Poisson naive Bayes for text classification with feature weighting

Proceedings of the 6th International Workshop on Information Retrieval with Asian Languages, IRAL 2003

Volumn , Issue , 2003, Pages 33-40

  Kim, Sang Bum ^a   Seo, Hee Cheol ^a   Rim, Hae Chang ^a  

^a Korea University   (South Korea)

Author keywords

[No Author keywords available]

Indexed keywords

CLASSIFICATION (OF INFORMATION); CLASSIFIERS; INFORMATION RETRIEVAL; INFORMATION RETRIEVAL SYSTEMS;

FEATURE WEIGHTING; FEATURE-BASED; FEATURES SELECTION; LEARN+; NAIVE BAYES; NAIVE BAYES TEXT CLASSIFIER; POISSON MODEL; TEST COLLECTION; TEXT CLASSIFICATION MODELS; TRAINING DOCUMENTS;

TEXT PROCESSING;

EID: 40549095554     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper

References (13)

1. William S. Cooper, Fredric C. Gey, and Daniel P. Dabney. 1992. Probabilistic retrieval based on staged logsitic regression. Proceedings of SIGIR-92, 15th ACM International Conference on Research and Development in Information Retrieval, pages 198–210.
2. Pedro Domingos and Michael J. Pazzani. 1997. On the optimality of the simple bayesian classifier under zero-one loss. Machine Learning, 29(2/3):103–130.
3. Susan Dumais, John Plat, David Heckerman, and Mehran Sahami. 1998. Inductive learning algorithms and representation for text categorization. Proceedings of CIKM-98, 7th ACM International Conference on Information and Knowledge Management, pages 148–155.
4. Thorsten Joachims. 1998. Text categorization with support vector machines: learning with many relevant features. Proceedings of ECML-98, 10th European Conference on Machine Learning, pages 137–142.
5. Karen Sparck Jones, Steve Walker, and Stephen E. Robertson. 2000. A probabilistic model of information retrieval: development and comparative experiments - part 1. Information Processing and Management, 36(6):779–808.
6. David D. Lewis. 1992. Representation and learning in information retrieval. Ph.D. thesis, Department of Computer Science, University of Massachusetts, Amherst, US.
7. David D. Lewis. 1998. Naive (Bayes) at forty: The independence assumption in information retrieval. Proceedings of ECML-98, 10th European Conference on Machine Learning, pages 4–15.
8. Andrew K. McCallum and Kamal Nigam. 1998. Employing EM in pool-based active learning for text classification. Proceedings of ICML-98, 15th International Conference on Machine Learning, pages 350–358.
9. Kamal Nigam, Andrew K. McCallum, Sebastian Thrun, and Tom M. Mitchell. 2000. Text classification from labeled and unlabeled documents using EM. Machine Learning, 39(2/3):103–134.
10. Robert E. Schapire and Yoram Singer. 2000. BOOSTEXTER: a boosting-based system for text categorization. Machine Learning, 39(2/3):135–168.
11. Yiming Yang and Christopher G. Chute. 1994. An example-based mapping method for text categorization and retrieval. ACM Transactions on Information Systems, 12(3):252–277.
12. Yiming Yang and Xin Liu. 1999. A re-examination of text categorization methods. Proceedings of SIGIR-99, 22nd ACM International Conference on Research and Development in Information Retrieval, pages 42–49.
13. Yiming Yang and Jan O. Pedersen. 1997. A comparative study on feature selection in text categorization. Proceedings of ICML-97, 14th International Conference on Machine Learning, pages 412–420.