Document Classification via Nonlinear Metric Learning
Author:
Funder
the National Natural Science Foundation of China
Shanghai Sailing Program
Publisher
Springer Science and Business Media LLC
Subject
Artificial Intelligence,Computer Networks and Communications,General Neuroscience,Software
Link
http://link.springer.com/article/10.1007/s11063-017-9654-y/fulltext.html
Reference32 articles.
1. Schneider KM (2005) Techniques for improving the performance of naive bayes for text classification. In: International conference on intelligent text processing and computational linguistics. Springer, Berlin, pp 682–693
2. Klopotek MA, Woch M (2003) Very large Bayesian networks in text classification. In: International conference on computational science. Springer, Berlin, pp 397–406
3. Siolas G, Dalchebuc F (2000) Support vector machines based on a semantic kernel for text categorization. In: Proceedings of the IEEE-INNS-ENNS international joint conference on neural networks. IEEE, pp 205–209
4. Shanahan JG, Roma N (2003) Improving SVM text classification performance through threshold adjustment. In: European conference on machine learning. Springer, Berlin, pp 361–372
5. Johnson DE, Oles FJ, Zhang T, Goetz T (2002) A decision-tree-based symbolic rule induction system for text categorization. IBM Syst J 41(3):428–437
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