Computer Engineering and Applications ›› 2009, Vol. 45 ›› Issue (12): 147-148.DOI: 10.3778/j.issn.1002-8331.2009.12.048
• 数据库、信号与信息处理 • Previous Articles Next Articles
SHI Rui-fang
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史瑞芳
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Abstract: Naïve Bayes method is a simple and effective established probability categorization method at present.However，the problems on scattered data in methodology and Laplace smoothness method have some disadvantages.Therefore，author proposes to use uni-gram smoothness method to improve the condition and the effect on categorization by Bayes method.
Key words: Bayes text categorization, scattered data, smoothness
摘要： 朴素贝叶斯文本分类是目前公认的一种简单有效的概率分类方法，但该方法的数据稀疏问题以及所采用的Laplace平滑方法还不是最优，存在一定的缺陷。因此，用一元统计语言模型的平滑方法来改进数据稀疏状况，提高了分类效果。
关键词: 贝叶斯文本分类, 数据稀疏, 平滑
SHI Rui-fang. Research and improvement on Naive Bayes text classifier[J]. Computer Engineering and Applications, 2009, 45(12): 147-148.
史瑞芳. 贝叶斯文本分类器的研究与改进[J]. 计算机工程与应用, 2009, 45(12): 147-148.
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URL: http://cea.ceaj.org/EN/10.3778/j.issn.1002-8331.2009.12.048
http://cea.ceaj.org/EN/Y2009/V45/I12/147
