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Chinese Web Text Classification System Model Based on Naive Bayes

机译:基于朴素贝叶斯的中文网页文本分类系统模型

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Web text classification is the process of determine the text types automatically under a given classification, according to the text content. Web text categorization system is the use of machine learning, knowledge engineering and other related fields of knowledge, access to the web on the text, after text preprocessing, Chinese word segmentation and training classifier, using classification algorithm to implement automatic classification. This paper designed a web of Chinese text categorization system model and system tested, experimental results show that the classification system of the web text categorization with two main characteristics which are efficiency and accuracy.
机译:Web文本分类是根据文本内容在给定分类下自动确定文本类型的过程。 Web文本分类系统是利用机器学习,知识工程等相关领域的知识,对文本进行访问的网络,经过文本预处理,中文分词和训练分类器后,使用分类算法来实现自动分类。本文设计了一种网络中文文本分类系统模型并进行了测试,实验结果表明,该网络文本分类系统具有效率和准确性两个主要特点。

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