A Multicriteria Clustering Approach Based on Similarity Indices and Clustering Ensemble Techniques

Baroudi Rouba () and Safia Nait Bahloul ()
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Baroudi Rouba: Department of Computer Science, Université de Mostaganem Abelhamid Ibn Badis, BP 188 Mostaganem, Algeria
Safia Nait Bahloul: Department of Computer Science, Université d'Oran Es-Sénia, BP 1524 El M'naouer, Oran, Algeria

International Journal of Information Technology & Decision Making (IJITDM), 2014, vol. 13, issue 04, 811-837

Abstract: This paper deals with the problem of multicriteria clusters construction. The aim is to propose a multicriteria clustering procedure aiming at discovering data structures from a multicriteria perspective by defining a dissimilarity measure which takes into account the multicriteria nature of the problem. Comparing two objects in the multicriteria context is based on the preference information that expresses whether these objects are indifferent, incomparable or one is preferred to the other. The proposed approach uses this preference information with an agreement–disagreement similarity index to compute a dissimilarity measure. The approach generates, according to the preference relations, a set of clusterings. Each clustering expresses a way of grouping objects according to the preference relation used. A good quality final clustering is obtained by combining the clusterings generated previously using a clustering ensemble technique.

Keywords: Clustering; multicriteria decision aid; preference information; similarity index; clustering ensemble (search for similar items in EconPapers)
Date: 2014
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Citations: View citations in EconPapers (6)

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DOI: 10.1142/S0219622014500631

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