Minimization of the Disagreements in Clustering Aggregation

Bahloul, Safia Nait; Rouba, Baroudi; Amghar, Youssef

doi:10.1007/978-3-540-85930-7_66

Cited by 3 publications

(2 citation statements)

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“…This problem has been studied by many researchers in data mining and many contributions have been developed to¯nd MCDA Clustering Approach Based on Clustering Ensemble 819 consensus clustering such as: hyper graph partitioning, 7 voting approach, [38][39][40][41][42][43][44][45][46][47][48][49] quadratic mutual information algorithm 5 and distance-based methods. 38 Optimization techniques have been also explored to solve the problem of clustering ensemble; Hornik and B€ ohm.…”

Section: Related Work In Clustering Ensemblementioning

confidence: 99%

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

Rouba

Bahloul

2014

Int. J. Info. Tech. Dec. Mak.

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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 de¯ning 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 indi®erent, 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¯nal clustering is obtained by combining the clusterings generated previously using a clustering ensemble technique.

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Section: Related Work In Clustering Ensemblementioning

confidence: 99%

“…This work has been extended to de¯ne relations between the clusters. [40][41][42][43][44][45][46][47][48][49][50] The problem of de¯ning relations between clusters has been also tackled in Ref. 34 where a formalization of the problem has been proposed using the preference relations.…”

Section: Introductionmentioning

confidence: 99%