A Parallel, Structural Comparison Scheme of Time-Series Implemented on a PC Cluster

S. Hirano, S. Tsumoto
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Abstract

This paper presents a scheme for pallarel computation of similarity matrix using a PC cluster. Pairwise comparison of N sequences essentially requires N(N + 1)/2 computational tasks; therefore, a simple and efficient comparison method such as Euclidean distance or Dynamic Time Warping is often used. Focusing on the fact that the pair-wise comparison can be processed independently for different pairs of sequences, we employ a palallel computation scheme with a PC cluster and attempt to include more complex, structure-based pairwise comparison method. Experimental results on the cylinder- bell-funnel data set demonstrate that the combination of parallel computation and structural comparison may be used for handling a difficult clustering task of time series.
一种在PC机集群上实现的并行、结构化时间序列比较方案
本文提出了一种基于PC聚类的相似矩阵并行计算方案。N个序列的两两比较本质上需要N(N + 1)/2个计算任务;因此,通常采用一种简单有效的比较方法,如欧几里得距离或动态时间翘曲。针对不同序列对的两两比较可以独立处理的事实,我们采用了PC集群的并行计算方案,并尝试包含更复杂的、基于结构的两两比较方法。在圆柱-钟形漏斗数据集上的实验结果表明,并行计算和结构比较相结合的方法可以用于处理时间序列的复杂聚类任务。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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