| 面向不均衡类别朴素贝叶斯犯罪案件文本分类 |
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| 引用本文： | 程春惠,何钦铭.面向不均衡类别朴素贝叶斯犯罪案件文本分类[J].计算机工程与应用,2009,45(35):126-128. |
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| 作者姓名： | 程春惠 何钦铭 |
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| 作者单位： | 浙江大学计算机科学与技术学院,杭州,310027 |
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| 基金项目： | 浙江省重大科技攻关项目 |
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| 摘 要： | 针对案件文本的特点,提出了具有针对性的特殊文本预处理方法,并比较了两种有效的特征选择方法。针对案件类别分布不均衡的特点,提出了改进的多变量贝努里模型。实验结果表明,改进的多变量贝努里模型有效地提高了案件文本分类的准确率。
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| 关 键 词： | 文本分类 朴素贝叶斯 犯罪挖掘 多变量贝努里模型 多项式模型 |
| 收稿时间： | 2009-5-27 |
| 修稿时间： | 2009-7-3
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Naive Bayes based criminal text classification of unbalanced classes |
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| CHENG Chun-hui,HE Qin-ming.Naive Bayes based criminal text classification of unbalanced classes[J].Computer Engineering and Applications,2009,45(35):126-128. |
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| Authors: | CHENG Chun-hui HE Qin-ming |
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| Affiliation: | College of Computer Science，Zhejiang University，Hangzhou 310027，China |
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| Abstract: | According to the feature of case text，this paper explores the special text preprocessing method and compares two effective feature selection methods.An improved model based on multi-variate Bernoulli model is proposed，due to the unbalanced distribution of criminal case categories.The experiment indicates that the improved Naive Bayes method performs better in the case text classification. |
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| Keywords: | text classification Naive Bayes criminal mining multi-variate Bernoulli model multinomial mode |
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