Automatic Chinese Text Classification Using N-Gram Model

Author:

Yen Show-Jane,Lee Yue-Shi,Wu Yu-Chieh,Ying Jia-Ching,Tseng Vincent S.

Publisher

Springer Berlin Heidelberg

Reference22 articles.

1. Aizawa, A.: Linguistic Techniques to Improve the Performance of Automatic Text Categorization. In: 6th Natural Language Processing Pacific Rim Symposium, pp. 307–314 (2001)

2. Chen, S., Goodman, J.: An Empirical Study of Smoothing Techniques for Language Modeling. In: 34th Annual Meeting of the Association for Computational Linguistics, pp. 310–318 (1998)

3. Cavnar, W., Trenkle, J.: N-Gram-Based Text Categorization. In: 3rd Annual Symposium on Document Analysis and Information Retrieval, pp. 161–175 (1994)

4. Damashek, M.: Gauging Similarity with N-Grams: Language-Independent Categorization of Text. Science 267, 843–848 (1995)

5. Dumais, S., Platt, J., Heckerman, D., Sahami, M.: Inductive Learning Algorithms and Representations for Text Categorization. In: 7th International Conference on Information and Knowledge Management, pp. 148–155 (1998)

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