Statistical Approach for Term Weighting in Very Short Documents for Text Categorization

Author:

Timonen Mika,Kasari Melissa

Publisher

Springer Berlin Heidelberg

Reference19 articles.

1. Salton, G., Buckley, C.: Term-weighting approaches in automatic text retrieval. Information Processing and Management 24, 513–523 (1988)

2. Timonen, M., Silvonen, P., Kasari, M.: Classification of short documents to categorize consumer opinions. In: Online Proceedings of 7th International Conference on Advanced Data Mining and Applications (ADMA 2011), China (2011), http://aminer.org/PDF/adma2011/session3D/adma11_conf_32.pdf (accessed October 10, 2012)

3. Timonen, M.: Categorization of very short documents. In: Internation Conference on Knowledge Discovery and Information Retrieval (KDIR 2012), Spain, pp. 5–16 (2012)

4. Forman, G.: An extensive empirical study of feature selection metrics for text classification. Journal of Machine Learning Research 3, 1289–1305 (2003)

5. Rennie, J.D.M., Jaakkola, T.: Using term informativeness for named entity detection. In: Proceedings of the 28th Annual International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR 2005), Brazil, pp. 353–360 (2005)

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