一种有效的多元时间序列相似性度量算法分析

The Analysis for an Effective Algorithm of Similarity Measurement of Multivariate Time Series

为验证Eros距离对MTS数据集相似性度量的有效性,针对不同MTS数据集进行了相似性搜索实验研究.结果表明:相对于其他的传统多元时间序列相似性度量,基于Eros距离的相似性度量方法比传统的方法在查全率-查准率上具有更大的优越性.

In order to show the validity of Eros for similarity search on MTS datasets, several experiments were performed on different datasets. The experimental results show that the method of similarity measurement based on Eros distance has superiority in Recall-Precision as compared to the traditional similarity measurements for MTS datasets.