New boosting algorithms for text categorization

Proceedings of the World Congress on Intelligent Control and Automation (WCICA)

Volumn 3, Issue , 2002, Pages 2326-2329

  Diao, Lili ^a   Lu, Mingyu ^a   Hu, Keyun ^a   Lu, Yuchang ^a   Shi, Chunyi ^a  

^a State Key Laboratory of Tribology   (China)

Author keywords

Boosting; Decision tree; Text categorization; VSM

Indexed keywords

DECISION THEORY; HEURISTIC METHODS; ITERATIVE METHODS; MATHEMATICAL MODELS; PROBLEM SOLVING; TEXT PROCESSING; TREES (MATHEMATICS); VECTORS;

BOOSTING ALGORITHM; DECISION TREE; SINGLE BASE CLASSIFIER; TEXT CATEGORIZATION; VECTOR SPACE MODEL;

ALGORITHMS;

EID: 0036956251     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper

References (5)

1. R. Schapire and Y. Singer, "BoosTexter: A boosting-based system for text categorization". Machine Learning, 39(2/3), 2000, pp.135-168
2. L. Diao, K. Hu, Y. Lu, et. al, "Boosting improved stumps for text categorization", Journal of Software, 2002, to appear.
3. F. Sebastiani, A. Perduti and N. Valdambrini, "An improved boosting algorithm and its application to automated text categorization". In Arvin Agah, Jamie Callan, and Elke Rundensteiner, editors, Proceedings of CIKM-00, 9th ACM International Conference on Information and Knowledge Management, McLean, US. ACM Press, New York, US. 2000, pp.78-85
4. G. Salton, A. Wong and C. Yang, "A Vector Space Model for Automatic Indexing". Communication of the ACM, Vol. 18, 1995, pp. 613-620
5. R. Schapire and Y. Singer, "Improved boosting algorithms using confidence-related predictions". Machine Learning, 37(3), 1999, pp.297-336