LoCoMotif: discovering time-warped motifs in time series
Author:
Funder
VLAIO ICON-AI Conscious project
Vlaamse regering
Publisher
Springer Science and Business Media LLC
Link
https://link.springer.com/content/pdf/10.1007/s10618-024-01032-z.pdf
Reference26 articles.
1. Alaee S, Kamgar K, Keogh E (2020) Matrix profile XXII: exact discovery of time series motifs under DTW. In: 2020 IEEE international conference on data mining (ICDM), pp 900–905. https://doi.org/10.1109/ICDM50108.2020.00099
2. Bagnall A, Hills J, Lines J (2014) Finding motif sets in time series. arXiv preprint arXiv:1407.3685. https://doi.org/10.48550/arXiv.1407.3685
3. Benavoli A, Corani G, Mangili F (2016) Should we really use post-hoc tests based on mean-ranks? J Mach Learn Res 17(5):1–10
4. