A rough set-based CBR approach for feature and document reduction in text categorization

Proceedings of 2004 International Conference on Machine Learning and Cybernetics

Volumn 4, Issue , 2004, Pages 2438-2443

  Li, Yan ^a,c   Shiu, Simon Chi Keung ^a   Pal, Sankar Kumar ^b   Liu, James Nga Kwok ^a  

^a HONG KONG POLYTECHNIC UNIVERSITY   (Hong Kong)

^b INDIAN STATISTICAL INSTITUTE   (India)

^c HEBEI UNIVERSITY   (China)

Author keywords

Case Coverage; Case Reachability; Case based Reasoning (CBR); Rough Set; Text Categorization (TC)

Indexed keywords

ALGORITHMS; FUZZY SETS; LEARNING SYSTEMS; MATHEMATICAL MODELS; MATRIX ALGEBRA; PATTERN RECOGNITION; PROBLEM SOLVING; SEMANTICS; VECTORS;

CASE COVERAGE; CASE REACHABILITY; CASE-BASED REASONING (CBR); ROUGH SET; TEXT CATEGORIZATION (TC);

SET THEORY;

EID: 6344222968     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper

References (12)

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