| 搜索引擎中分类技术研究 |
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| 引用本文： | 万小容,马帅,刘利军.搜索引擎中分类技术研究[J].宁波广播电视大学学报,2008,6(2):116-118. |
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| 作者姓名： | 万小容 马帅 刘利军 |
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| 作者单位： | 昆明理工大学信息工程与自动化学院,云南昆明,650051 |
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| 基金项目： | 昆明理工大学信息工程与自动化学院基金 |
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| 摘 要： | 本文提出了一种基于主题采集的Web文档自动分类算法，该算法对朴素贝叶斯分类模型进行了改进。利用该算法，我们实现了一个基于主题信息采集的网页分类系统。文中着重对该系统的页面解析、中文分词和文本分类模块进行了论述，并对改进后的贝叶斯分类方法进行了评估。实验结果表明，该算法对网页分类有较高的准确性。
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| 关 键 词： | 主题采集 Spider采集 中文分词 文本分类 贝叶斯分类 |
On the Classification Technology in the Search Engine |
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| WAN Xiao-rong,MA Shuai,LIU Li-jun.On the Classification Technology in the Search Engine[J].Journal of Ningbo Radio & TV University,2008,6(2):116-118. |
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| Authors: | WAN Xiao-rong MA Shuai LIU Li-jun |
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| Institution: | (Faculty of Information Engineering and Automation, Kunming University of Science and Technology, Kunming 650051,Yunnan, China ) |
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| Abstract: | This article studied an auto-categorization algorithm based on focused crawling. Naive Bayes categorization model was improved by our algorithm. Using the algorithm, a system ofwebpage auto-categorization was implemented. The implementation of 3 main modules of the system were described in this article： page parsing, Chinese text splitter and text classifying. Finally, an evaluation of algorithm efficiency was given. Experiment data showed that this auto-categorization algorithm had a higher accuracy when applied to webpage classification. |
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| Keywords: | Topic collcting Spider crawling Chinese word segmenting Text classifying Bayes Classifier |
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