10.7: References

[1] Sidorov, G., Gupta, A., Tozer, M., Catal , D., Catena, A. and Fuentes, S. (2013). Rule-based System for Automatic Grammar Correction Using Syntactic N-grams for English Language Learning (L2). CoNLL Shared Task, pp.

[2] Correa, D., Sureka, A. (2014). Chaff from the wheat: characterization and modeling of deleted questions on stack overflow. Proceedings of the 23rd international conference on World wide web April 2014 Pages 631 642https://doi.org/10.1145/2566486.2568036

[3] Yang, Y., Pedersen, J. (1997). A Comparative Study on Feature Selection in Text Categorization. ICML '97: Proceedings of the Fourteenth International Conference on Machine Learning. July 1997. Pages 412 420

[4] Largeron, C., Moulin C., G ry M. Entropy based feature selection for text categorization. ACM Symposium on Applied Computing, Mar 2011, TaiChung, Taiwan. pp.924-928, ff10.1145/1982185.1982389ff. ffhal-00617969

[5] Simeon, M. and Hilderman, R. (2008). Categorical Proportional Difference: A Feature Selection Method for Text Categorization. In Proc. Seventh Australasian Data Mining Conference (AusDM 2008), Glenelg, South Australia. CRPIT, 87. Roddick, J. F., Li, J., Christen, P. and Kennedy, P. J., Eds. ACS. 201-208.

[6] O Keefe, T., Koprinska, I. (2009) Feature Selection and Weighting Methods in Sentiment Analysis

[7] Bidi, N., Elberrichi, Z. (2016) Feature selection for text classification using genetic algorithms. 8th International Conference on modeling, Identification and Control (ICMIC). 15-17 Nov. 2016

[8] Kumar, G., Ramachandra, G., Nagamani, K. (2014) An Efficient Feature Selection System to Integrating SVM with Genetic Algorithm for Large Medical Datasets. International Journal of Advanced Research in Computer Science and Software Engineering. Volume 4, Issue 2, February 2014

[9] Wang, H., He, C., Li, Z. (2020). A new ensemble feature selection approach based on genetic algorithm. Soft Comput 24, 15811 15820 (2020). https://doi.org/10.1007/s00500-020-04911-x

[10] Goldberg, Y., Levy, O. (2014) word2vec Explained: deriving Mikolov et al.'s negative-sampling word-embedding method