Scaling and time warping in time series querying
Scaling and time warping in time series querying
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DOI：
10.1007/s00778-006-0040-z
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发表时间：
2008-07-01
期刊：
影响因子：
4.2
通讯作者：
Wong, Raymond Chi-Wing
中科院分区：
文献类型：
--
作者：
Fu, Ada Wai-Chee;Keogh, Eamonn;Wong, Raymond Chi-Wing
在过去几年中，人们越来越认识到动态时间规整 (DTW) 这种技术可以在对齐时间序列时实现局部灵活性，它优于普遍存在的时间序列分类、聚类和索引的欧几里得距离。最近，研究表明，对于某些问题，统一缩放（US）（一种允许对时间序列进行全局缩放的技术）对于某些问题可能同样重要。在这项工作中，我们注意到，对于许多现实世界的问题，有必要将 DTW 和 US 结合起来才能取得有意义的结果。在我们必须考虑人类行为的自然变异性的领域尤其如此，包括生物识别、嗡嗡声查询、动作捕捉/动画和手写识别。我们介绍了第一种可以同时处理 DTW 和 US 的技术，我们的技术涉及通过下限技术和多维索引来加速搜索的搜索修剪。我们展示了我们的方法在工业、医学和娱乐领域的广泛问题上的实用性和有效性。
The last few years have seen an increasing understanding that dynamic time warping (DTW), a technique that allows local flexibility in aligning time series, is superior to the ubiquitous Euclidean distance for time series classification, clustering, and indexing. More recently, it has been shown that for some problems, uniform scaling (US), a technique that allows global scaling of time series, may just be as important for some problems. In this work, we note that for many real world problems, it is necessary to combine both DTW and US to achieve meaningful results. This is particularly true in domains where we must account for the natural variability of human actions, including biometrics, query by humming, motion-capture/animation, and handwriting recognition. We introduce the first technique which can handle both DTW and US simultaneously, our techniques involve search pruning by means of a lower bounding technique and multi-dimensional indexing to speed up the search. We demonstrate the utility and effectiveness of our method on a wide range of problems in industry, medicine, and entertainment.