Doerfel, S.; Jäschke, R. & Stumme, G.
(2012):
Publication Analysis of the Formal Concept Analysis Community.
In: ICFCA 2012,
Berlin/Heidelberg.
[Volltext]
[Kurzfassung] [BibTeX][Endnote]
We present an analysis of the publication and citation networks of all previous editions of the three conferences most relevant to the FCA community: ICFCA, ICCS and CLA. Using data mining methods from FCA and graph analysis, we investigate patterns and communities among authors, we identify and visualize influential publications and authors, and we give a statistical summary of the conferences’ history.
@inproceedings{doerfel2012publication,
author = {Doerfel, Stephan and Jäschke, Robert and Stumme, Gerd},
title = {Publication Analysis of the Formal Concept Analysis Community},
editor = {Domenach, F. and Ignatov, D.I. and Poelmans, J.},
booktitle = {ICFCA 2012},
series = {Lecture Notes in Artificial Intelligence},
publisher = {Springer},
address = {Berlin/Heidelberg},
year = {2012},
volume = {7278},
pages = {77--95},
url = {https://www.kde.cs.uni-kassel.de/pub/pdf/doerfel2012publication.pdf},
keywords = {2012, analysis, community, concept, fca, home, info20pub, itegpub, l3s, myown, scientometrics},
abstract = {We present an analysis of the publication and citation networks of all previous editions of the three conferences most relevant to the FCA community: ICFCA, ICCS and CLA. Using data mining methods from FCA and graph analysis, we investigate patterns and communities among authors, we identify and visualize influential publications and authors, and we give a statistical summary of the conferences’ history.
}
}
%0 = inproceedings
%A = Doerfel, Stephan and Jäschke, Robert and Stumme, Gerd
%B = ICFCA 2012
%C = Berlin/Heidelberg
%D = 2012
%I = Springer
%T = Publication Analysis of the Formal Concept Analysis Community
%U = https://www.kde.cs.uni-kassel.de/pub/pdf/doerfel2012publication.pdf
Jäschke, R.; Hotho, A.; Schmitz, C.; Ganter, B. & Stumme, G.
(2008):
Discovering Shared Conceptualizations in Folksonomies.
In: Journal of Web Semantics,
Ausgabe/Number: 1,
Vol. 6,
Erscheinungsjahr/Year: 2008.
Seiten/Pages: 38-53.
[Volltext] [BibTeX]
[Endnote]
@article{jaeschke08discovering,
author = {Jäschke, Robert and Hotho, Andreas and Schmitz, Christoph and Ganter, Bernhard and Stumme, Gerd},
title = {Discovering Shared Conceptualizations in Folksonomies},
journal = {Journal of Web Semantics},
year = {2008},
volume = {6},
number = {1},
pages = {38-53},
url = {http://dx.doi.org/10.1016/j.websem.2007.11.004},
keywords = {2008, FCA, OntologyHandbook, analysis, bibsonomy, concept, discovering, fca, folksonomies, formal, itegpub, l3s, myown, shared, triadic}
}
%0 = article
%A = Jäschke, Robert and Hotho, Andreas and Schmitz, Christoph and Ganter, Bernhard and Stumme, Gerd
%D = 2008
%T = Discovering Shared Conceptualizations in Folksonomies
%U = http://dx.doi.org/10.1016/j.websem.2007.11.004
Cimiano, P.; Hotho, A.; Stumme, G. & Tane, J.
(2004):
Conceptual Knowledge Processing with Formal Concept
Analysis and Ontologies.
In: Concept Lattices.
2961. Aufl./Vol..
Hrsg./Editors: Eklund, P.
Verlag/Publisher: Springer,
Berlin/Heidelberg.
Erscheinungsjahr/Year: 2004.
Seiten/Pages: 189-207.
