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Abstract: In this work, a set of comparative experiments for the problem of automatically filtering unwanted electronic mail messages are performed on two public corpora: PU1 and LingSpam. Several variants of the AdaBoost algorithm with confidence--rated predictions [14] have been applied, which differ in the complexity of the base learners considered. (Update)
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BibTeX entry: (Update)
X. Carreras and L. Mrquez. Boosting trees for anti-spam email filtering. In Proceedings of RANLP-01, Jth International Conference on Recent Advances in Natural Language Processing, Tzigov Chark, BG, 2001. http://citeseer.ist.psu.edu/article/carreras01boosting.html More
@inproceedings{ carreras01boosting,
author = "Xavier Carreras and Llu\'{\i}s M\'arquez",
title = "Boosting Trees for Anti-Spam Email Filtering",
booktitle = "Proceedings of {RANLP}-01, 4th International Conference on Recent Advances in Natural Language Processing",
address = "Tzigov Chark, BG",
year = "2001",
url = "citeseer.ist.psu.edu/article/carreras01boosting.html" }
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236 Additive logistic regression: a statistical view of boosting - Friedman, Hastie et al. - 2000
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166 A re-examination of text categorization methods - Yang, Liu - 1999
149 An evaluation of statistical approaches to text categorizati.. - Yang - 1999
76 BoosTexter: A boosting-based system for text categorization - Schapire, Singer - 2000
76 A bayesian approach to filtering junk e-mail - Sahami, Dumais et al. - 1998
66 Learning rules that classify e-mail - Cohen
54 Boosting and Rocchio applied to text filtering - Schapire, Singer et al. - 1998
32 Evaluating and optimizing autonomous text classification sys.. - Lewis - 1995
29 Maximizing text-mining performance (context) - Weiss, Apte et al. - 1999
26 Support vector machines for spam categorization (context) - Drucker, Wu et al. - 1999
25 The alternating decision tree learning algorithm - Freund, Mason - 1999
23 The trec-9 filtering track final report - Robertson, Hull - 2001
19 Communications of the ACM (context) - Cranor, LaMacchia - 1998
15 An experimental comparison of naive bayesian and keyword-bas.. (context) - Androutsopoulos, Koutsias et al. - 2000
6 Part--of--Speech Tagging: A Machine--Learning Approach based.. (context) - Marquez - 1999
5 Stacking classifiers for anti-spam filtering of e-mail (context) - Sakkis, Androutsopoulos et al.
5 Learning to filter spam e-mail: A comparison of a naive baye.. - Androutsopoulos, Paliouras et al.
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