A new feature selection based on comprehensive measurement both in inter-category and intra-category for text categorization

Information Processing and Management

Volumn 48, Issue 4, 2012, Pages 741-754

  Yang, Jieming ^a,b   Liu, Yuanning ^a   Zhu, Xiaodong ^a   Liu, Zhen ^a,c   Zhang, Xiaoxu ^a  

^a JILIN UNIVERSITY   (China)

^b NORTHEAST ELECTRIC POWER UNIVERSITY   (China)

^c NAGASAKI INSTITUTE OF APPLIED SCIENCE   (Japan)

Author keywords

Feature selection; Na ve Bayes; Support Vector Machines; Text categorization

Indexed keywords

BAYES CLASSIFIER; COMPREHENSIVE MEASUREMENT; DOCUMENT COLLECTION; DOCUMENT FREQUENCY; FEATURE SELECTION ALGORITHM; INFORMATION GAIN; REUTERS-21578; TEXT CATEGORIZATION; TWO CLASSIFICATION;

ALGORITHMS; FEATURE EXTRACTION; INFORMATION RETRIEVAL SYSTEMS; SUPPORT VECTOR MACHINES; TEXT PROCESSING;

CLASSIFIERS;

EID: 84862784257     PISSN: 03064573     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.ipm.2011.12.005     Document Type: Article

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