We address the problem of subsequence search in time series using Chebyshev distance, to which we refer as twin subsequence search. We first show how existing time series indices can be extended to perform twin subsequence search. Then, we introduce TS-Index, a novel index tailored to this problem. Our experimental evaluation compares these approaches against real time series datasets, and demonstrates that TS-Index can retrieve twin subsequences much faster under various query conditions. This paper has been published in the 24th International Conference on Extending Database Technology (EDBT 2021).
翻译:我们用切比谢夫距离(我们称之为双次次次次次次次次次次次次的搜索)解决时间序列中的后继搜索问题。 我们首先展示如何扩大现有时间序列指数以进行双次次次次次的搜索。 然后, 我们引入了针对这一问题的新颖的TS- Index指数。 我们的实验性评估将这些方法与实时序列数据集进行比较, 并表明TS- Index在不同查询条件下可以更快地检索双次次次序列。 这份文件已在第24次扩展数据库技术国际会议( EDBT 2021)上发表。