Semantic features for multi-view semi-supervised and active learning of text classification

Proceedings - IEEE International Conference on Data Mining Workshops, ICDM Workshops 2008

Volumn , Issue , 2008, Pages 731-735

  Sun, Shiliang ^a  

^a EAST CHINA NORMAL UNIVERSITY   (China)

Author keywords

[No Author keywords available]

Indexed keywords

DATA MINING; EDUCATION; INFORMATION MANAGEMENT; INFORMATION THEORY; SEMANTICS; SUPERVISED LEARNING; TECHNICAL PRESENTATIONS; TEXT PROCESSING;

ACTIVE LEARNING; BASIS VECTORS; CANONICAL CORRELATION ANALYSIS; CLASSIFIER TRAININGS; CO TRAININGS; EXISTING METHODS; INTEGRATING INFORMATIONS; LEARNING PARADIGMS; MULTI VIEWS; MULTI-VIEW LEARNING; MULTIPLE VIEWS; PATTERN REPRESENTATIONS; SEMANTIC FEATURES; SEMANTIC SPACES; SEMI-SUPERVISED; SEMI-SUPERVISED LEARNING; TEXT CLASSIFICATIONS; TWO STATE;

LEARNING ALGORITHMS;

EID: 62449091237     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/ICDMW.2008.13     Document Type: Conference Paper

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