A comparative study of centroid-based, neighborhood-based and statistical approaches for effective document categorization

Proceedings - International Conference on Pattern Recognition

Volumn 16, Issue 4, 2002, Pages 235-238

  Tam, Vincent ^a   Santoso, Ardi ^b   Setiono, Rudy ^b  

^a UNIVERSITY OF HONG KONG   (Hong Kong)

^b NATIONAL UNIVERSITY OF SINGAPORE   (Singapore)

Author keywords

[No Author keywords available]

Indexed keywords

ALGORITHMS; PATTERN RECOGNITION; PATTERN RECOGNITION SYSTEMS; CLASSIFIERS;

CENTROID-BASED CLASSIFIERS; DOCUMENT CATEGORIZATION; HIGHEST AVERAGE SIMILARITY OVER RETRIEVED DOCUMENTS (HASRD);

INFORMATION RETRIEVAL SYSTEMS; NEAREST NEIGHBOR SEARCH;

AVERAGE SIMILARITIES; COMPARATIVE STUDIES; DOCUMENT CATEGORIZATION; K-NEAREST NEIGHBORHOODS; RETRIEVED DOCUMENTS; REUTERS-21578 CORPUS; STATISTICAL APPROACH; TERM WEIGHTING SCHEME;

EID: 29144522357     PISSN: 10514651     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper

References (9)

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