[Volltext] [BibTeX]
[Endnote]
@incollection{cimiano2004conceptual,
author = {Cimiano, Philipp and Hotho, Andreas and Stumme, Gerd and Tane, Julien},
title = {Conceptual Knowledge Processing with Formal Concept
Analysis and Ontologies},
editor = {Eklund, Peter},
booktitle = {Concept Lattices},
series = {Lecture Notes in Computer Science},
publisher = {Springer},
address = {Berlin/Heidelberg},
year = {2004},
volume = {2961},
pages = {189--207},
url = {http://dx.doi.org/10.1007/978-3-540-24651-0_18},
isbn = {978-3-540-21043-6},
keywords = {2004, citedBy:doerfel2012publication, fca, icfca, itegpub, knowledge, l3s, myown, processing}
}
%0 = incollection
%A = Cimiano, Philipp and Hotho, Andreas and Stumme, Gerd and Tane, Julien
%B = Concept Lattices
%C = Berlin/Heidelberg
%D = 2004
%I = Springer
%T = Conceptual Knowledge Processing with Formal Concept
Analysis and Ontologies
%U = http://dx.doi.org/10.1007/978-3-540-24651-0_18
Stumme, G.
(2004):
Iceberg Query Lattices for Datalog.
In: Conceptual Structures at Work: 12th International Conference on Conceptual Structures (ICCS 2004),
Heidelberg.
[Volltext]
[BibTeX][Endnote]
@inproceedings{stumme2004iceberg,
author = {Stumme, Gerd},
title = {Iceberg Query Lattices for Datalog},
editor = {Wolff, Karl Erich and Pfeiffer, Heather D. and Delugach, Harry S.},
booktitle = {Conceptual Structures at Work: 12th International Conference on Conceptual Structures (ICCS 2004)},
series = {LNCS},
publisher = {Springer},
address = {Heidelberg},
year = {2004},
volume = {3127},
pages = {109-125},
url = {http://www.kde.cs.uni-kassel.de/stumme/papers/2004/stumme2004iceberg.pdf},
keywords = {2004, analysis, concept, context, datalog, families, family, fca, formal, iceberg, itegpub, l3s, lattices, myown, pcf, power, queries, query}
}
%0 = inproceedings
%A = Stumme, Gerd
%B = Conceptual Structures at Work: 12th International Conference on Conceptual Structures (ICCS 2004)
%C = Heidelberg
%D = 2004
%I = Springer
%T = Iceberg Query Lattices for Datalog
%U = http://www.kde.cs.uni-kassel.de/stumme/papers/2004/stumme2004iceberg.pdf
Stumme, G.; Taouil, R.; Bastide, Y.; Pasquier, N. & Lakhal, L.
(2002):
Computing iceberg concept lattices with TITANIC.
In: Data & Knowledge Engineering,
Ausgabe/Number: 2,
Vol. 42,
Verlag/Publisher: Elsevier Science Publishers B. V..
Erscheinungsjahr/Year: 2002.
Seiten/Pages: 189-222.
[Volltext] [Kurzfassung] [BibTeX]
[Endnote]
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.
@article{stumme2002computing,
author = {Stumme, Gerd and Taouil, Rafik and Bastide, Yves and Pasquier, Nicolas and Lakhal, Lotfi},
title = {Computing iceberg concept lattices with TITANIC},
journal = {Data & Knowledge Engineering},
publisher = {Elsevier Science Publishers B. V.},
address = {Amsterdam, The Netherlands, The Netherlands},
year = {2002},
volume = {42},
number = {2},
pages = {189--222},
url = {http://portal.acm.org/citation.cfm?id=606457},
doi = {10.1016/S0169-023X(02)00057-5},
issn = {0169-023X},
keywords = {citedBy:doerfel2012publication, fca, icfca, itegpub, l3s, myown, titanic},
abstract = {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.}
}
%0 = article
%A = Stumme, Gerd and Taouil, Rafik and Bastide, Yves and Pasquier, Nicolas and Lakhal, Lotfi
%C = Amsterdam, The Netherlands, The Netherlands
%D = 2002
%I = Elsevier Science Publishers B. V.
%T = Computing iceberg concept lattices with TITANIC
%U = http://portal.acm.org/citation.cfm?id=606457