Publication Analysis of the Formal Concept Analysis Community.
In: F. Domenach, D. Ignatov and J. Poelmans, editors,
ICFCA 2012, volume 7278, series Lecture Notes in Artificial Intelligence, pages 77-95.
Springer, Berlin/Heidelberg, 2012.
Stephan Doerfel, Robert Jäschke and Gerd Stumme.
[doi]
[abstract]
[BibTeX]
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.
Discovering Shared Conceptualizations in Folksonomies.
Journal of Web Semantics, 6(1):38-53, 2008.
Robert Jäschke, Andreas Hotho, Christoph Schmitz, Bernhard Ganter and Gerd Stumme.
[doi]
[BibTeX]
Conceptual Knowledge Processing with Formal Concept Analysis and Ontologies.
In:
P. Eklund, editor,
Concept Lattices, pages 189-207.
Springer, Berlin/Heidelberg, 2004.
Philipp Cimiano, Andreas Hotho, Gerd Stumme and Julien Tane.
[doi]
[BibTeX]
Iceberg Query Lattices for Datalog.
In: K. E. Wolff, H. D. Pfeiffer and H. S. Delugach, editors,
Conceptual Structures at Work: 12th International Conference on Conceptual Structures (ICCS 2004), volume 3127, series LNCS, pages 109-125.
Springer, Heidelberg, 2004.
Gerd Stumme.
[doi]
[BibTeX]
Computing iceberg concept lattices with TITANIC.
Data & Knowledge Engineering, 42(2):189-222, 2002.
Gerd Stumme, Rafik Taouil, Yves Bastide, Nicolas Pasquier and Lotfi Lakhal.
[doi]
[abstract]
[BibTeX]
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.