| 基于粗糙集与贝叶斯决策的不良网页过滤研究 |
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| 引用本文： | 孙艳,周学广.基于粗糙集与贝叶斯决策的不良网页过滤研究[J].中文信息学报,2012,26(1):67-72. |
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| 作者姓名： | 孙艳 周学广 |
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| 作者单位： | 海军工程大学 电子工程学院,湖北 武汉 430033 |
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| 基金项目： | 海军工程大学科学研究基金(HGDYDJJ10008);总参预研项目 |
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| 摘 要： | 不良网页过滤是一种两类网页分类问题。提出了一种基于粗糙集与贝叶斯决策相结合的不良网页分类过滤方法,首先利用粗糙集理论的区分矩阵和区分函数得到网页分类决策的属性约简;然后通过贝叶斯决策理论对网页进行分类与过滤决策。仿真实验表明,该方法在不良网页分类过滤系统中开销小,过滤准确度高,因而在快速过滤不良网页的应用中具有工程应用价值。
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| 关 键 词： | 信息安全 网页过滤 粗糙集 区分矩阵 贝叶斯决策 |
Research on Webpage Filtering Based on Rough Set and Bayesian Decision Theory |
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| SUN Yan
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ZHOU Xueguang.Research on Webpage Filtering Based on Rough Set and Bayesian Decision Theory[J].Journal of Chinese Information Processing,2012,26(1):67-72. |
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| Authors: | SUN Yan ZHOU Xueguang |
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| Affiliation: | College of Electronic Engineering, Naval University of Engineering, Wuhan, Hubei 430033,China |
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| Abstract: | Treating the webpage filtering as a classification task,a new method based on Rough set and Bayesian decision theory is proposed.Attribute reduction of Webpages classification is obtained by the discernibility matrix and discernibility function according to the the Rough Set theory.Then,the Webpage is classified and filtered by the Bayesian decision theory.Simulation experiments show the effectiveness of the proposed method. |
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| Keywords: | information security Webpage filtering rough set discernibility matrix Bayesian decision |
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