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基于时间窗口权值的数据流分类算法

Data stream classification algorithm using time window weighting
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摘要 针对不同时间段的数据流对当前数据流分类影响程度不同,在滑动窗口技术基础上提出了时间窗口权值的频繁模式(TWWFP)分类算法.首先,对滑动窗口中的每个基本窗口赋予一个与时间有关的窗口权值;然后,采用TWWFP-Tree结构存储当前滑动窗口中每个基本窗口中的频繁数据属性,实时更新TWWFP-Tree结构;最后,检测相邻3个滑动窗口中权值属性的平均分类误差,发现突变后及时减少下一个滑动窗口的长度可适应数据流的变化.实验证明该分类算法比没有时间窗口权值分类算法的精确度最大提高3%. Data stream classification algorithm was proposed using time window weighed frequent patterns（TWWFP） based on sliding window technology.The algorithm improves classification precision and the ability of accommodating the mutational data stream.First,every basic window of sliding window was endow with time window weighting.Second,the frequent data attributes in basing window were stored in TWWFP-Tree that update in time.Finally,it showed that the length of the sliding window will be reduced to adapt the data stream changing by inspecting the average classification error in the vicinity of the two sliding window.Experiments show that the precision of classification algorithm with time window weight was improved by 3% than that with no time window weighting.
作者 方湘艳 于燕婷 丁宜栋 熊庭刚
机构地区 哈尔滨工程大学计算机学院 中国船舶重工集团公司第 海军工程大学电气工程学院 海军计算机技术研究所
出处 《华中科技大学学报（自然科学版）》 EI CAS CSCD 北大核心 2011年第1期41-44,共4页 Journal of Huazhong University of Science and Technology(Natural Science Edition)
基金 国防科技预研基金资助项目(08J3.74)
关键词 数据流 滑动窗口 时间窗口权值 频繁模式 窗口突变 data stream sliding windows time window weighting frequent patterns window mutation
分类号 TP311 [自动化与计算机技术—计算机软件与理论]
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参考文献13

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二级参考文献18

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共引文献25

华中科技大学学报（自然科学版）
2011年 第1期

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