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

• Type: Journal
• Year: 2002
• Where: SIGIR
• Authors: Kian Ming Adam Chai, Hai Leong Chieu, Hwee Tou Ng
• Keywords: Information Technology, SIGIR 2002, Text Classification, Text Filtering, Text Filtering Task