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Volumn , Issue , 2003, Pages 28-30

Question classification with support vector machines and error correcting codes

Author keywords

[No Author keywords available]

Indexed keywords

CLASSIFICATION (OF INFORMATION); SEMANTICS; VECTORS;

EID: 85050155813     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper
Times cited : (94)

References (10)
  • 4
    • 27144489164 scopus 로고    scopus 로고
    • A tutorial on support vector machines for pattern recognition
    • 1998
    • C. J. Burges 1998. A tutorial on support vector machines for pattern recognition. Data Mining and Knowledge Discovery. 2(2), pages 121-167, 1998.
    • (1998) Data Mining and Knowledge Discovery , vol.2 , Issue.2 , pp. 121-167
    • Burges, C. J.1
  • 5
    • 69549123046 scopus 로고    scopus 로고
    • Error correcting output codes: A general method for improving multiclass inductive learning programs
    • Anaheim, CA, AAAl Press
    • Tom G. Dietterich and Ghulum Bakiri. 2002. Error correcting output codes: A general method for improving multiclass inductive learning programs. Ninth National Conference on Artificial Intelligence, pages 572-577, Anaheim, CA, AAAl Press.
    • (2002) Ninth National Conference on Artificial Intelligence , pp. 572-577
    • Dietterich, Tom G.1    Bakiri, Ghulum2
  • 9
    • 0002442796 scopus 로고    scopus 로고
    • Machine learning in automated text categorization
    • F. Sebastiani 2002. Machine learning in automated text categorization. ACM Computing Surveys, Vol. 34, No. 1, pages 1-47.
    • (2002) ACM Computing Surveys , vol.34 , Issue.1 , pp. 1-47
    • Sebastiani, F.1
  • 10
    • 33750323368 scopus 로고    scopus 로고
    • Features for unsupervised document classification
    • Taipei, Taiwan,. 2 121-167, 1998
    • S. H. Srinivasan 2002. Features for unsupervised document classification. Proceedings of CoNLL-2002, pages 36-42. Taipei, Taiwan,. 2(2):121-167, 1998.
    • (2002) Proceedings of CoNLL-2002 , Issue.2 , pp. 36-42
    • Srinivasan, S. H.1


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.