DB-CSC: A density-based approach for subspace clustering in graphs with feature vectors

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

Volumn 6911 LNAI, Issue PART 1, 2011, Pages 565-580

  Günnemann, Stephan ^a   Boden, Brigitte ^a   Seidl, Thomas ^a  

^a RWTH AACHEN UNIVERSITY   (Germany)

Author keywords

[No Author keywords available]

Indexed keywords

ARBITRARY SHAPE; ATTRIBUTE INFORMATION; ATTRIBUTE SIMILARITY; CLUSTER MODELS; CLUSTERING APPROACH; DATA SOURCE; DENSITY-BASED; DENSITY-BASED APPROACHES; FEATURE VECTORS; GRAPH DENSITY; KNOWLEDGE EXTRACTION; MINING TECHNIQUES; NETWORK INFORMATION; SUBGRAPH MINING; SUBSPACE CLUSTERING; SUB-SPACE CLUSTERING;

LEARNING SYSTEMS; VECTORS; DATA MINING; MACHINE LEARNING;

CLUSTERING ALGORITHMS;

EID: 80052417297     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: 10.1007/978-3-642-23780-5_46     Document Type: Conference Paper

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