| 基于支持向量机的垃圾标签检测模型 |
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| 引用本文： | 覃希,夏宁霞,苏一丹.基于支持向量机的垃圾标签检测模型[J].计算机应用研究,2010,27(10):3893-3895. |
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| 作者姓名： | 覃希 夏宁霞 苏一丹 |
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| 作者单位： | 1. 广西工学院,计算机工程系,广西,柳州,545006
2. 广西大学,计算机与电子信息学院,南宁,530004 |
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| 摘 要： | 为解决Folksonomy存在垃圾标签的问题，提出垃圾标签检测模型。利用向量空间模型表征用户特征，再用支持向量机将Folksonomy用户二分类。通过检测出隐藏在正常用户群体中的垃圾投放人，以此减少垃圾标签数量。实验结果表明，基于支持向量机的垃圾标签检测模型具有更高的分类精度，优于其他检测方法。
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| 关 键 词： | 垃圾标签 社会化标签系统 支持向量机 检测模型 |
SVM-based social spam detection model |
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| QIN Xi,XIA Ning-xi,SU Yi-dan.SVM-based social spam detection model[J].Application Research of Computers,2010,27(10):3893-3895. |
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| Authors: | QIN Xi XIA Ning-xi SU Yi-dan |
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| Affiliation: | (1. Dept. of Computer Engineering, Guangxi University of Technology, Liuzhou Guangxi 545006, China; 2. School of Computer & Electronics Information, Guangxi University, Nanning 530004, China) |
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| Abstract: | The popular social bookmarking sites were always attacked by social spam. This paper designed a SVM-based social spam detection model to solve this problem. That was using VSM to build the user model ,and then divided the users of the sites into two classes by SVM, of which one was the normal, the other was spammer. So cut off the social spam by reducing the spammer. The result of the experiment shows that the classification accuracy of SVM-based social spam detection model is higher than others. |
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| Keywords: | social spam social bookmark system SVM(support vector machines) detection model |
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