| 基于意群的计算机证据倾向性研究 |
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| 引用本文： | 易军凯,孟庆庆.基于意群的计算机证据倾向性研究[J].北京化工大学学报(自然科学版),2010,37(1):126-129. |
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| 作者姓名： | 易军凯 孟庆庆 |
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| 作者单位： | 北京化工大学 信息科学与技术学院， 北京 100029 |
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| 基金项目： | “十一五”国家科技支撑计划(2006BAK31B04) |
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| 摘 要： | 计算机证据具有数量繁多、复杂多样等特点,因此如何快速地定位可疑文件是目前亟需解决的问题。利用意群概念和朴素贝叶斯算法对计算机证据的倾向性进行了分析研究。通过训练产生以意群为单位存储的倾向性词库。利用朴素贝叶斯算法,对待测文档中筛选出的一定数目的关键词的概率进行计算,从而得出待测文档内容的倾向性。实验表明基于意群的计算机证据倾向性研究方法在获取可疑文件方面有很好的应用效果。
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| 关 键 词： | 意群 证据倾向性 朴素贝叶斯 |
| 收稿时间： | 2009-04-28 |
Sense group-based computer evidence tendencies |
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| YI JunKai,MENG QingQing.Sense group-based computer evidence tendencies[J].Journal of Beijing University of Chemical Technology,2010,37(1):126-129. |
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| Authors: | YI JunKai MENG QingQing |
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| Institution: | College of Information Science and Technology, Beijing University of Chemical Technology, Beijing 100029, China |
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| Abstract: | Computer evidence is characterized by features such as large quantities,complexity and diversity.How to position suspicious files quickly is an urgent problem.Here we use the concept of a sense group and a Naive Bayes algorithm to study sense group-based computer evidence tendencies.The library of tendency words including sense group units is set up by training.A Naive Bayes algorithm is used to calculate the probability of some keywords which are selected from a test file.Computer evidence tendency can be ... |
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| Keywords: | sense group computer evidence tendency Naive Bayes algorithm |
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