首页> 外文会议>2012 Ninth Web Information Systems and Applications Conference >Detection Splog Algorithm Based on Features Relation Tree
【24h】

Detection Splog Algorithm Based on Features Relation Tree

机译:基于特征关系树的检测Splog算法

获取原文
获取原文并翻译 | 示例

摘要

Blogosphere has become a hot research field in recent years.As the existing detection algorithm has problems of inefficient feature selection and weak correlation,we propose an algorithm of splog detection based on features relation tree.We could construct the tree according to the correlation of the features,reserving the strong relevance features and removing the weak ones,then prune the redundant and irrelevance features by using the secondary features selection method and retain the best feature subset.The experimental results conducted in the Libsvm platform show that the algorithm based on the features of relation tree has higher precision and covering rate compared to the traditional ones.The precision of the algorithm on simulated training remains at about 90%,which has better generalization ability.
机译:由于目前的检测算法存在特征选择效率低,相关性弱的问题,因此提出了一种基于特征关系树的splog检测算法。特征,保留强关联特征,去除弱关联,然后通过使用次要特征选择方法修剪冗余特征和不相关特征,并保留最佳特征子集。在Libsvm平台上进行的实验结果表明,基于特征的算法与传统算法相比,该算法具有更高的精度和覆盖率。该算法在模拟训练中的精度保持在90%左右,具有较好的泛化能力。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号