International Journal of Computational Intelligence Systems

Volume 6, Issue 6, November 2013, Pages 1125 - 1142

Clustering bipartite graphs in terms of approximate formal concepts and sub-contexts

Authors
Bruno Gaume, Emmanuel Navarro, Henri Prade
Corresponding Author
Bruno Gaume
Received 11 April 2011, Accepted 22 November 2011, Available Online 1 November 2013.
DOI
10.1080/18756891.2013.819179How to use a DOI?
Keywords
formal concept analysis (FCA), bipartite graph, small world, clustering, possibility theory
Abstract

The paper first offers a parallel between two approaches to conceptual clustering, namely formal concept analysis (augmented with the introduction of new operators) and bipartite graph analysis. It is shown that a formal concept (as defined in formal concept analysis) corresponds to the idea of a maximal bi-clique, while sub-contexts, which correspond to independent “conceptual worlds” that can be characterized by means of the new operators introduced, are disconnected sub-graphs in a bipartite graph. The parallel between formal concept analysis and bipartite graph analysis is further exploited by considering “approximation” methods on both sides. It leads to suggest new ideas for providing simplified views of datasets, taking also inspiration from the search for approximate itemsets in data mining (with relaxed requirements), and the detection of communities in hierarchical small worlds.

Copyright
© 2017, the Authors. Published by Atlantis Press.
Open Access
This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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Journal
International Journal of Computational Intelligence Systems
Volume-Issue
6 - 6
Pages
1125 - 1142
Publication Date
2013/11/01
ISSN (Online)
1875-6883
ISSN (Print)
1875-6891
DOI
10.1080/18756891.2013.819179How to use a DOI?
Copyright
© 2017, the Authors. Published by Atlantis Press.
Open Access
This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

Cite this article

TY  - JOUR
AU  - Bruno Gaume
AU  - Emmanuel Navarro
AU  - Henri Prade
PY  - 2013
DA  - 2013/11/01
TI  - Clustering bipartite graphs in terms of approximate formal concepts and sub-contexts
JO  - International Journal of Computational Intelligence Systems
SP  - 1125
EP  - 1142
VL  - 6
IS  - 6
SN  - 1875-6883
UR  - https://doi.org/10.1080/18756891.2013.819179
DO  - 10.1080/18756891.2013.819179
ID  - Gaume2013
ER  -