Doerfel, S.; Jäschke, R. & Stumme, G.: Publication Analysis of the Formal Concept Analysis Community. In: Domenach, F.; Ignatov, D. & Poelmans, J. (Hrsg.):
ICFCA 2012. Berlin/Heidelberg: Springer, 2012 (Lecture Notes in Artificial Intelligence 7278), S. 77-95
[Volltext] [Kurzfassung]
[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.
Jäschke, R.; Hotho, A.; Schmitz, C.; Ganter, B. & Stumme, G.: Discovering Shared Conceptualizations in Folksonomies. In:
Journal of Web Semantics 6 (2008), Nr. 1, S. 38-53
[Volltext]
[BibTeX]
Cattuto, C.; Schmitz, C.; Baldassarri, A.; Servedio, V. D. P.; Loreto, V.; Hotho, A.; Grahl, M. & Stumme, G.: Network Properties of Folksonomies. In:
AI Communications Journal, Special Issue on ``Network Analysis in Natural Sciences and Engineering'' 20 (2007), Nr. 4, S. 245-262
[Volltext]
[BibTeX]
Schmitz, C.; Grahl, M.; Hotho, A.; Stumme, G.; Catutto, C.; Baldassarri, A.; Loreto, V. & Servedio, V. D. P.: Network Properties of Folksonomies.
Proc. WWW2007 Workshop ``Tagging and Metadata for Social Information Organization''. Banff: 2007
[Volltext]
[BibTeX]
Hotho, A.; Jäschke, R.; Schmitz, C. & Stumme, G.: Information Retrieval in Folksonomies: Search and Ranking. In: Sure, Y. & Domingue, J. (Hrsg.):
The Semantic Web: Research and Applications. Heidelberg: Springer, 2006 (LNAI 4011), S. 411-426
[BibTeX]
Jäschke, R.; Hotho, A.; Schmitz, C.; Ganter, B. & Stumme, G.: TRIAS - An Algorithm for Mining Iceberg Tri-Lattices.
Proceedings of the 6th IEEE International Conference on Data Mining (ICDM 06). Hong Kong: IEEE Computer Society, 2006, S. 907-911
[Volltext]
[BibTeX]
Schmitz, C.; Hotho, A.; Jäschke, R. & Stumme, G.: Mining Association Rules in Folksonomies. In: Batagelj, V.; Bock, H.-H.; Ferligoj, A. & vZiberna, A. (Hrsg.):
Data Science and Classification: Proc. of the 10th IFCS Conf.. Berlin, Heidelberg: Springer, 2006Studies in Classification, Data Analysis, and Knowledge Organization , S. 261-270
[BibTeX]
Formal Concept Analysis - Foundations and Applications. LNAI Heidelberg, 2005
[BibTeX]
Lakhal, L. & Stumme, G.:
Efficient Mining of Association Rules Based on Formal Concept Analysis. LNAI Heidelberg, 2005
[Volltext] [Kurzfassung]
[BibTeX]
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.
Pasquier, N.; Taouil, R.; Bastide, Y.; Stumme, G. & Lakhal, L.: Generating a Condensed Representation for Association Rules. In:
Journal Intelligent Information Systems (JIIS) 24 (2005), Nr. 1, S. 29-60
[Volltext]
[BibTeX]
Stumme, G.: A Finite State Model for On-Line Analytical Processing in
Triadic Contexts. In: Ganter, B. & Godin, R. (Hrsg.):
Proc. 3rd Intl. Conf. on Formal Concept Analysis. Heidelberg: Springer, 2005 (Lecture Notes in Computer Science 3403), S. 315-328
[Volltext]
[BibTeX]
Stumme, G.: A Finite State Model for On-Line Analytical Processing in Triadic
Contexts.. In: Ganter, B. & Godin, R. (Hrsg.):
Proc. 3rd Intl. Conf. on Formal Concept Analysis. Springer, 2005 (LNCS 3403), S. 315-328
[BibTeX]
Stumme, G.: Conceptual Knowledge Processing (Invited Talk). In: Collard, M. & Cavarero, J.-L. (Hrsg.):
Ontologies-based techniques for DataBases and Information Systems. Trondheim: 2005, S. 5
[Volltext]
[BibTeX]
Cimiano, P.; Hotho, A.; Stumme, G. & Tane, J.: Conceptual Knowledge Processing with Formal Concept Analysis and Ontologies. In: Eklund, P. (Hrsg.):
Concept Lattices. Berlin/Heidelberg: Springer, 2004 (Lecture Notes in Computer Science 2961), S. 189-207
[Volltext]
[BibTeX]
Cimiano, P.; Hotho, A.; Stumme, G. & Tane, J.: Conceptual Knowledge Processing with Formal Concept Analysis and Ontologies. In: Eklund, P. (Hrsg.):
Concept Lattices. Heidelberg: Springer, 2004 (LNAI 2961), S. 189-207
[Volltext] [Kurzfassung]
[BibTeX]
Among many other knowledge representations formalisms, Ontologies
and Formal Concept Analysis (FCA) aim at modeling 'concepts'. We
discuss how these two formalisms may complement another from an
application point of view. In particular, we will see how FCA can
be used to support Ontology Engineering, and how ontologies can be
exploited in FCA applications. The interplay of FCA and ontologies
is studied along the life cycle of an ontology:
(i) FCA can support the building of the ontology as a
learning technique.
(ii) The established ontology can be analyzed and navigated by
using techniques of FCA.
(iii) Last but not least, the ontology may be used to improve an FCA
application.
Stumme, G.: Iceberg Query Lattices for Datalog. In: Wolff, K. E.; Pfeiffer, H. D. & Delugach, H. S. (Hrsg.):
Conceptual Structures at Work: 12th International Conference on Conceptual Structures (ICCS 2004). Heidelberg: Springer, 2004 (LNCS 3127), S. 109-125
[Volltext]
[BibTeX]
Tane, J.; Schmitz, C. & Stumme, G.: Semantic resource management for the web: an e-learning application.
Proc. 13th International World Wide Web Conference (WWW 2004). 2004, S. 1-10
[Volltext]
[BibTeX]
Stumme, G.; Taouil, R.; Bastide, Y.; Pasquier, N. & Lakhal, L.: Computing iceberg concept lattices with TITANIC. In:
Data & Knowledge Engineering 42 (2002), Nr. 2, S. 189-222
[Volltext]
[Kurzfassung]
[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.