A Maximal Figure-of-Merit Learning Approach to Text Categorization

SIGIR Forum (ACM Special Interest Group on Information Retrieval)

Volumn , Issue SPEC. ISS., 2003, Pages 174-181

  Gao, Shena ^a   Wu, Wen ^b   Lee, Chin Hui ^b,c   Chua, Tat Seng ^b  

^a INSTITUTE FOR INFOCOMM RESEARCH   (Singapore)

^b NATIONAL UNIVERSITY OF SINGAPORE   (Singapore)

^c GEORGIA INSTITUTE OF TECHNOLOGY   (United States)

Author keywords

Decision tree; Generalized probabilistic descent method; Latent semantic indexing; Maximal figure of merit; Support vector machines; Text categorization

Indexed keywords

CLASSIFICATION (OF INFORMATION); DECISION THEORY; ERROR ANALYSIS; FEATURE EXTRACTION; INDEXING (OF INFORMATION); LEARNING SYSTEMS; NEURAL NETWORKS; PARAMETER ESTIMATION; PROBABILISTIC LOGICS; TREES (MATHEMATICS); VECTORS;

DECISION TREE; GENERALIZED PROBABILISTIC DESCENT METHOD; LATENT SEMANTIC INDEXING; MAXIMAL FIGURE-OF-MERIT; SUPPORT VECTOR MACHINES; TEXT CATEGORIZATION;

TEXT PROCESSING;

EID: 1542377538     PISSN: 01635840     EISSN: None     Source Type: Journal    
DOI: 10.1145/860468.860469     Document Type: Conference Paper

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