Knowledge discovery in high-dimensional data: Case studies and a user survey for the rank-by-feature framework

IEEE Transactions on Visualization and Computer Graphics

Volumn 12, Issue 3, 2006, Pages 311-322

  Seo, Jinwook ^a,b,d   Shneiderman, Ben ^a,c,e,f,g  

^a IEEE   (United States)

^b CHILDREN S RESEARCH INSTITUTE   (United States)

^c Children's Research Institute ^*  (United States)

^d ACM   (United States)

^e ACM ^*  (United States)

^f UNIVERSITY OF MARYLAND   (United States)

^g UNIVERSITY OF MARYLAND   (United States)

Author keywords

Case study; Hierarchical clustering explorer; Information visualization evaluation; Rank by feature framework; User survey

Indexed keywords

CASE STUDY; HIERARCHICAL CLUSTERING EXPLORER; INFORMATION VISUALIZATION EVALUATION; RANK-BY-FEATURE FRAMEWORK; USER SURVEY;

DATA ACQUISITION; FEATURE EXTRACTION; HIERARCHICAL SYSTEMS; INTERACTIVE COMPUTER GRAPHICS;

KNOWLEDGE ACQUISITION;

ALGORITHM; ARTICLE; ARTIFICIAL INTELLIGENCE; CLUSTER ANALYSIS; COMPUTER GRAPHICS; COMPUTER INTERFACE; COMPUTER SIMULATION; DNA MICROARRAY; METHODOLOGY; THEORETICAL MODEL; THREE DIMENSIONAL IMAGING;

ALGORITHMS; ARTIFICIAL INTELLIGENCE; CLUSTER ANALYSIS; COMPUTER GRAPHICS; COMPUTER SIMULATION; IMAGING, THREE-DIMENSIONAL; MODELS, THEORETICAL; OLIGONUCLEOTIDE ARRAY SEQUENCE ANALYSIS; USER-COMPUTER INTERFACE;

EID: 33645150800     PISSN: 10772626     EISSN: None     Source Type: Journal    
DOI: 10.1109/TVCG.2006.50     Document Type: Article

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