基于倾斜时间窗口的高效数据流偏向最近聚类分析算法

提出一种基于倾斜时间窗口的数据流偏向最近聚类算法。该算法首先通过将滑动窗口中数据等长分割形成不重叠的数据块——基本窗口，然后对每一基本窗口以Haar小波变换提取窗口数据的特征，通过改变所取各基本窗口小波变换系数个数达到保留较多最近数据细节特征的目的，即对于越近的基本窗口保留越多的小波系数而越旧的基本窗口保留越少的小波系数，最后通过定义数据流偏向最近距离，完成基于倾斜时间窗口的偏向最近聚类算法。该算法计算速度快，能高效地实现数据流偏向最近聚类分析。仿真实验验证了该算法的有效性。

Efficient Recent-biased Clustering Algorithm of Data Stream Based on Tilted-time Window

A recent-biased clustering algorithm of data stream based on tilted-time window is proposed.First,the algorithm segments sliding window equal in length to form no overlap data blocks(basic window),then extracts feature of every data block through Haar wavelet transform,and preserves detailed feature of recent data by varying number of wavelet coefficients of data block,namely more recent data block,more wavelet coefficient preserved,and vice versa.Finally,by defining recent-biased distance of data stream,th...