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SIGIR
1998
ACM

Boosting and Rocchio Applied to Text Filtering

9 years 4 months ago
Boosting and Rocchio Applied to Text Filtering
We discuss two learning algorithms for text filtering: modified Rocchio and a boosting algorithm called AdaBoost. We show how both algorithms can be adapted to maximize any general utility matrix that associates cost (or gain) for each pair of machine prediction and correct label. We first show that AdaBoost significantly outperforms another highly effective text filtering algorithm. We then compare AdaBoost and Rocchio over three large text filtering tasks. Overall both algorithms are comparable and are quite effective. AdaBoost produces better classifiers than Rocchio when the training collection contains a very large number of relevant documents. However, on these tasks, Rocchio runs much faster than AdaBoost.
Robert E. Schapire, Yoram Singer, Amit Singhal
Added 05 Aug 2010
Updated 05 Aug 2010
Type Conference
Year 1998
Where SIGIR
Authors Robert E. Schapire, Yoram Singer, Amit Singhal
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