One optimized choosing method of K-means document clustering center

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

Volumn 4993 LNCS, Issue , 2008, Pages 490-495

  Suo, Hongguang ^a   Nie, Kunming ^a   Sun, Xin ^a   Wang, Yuwei ^a  

^a CHINA UNIVERSITY OF PETROLEUM   (China)

Author keywords

Document clustering; Initial center; K means; Sub graph division

Indexed keywords

ATMOSPHERIC RADIATION; CLUSTER ANALYSIS; COMPUTER NETWORKS; FLOW OF SOLIDS; GRAPH THEORY; INFORMATION ANALYSIS; INFORMATION RETRIEVAL; INFORMATION SCIENCE; INFORMATION SERVICES; INFORMATION TECHNOLOGY; INFRARED DEVICES; INFRARED INSTRUMENTS; NUMERICAL METHODS; REAL TIME CONTROL; SEARCH ENGINES; SOUNDING APPARATUS; TECHNOLOGY;

(E ,3E) PROCESS; ALLOWABLE RANGE; CLUSTERING CENTERS; DOCUMENT CLUSTERING; EXPERIMENT RESULTS; F MEASURE; HEIDELBERG (CO); INFORMATION RETRIEVAL TECHNOLOGY; K MEANS; NOISE DATA; RETRIEVAL (MIR); SIMILARITY MATRIX; SPRINGER (CO);

NUMBER THEORY;

EID: 45449108799     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: 10.1007/978-3-540-68636-1_53     Document Type: Conference Paper

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