Very large Bayesian multinets for text classification

Klopotek MA

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Very large Bayesian multinets for text classification

机译：用于文本分类的超大型贝叶斯多网

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摘要

This paper presents a newly developed algorithm learning very large tree-like Bayesian networks from data and exploits it to create a Bayesian multinet (BMN) classifier for natural language text documents.Results of empirical evaluation of this BMN classifier are presented. The study suggests that tree-like Bayesian networks are able to handle a classification task in 100 000 variables with sufficient speed and accuracy. (c) 2004 Elsevier B.V. All rights reserved.

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《Future generation computer systems》 |2005年第7期|p. 1068-1082|共15页
作者
Klopotek MA;
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作者单位

Polish Acad Sci, Inst Comp Sci, PL-01237 Warsaw, Poland;

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收录信息美国《科学引文索引》(SCI);美国《工程索引》(EI);
原文格式 PDF
正文语种 eng
中图分类计算技术、计算机技术;
关键词
Bayesian; multinets; classification; DEPENDENCE;

机译：贝叶斯;多网;分类;依赖;

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Very large Bayesian multinets for text classification

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