计算机应用研究2011，Vol.28Issue(3)：895-898,4.DOI:10.3969/j.issn.1001-3695.2011.03.028
挖掘滑动时间衰减窗口中网络流频繁项集
Mining network traffic frequent itemsets with sliding-time-fading window
摘要
Abstract
Mining network traffic frequent itemsets is an important foundation for network traffic analysis.This paper proposed a novel algorithm STFWFI( sliding time fading window frequent itemsets) based on lexicographic ordered prefix tree LOP-Tree.STFWFI used a sliding-time-fading window model which accorded with the characteristic of network traffic, and reduced the computational time complexity and space complexity efficiently.Proposed a novel node weight count measure SDNW( statistical distribution node weight )in LOP-Tree structure based on statistical distribution instead of the conventional statistical count measure, and improved the count precision of network traffic nodes.The experimental results show that STFWFI performs much better than the previous approaches in mining network traffic frequent itemsets.关键词
网络流数据挖掘/频繁项集/滑动时间衰减窗口/字典顺序前缀树分类
信息技术与安全科学引用本文复制引用
赖军,李双庆..挖掘滑动时间衰减窗口中网络流频繁项集[J].计算机应用研究,2011,28(3):895-898,4.基金项目
中央高校基本科研业务费资助项目(CDJZR10180012) （CDJZR10180012）
