Y. and Taouil, R. and Pasquier, N. and Stumme, G. and Lakhal, L.},
title = {Mining Frequent Patterns with Counting Inference.},
journal = {SIGKDD Explorations, Special Issue on Scalable Algorithms},
year = {2000},
volume = {2},
number = {2},
pages = {71-80},
keywords = {2000, FCA, OntologyHandbook, analys, association, closed, concept, condensed, data, discovery, fca, formal, frequent, itemsets, kdd, knowledge, mining, myown, representation, representations, rule, rules}
}
%0 = article
%A = Bastide, Y. and Taouil, R. and Pasquier, N. and Stumme, G. and Lakhal, L.
%D = 2000
%T = Mining Frequent Patterns with Counting Inference.
|
| P |
Bastide, Y.; Pasquier, N.; Taouil, R.; Stumme, G. & Lakhal, L.
(2000):
Mining Minimal Non-Redundant Association Rules Using Frequent Closed Itemsets.
In: Computational Logic -- CL 2000 Proc. CL'00,
Heidelberg.
[Volltext]
[BibTeX][Endnote]
@inproceedings{bastide00miningminimal,
author = {Bastide, Y. and Pasquier, N. and Taouil, R. and Stumme, G. and Lakhal, L.},
title = {Mining Minimal Non-Redundant Association Rules Using Frequent Closed Itemsets},
editor = {Lloyd, J. and Dahl, V. and Furbach, U. and Kerber, M. and Laus, K.-K. and Palamidessi, C. and Pereira, L.M. and Sagiv, Y. and Stuckey, P.J.},
booktitle = {Computational Logic --- CL 2000 Proc. CL'00},
series = {LNAI},
publisher = {Springer},
address = {Heidelberg},
year = {2000},
volume = {1861},
url = {http://www.kde.cs.uni-kassel.de/stumme/papers/2000/DOOD00.pdf},
keywords = {2000, analys, association, closed, concept, condensed, data, discovery, fca, formal, frequent, itemsets, kdd, knowledge, mining, myown, representation, representations, rule, rules}
}
%0 = inproceedings
%A = Bastide, Y. and Pasquier, N. and Taouil, R. and Stumme, G. and Lakhal, L.
%B = Computational Logic --- CL 2000 Proc. CL'00
%C = Heidelberg
%D = 2000
%I = Springer
%T = Mining Minimal Non-Redundant Association Rules Using Frequent Closed Itemsets
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|
| P |
Boulicaut, J.-F.; Bykowski, A. & Rigotti, C.
(2000):
Approximation of Frequency Queris by Means of Free-Sets.
In: Principles of Data Mining and Knowledge Discovery,
[Volltext]
[BibTeX][Endnote]
@inproceedings{boulicaut00approximation,
author = {Boulicaut, Jean-Francois and Bykowski, Artur and Rigotti, Christophe},
title = {Approximation of Frequency Queris by Means of Free-Sets},
booktitle = {Principles of Data Mining and Knowledge Discovery},
year = {2000},
pages = {75-85},
url = {citeseer.ist.psu.edu/boulicaut00approximation.html},
keywords = {Analysis, Concept, Formal, closed, dm, fca, free, itemset, itemsets, kdd, mining, sets}
}
%0 = inproceedings
%A = Boulicaut, Jean-Francois and Bykowski, Artur and Rigotti, Christophe
%B = Principles of Data Mining and Knowledge Discovery
%D = 2000
%T = Approximation of Frequency Queris by Means of Free-Sets
%U = citeseer.ist.psu.edu/boulicaut00approximation.html
|
| P |
Stumme, G.; Taouil, R.; Bastide, Y.; Pasquier, N. & Lakhal, L.
(2000):
Fast Computation of Concept Lattices Using Data Mining Techniques.
In: Proc. 7th Intl. Workshop on Knowledge Representation Meets Databases,
[Volltext]
[BibTeX][Endnote]
@inproceedings{stumme00fast,
author = {Stumme, G. and Taouil, R. and Bastide, Y. and Pasquier, N. and Lakhal, L.},
title = {Fast Computation of Concept Lattices Using Data Mining Techniques},
editor = {Bouzeghoub, M. and Klusch, M. and Nutt, W. and Sattler, U.},
booktitle = {Proc. 7th Intl. Workshop on Knowledge Representation Meets Databases},
year = {2000},
note = {http://ceur-ws.org/Vol-29. Part of testumme02computing},
url = {http://www.kde.cs.uni-kassel.de/stumme/papers/2000/KRDB00.pdf},
keywords = {2000, algorithm, algorithms, analysis, closed, computation, concept, condensed, fca, formal, iceberg, itemsets, lattices, myown, representations}
}
%0 = inproceedings
%A = Stumme, G. and Taouil, R. and Bastide, Y. and Pasquier, N. and Lakhal, L.
%B = Proc. 7th Intl. Workshop on Knowledge Representation Meets Databases
%D = 2000
%T = Fast Computation of Concept Lattices Using Data Mining Techniques
%U = http://www.kde.cs.uni-kassel.de/stumme/papers/2000/KRDB00.pdf
|
|
Stumme, G.
(1999):
Conceptual Knowledge Discovery with Frequent Concept Lattices.
[Volltext] [BibTeX]
[Endnote]
@techreport{stumme99conceptualknowledge,
author = {Stumme, G.},
title = {Conceptual Knowledge Discovery with Frequent Concept Lattices},
type = {FB4-Preprint 2043},
year = {1999},
url = {http://www.kde.cs.uni-kassel.de/stumme/papers/1999/P2043.pdf},
keywords = {1999, analysis, association, closed, concept, condensed, data, discovery, fca, formal, frequent, iceberg, itemsets, kdd, knowledge, lattices, mining, myown, representations, rule, rules}
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|