Reference : A Clustering Approach using Weighted Similarity Majority Margins |
Scientific congresses, symposiums and conference proceedings : Paper published in a book | |||
Engineering, computing & technology : Computer science | |||
http://hdl.handle.net/10993/285 | |||
A Clustering Approach using Weighted Similarity Majority Margins | |
English | |
Bisdorff, Raymond ![]() | |
Meyer, Patrick [Télécom Bretagne, France] | |
Olteanu, Alexandru ![]() | |
2011 | |
Advanced Data Mining and Applications ADMA, Beijing spring 2013 | |
Springer-Verlag | |
LNAI 7120 | |
15-28 | |
Yes | |
No | |
International | |
978-3-642-25853-4 | |
ADMA 2011 | |
17-19 December 2011 | |
Beijing | |
China | |
[en] Multiple Criteria Clustering ; Bipolar-valued Similarity ; Meta-heuristic Algorithm | |
[en] We propose a meta-heuristic for clustering objects that are described on multiple incommensurable attributes of nominal, ordinal and/or cardinal type. Our approach makes use of an innovative bipolar-valued dual similarity-dissimilarity relation characterized by pairwise weighted majority margins of similar minus dissimilar attribute evaluations. The clustering is computed in two steps. First, an evolutionary algorithm searches for a suitable subset of maximal similarity cliques that will best serve as cluster cores. In a second step, we construct with a greedy heuristic, around these initial cluster cores, a corresponding final partition which best fits the given bipolar-valued similarity relation. | |
http://hdl.handle.net/10993/285 | |
10.1007/978-3-642-25853-4_2 | |
LNAI 7120
Part I Advanced Data Mining and Applications ADMA 201 J. Tang et al. (Eds) |
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