基于朴素贝叶斯的中文Web文本分类系统模型

Zheng Gong, Tian Yu
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引用次数: 25

摘要

Web文本分类是在给定的分类下,根据文本内容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,获取Web上的文本,经过文本预处理、中文分词和训练分类器,利用分类算法实现自动分类。本文设计了一个web中文文本分类系统模型并对系统进行了测试,实验结果表明该分类系统对web文本分类具有效率和准确性两个主要特点。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Chinese Web Text Classification System Model Based on Naive Bayes
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.
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