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SIGIR
2002
ACM

Bayesian online classifiers for text classification and filtering

9 years 27 days ago
Bayesian online classifiers for text classification and filtering
This paper explores the use of Bayesian online classifiers to classify text documents. Empirical results indicate that these classifiers are comparable with the best text classification systems. Furthermore, the online approach offers the advantage of continuous learning in the batch-adaptive text filtering task. Categories and Subject Descriptors H.3.3 [Information Systems]: Information Search and Retrieval--Information filtering General Terms Algorithms, Experimentation Keywords Text Classification, Text Filtering, Bayesian, Online, Machine Learning
Kian Ming Adam Chai, Hai Leong Chieu, Hwee Tou Ng
Added 23 Dec 2010
Updated 23 Dec 2010
Type Journal
Year 2002
Where SIGIR
Authors Kian Ming Adam Chai, Hai Leong Chieu, Hwee Tou Ng
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