A new clustering algorithm based on regions of influence with self-detection of the best number of clusters

Proceedings - IEEE International Conference on Data Mining, ICDM

Volumn , Issue , 2009, Pages 884-889

  Muhlenbach, Fabrice ^a   Lallich, Stéphane ^b  

^a UNIVERSITÉ JEAN MONNET   (France)

^b UNIVERSITÉ DE LYON   (France)

Author keywords

Clustering; Neighborhood graph

Indexed keywords

BENCHMARKING; CLUSTER ANALYSIS; DATA MINING; GRAPHIC METHODS;

CLUSTERING; CLUSTERING METHODS; GRAPH-BASED CLUSTERING; HIERARCHICAL CLUSTERING METHODS; NEIGHBORHOOD GRAPHS; NEW CLUSTERING ALGORITHMS; NUMBER OF CLUSTERS; QUALITY INDICES;

CLUSTERING ALGORITHMS;

EID: 77951181778     PISSN: 15504786     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/ICDM.2009.133     Document Type: Conference Paper

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