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» Online Discriminative Spam Filter Training
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KDD
2008
ACM
132views Data Mining» more  KDD 2008»
14 years 5 months ago
Partitioned logistic regression for spam filtering
Naive Bayes and logistic regression perform well in different regimes. While the former is a very simple generative model which is efficient to train and performs well empirically...
Ming-wei Chang, Wen-tau Yih, Christopher Meek
SIGIR
2009
ACM
13 years 11 months ago
Spam filter evaluation with imprecise ground truth
When trained and evaluated on accurately labeled datasets, online email spam filters are remarkably effective, achieving error rates an order of magnitude better than classifie...
Gordon V. Cormack, Aleksander Kolcz
AIRWEB
2008
Springer
13 years 6 months ago
A few bad votes too many?: towards robust ranking in social media
Online social media draws heavily on active reader participation, such as voting or rating of news stories, articles, or responses to a question. This user feedback is invaluable ...
Jiang Bian, Yandong Liu, Eugene Agichtein, Hongyua...
ML
2010
ACM
135views Machine Learning» more  ML 2010»
12 years 11 months ago
Multi-domain learning by confidence-weighted parameter combination
State-of-the-art statistical NLP systems for a variety of tasks learn from labeled training data that is often domain specific. However, there may be multiple domains or sources o...
Mark Dredze, Alex Kulesza, Koby Crammer