Multinomial Naive Bayes for Text Categorization Revisited

Author:

Kibriya Ashraf M.,Frank Eibe,Pfahringer Bernhard,Holmes Geoffrey

Publisher

Springer Berlin Heidelberg

Reference13 articles.

1. Rennie, J.D.M., Shih, L., Teevan, J., Karger, D.R.: Tackling the poor assumptions of naive Bayes text classifiers. In: Proceedings of the Twentieth International Conference on Machine Learning, Washington, DC, pp. 616–623. AAAI Press, Menlo Park (2003)

2. McCallum, A., Nigam, K.: A comparison of event models for naive Bayes text classification. Technical report, American Association for Artificial Intelligence Workshop on Learning for Text Categorization (1998)

3. Eyheramendy, S., Lewis, D.D., Madigan, D.: On the naive Bayes model for text categorization. In: Ninth International Workshop on Artificial Intelligence and Statistics, pp. 3–6 (2003)

4. Joachims, T.: Text categorization with support vector machines: Learning with many relevant features. In: Proceedings of the Tenth European Conference on Machine Learning, pp. 137–142. Springer, Heidelberg (1998)

5. Dumais, S., Platt, J., Heckerman, D., Sahami, M.: Inductive learning algorithms and representations for text categorization. In: Proceedings of the Seventh International Conference on Information and Knowledge Management, pp. 148–155. ACM Press, New York (1998)

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