A parallel between extended formal concept analysis and bipartite graphs analysis

Gaume, B; Navarro, E; Prade, H

A parallel between extended formal concept analysis and bipartite graphs analysis

Gaume, B Navarro, E Prade, H

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Publication Type:: Conference Proceeding
Citation:: Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 2010, 6178 LNAI pp. 270 - 280
Issue Date:: 2010-01-01

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Field	Value	Language
dc.contributor.author	Gaume, B	en_US
dc.contributor.author	Navarro, E	en_US
dc.contributor.author	Prade, H https://orcid.org/0000-0003-4586-8527	en_US
dc.date.issued	2010-01-01	en_US
dc.identifier.citation	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 2010, 6178 LNAI pp. 270 - 280	en_US
dc.identifier.isbn	3642140483	en_US
dc.identifier.isbn	9783642140488	en_US
dc.identifier.issn	0302-9743	en_US
dc.identifier.uri	http://hdl.handle.net/10453/32822
dc.description.abstract	The paper 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 a "conceptual world" (defined through a Galois connection associated of the new operators) is a disconnected sub-graph 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 suggests new ideas for providing simplified views of datasets. © 2010 Springer-Verlag Berlin Heidelberg.	en_US
dc.relation.ispartof	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)	en_US
dc.relation.isbasedon	10.1007/978-3-642-14049-5_28	en_US
dc.subject.classification	Artificial Intelligence & Image Processing	en_US
dc.title	A parallel between extended formal concept analysis and bipartite graphs analysis	en_US
dc.type	Conference Proceeding
utslib.citation.volume	6178 LNAI	en_US
utslib.for	0801 Artificial Intelligence and Image Processing	en_US
pubs.embargo.period	Not known	en_US
pubs.organisational-group	/University of Technology Sydney
pubs.organisational-group	/University of Technology Sydney/Faculty of Engineering and Information Technology
pubs.organisational-group	/University of Technology Sydney/Faculty of Engineering and Information Technology/School of Software
pubs.organisational-group	/University of Technology Sydney/Strength - CAI - Centre for Artificial Intelligence
utslib.copyright.status	closed_access
pubs.publication-status	Published	en_US
pubs.volume	6178 LNAI	en_US

Abstract:

The paper 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 a "conceptual world" (defined through a Galois connection associated of the new operators) is a disconnected sub-graph 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 suggests new ideas for providing simplified views of datasets. © 2010 Springer-Verlag Berlin Heidelberg.

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http://hdl.handle.net/10453/32822