A semi-supervised approach to improve classification of infrequent discourse relations using feature vector extension

EMNLP 2010 - Conference on Empirical Methods in Natural Language Processing, Proceedings of the Conference

Volumn , Issue , 2010, Pages 399-409

  Hernault, Hugo ^a   Bollegala, Danushka ^a   Ishizuka, Mitsuru ^a  

^a UNIVERSITY OF TOKYO   (Japan)

Author keywords

[No Author keywords available]

Indexed keywords

CLASSIFICATION ACCURACY; F-SCORE; FEATURE VECTORS; MACHINE-LEARNING; SEMI-SUPERVISED; SEMI-SUPERVISED METHOD; SMALL TRAINING; TRAINING CORPUS; TRAINING SETS; TREEBANKS; UNLABELED DATA;

COMPUTATIONAL LINGUISTICS; LEARNING ALGORITHMS; NATURAL LANGUAGE PROCESSING SYSTEMS;

CLASSIFICATION (OF INFORMATION);

EID: 79952272600     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper

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