A novel attribute weighting algorithm for clustering high-dimensional categorical data

Pattern Recognition

Volumn 44, Issue 12, 2011, Pages 2843-2861

  Bai, Liang ^a,b   Liang, Jiye ^a   Dang, Chuangyin ^b   Cao, Fuyuan ^a  

^a SHANXI UNIVERSITY   (China)

^b CITY UNIVERSITY OF HONG KONG   (Hong Kong)

Author keywords

Attribute weighting; Cluster analysis; High dimensional categorical data; Optimization algorithm; Subspace clustering

Indexed keywords

ATTRIBUTE WEIGHTING; CATEGORICAL DATA; DATA SPARSENESS; EXPERIMENTAL STUDIES; HIGH DIMENSIONAL DATA; HIGH-DIMENSIONAL; K-MODES; LARGE DATASETS; LINEAR TIME COMPLEXITY; NUMBER OF DATUM; OPTIMIZATION ALGORITHM; OPTIMIZATION ALGORITHMS; OPTIMIZATION FRAMEWORK; SUBSPACE CLUSTERING; SYNTHETIC AND REAL DATA; WEIGHT VALUES; WEIGHTING TECHNIQUES;

CLUSTER ANALYSIS; CONVERGENCE OF NUMERICAL METHODS; OPTIMIZATION;

CLUSTERING ALGORITHMS;

EID: 79959359175     PISSN: 00313203     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.patcog.2011.04.024     Document Type: Article

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