点击次数：

影响因子：3.4

DOI码：10.1016/j.softx.2022.101049

所属单位：University of Bremen

发表刊物：SoftwareX

刊物所在地：Netherlands

关键字：time series; subsequence search; distances; similarity measurements; query-based search; segmentation; Python package

摘要：Subsequence search and distance measures are crucial tools in time series data mining. This paper presents our Python package entitled TSSEARCH, which provides a comprehensive set of methods for subsequence search and similarity measurement in time series. These methods are user-customizable for more flexibility and efficient integration into real deployment scenarios. TSSEARCH enables fast exploratory time series data analysis and was validated in the context of human activity recognition and indoor localization.

备注：https://tssearch.readthedocs.io/en/latest/

全部作者：Duarte Folgado*, Marília Barandas, Margarida Antunes, Maria Lua Nunes, Hui Liu, Yale Hartmann, Tanja Schultz, Hugo Gamboa

论文类型：期刊论文

学科门类：工学

文献类型：J

卷号：18

页面范围：101049

ISSN号：2352-7110

是否译文：否

发表时间：2022-06-01

收录刊物：SCI

发布刊物链接：https://www.sciencedirect.com/science/article/pii/S2352711022000425