@inproceedings{1d1a7f2fc5ba44b39c500d1526be7b48,
title = "Critical vector learning for text categorisation",
abstract = "This paper proposes a new text categorisation method based on the critical vector learning algorithm. By implementing a Bayesian treatment of a generalised linear model of identical function form to the support vector machine, the proposed approach requires signi-cantly fewer support vectors. This leads to much reduced computational com- plexity of the prediction process, which is critical in online applications.",
keywords = "Critical vector learning, Relevance vector machine, Support vector machine, Text Classi cation",
author = "Lei Zhang and Debbie Zhang and Simo, \{Simeon J.\}",
year = "2005",
language = "English",
isbn = "1863657169",
series = "AusDM 2005 Proc. - 4th Australasian Data Mining Conf. - Collocated with the 18th Australian Joint Conf. on Artificial Intelligence, AI 2005 and the 2nd Australian Conf. on Artifical Life, ACAL 2005",
pages = "27--35",
booktitle = "AusDM 2005 Proc. - 4th Australasian Data Mining Conf. - Collocated with the 18th Australian Joint Conf. on Artificial Intelligence, AI 2005 and the 2nd Australian Conf. on Artificial Life, ACAL 2005",
note = "4th Australasian Data Mining Conference, AusDM 2005 - Collocated with the 18th Australian Joint Conference on Artificial Intelligence, AI 2005 and the 2nd Australian Conference on Artificial Life, ACAL 2005 ; Conference date: 05-12-2005 Through 06-12-2005",
}