基于Naïve贝叶斯方法的中文文本分类器研究与实现

Jian Huang, Zhongdi Cen, Qiuhong Zheng
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引用次数: 2

摘要

Naïve贝叶斯分类器被证明是最有效的分类器之一,应用广泛。它将统计理论应用于文本分类。本文研究并实现了一个基于Naïve贝叶斯方法的JAVA中文文本分类器。本文首先对测试分类系统进行了描述,内容包括文本信息的表达、提取和中文文本分类方法。然后利用JAVA实现Naïve贝叶斯分类算法。最后,本文对该分类系统中的分类器进行了性能评价,用查全率、查全率和运行时间等指标对分类结果进行了评价,实验表明该分类系统具有较高的分类准确率。
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Research and Implement of Chinese Text Classifier Based on Naïve Bayes Method
Naïve Bayes classifier is proved to be one of the most effective classifier an be used widely. It applies statistical theory to text classification. This paper researched and implemented a Chinese text classifier using JAVA base on Naïve Bayes Method. First of all, this paper described test classification system, the content includes text information expressing, extracting and the method of Chinese text classification. Then it used JAVA to implement Naïve Bayes classification algorithm. Finally this paper made a performance evaluation to the classifier in this classification system, it used the indicators of precision, recall and run time to evaluate the classification results, experiment showed that this classification system has a higher classification accuracy.
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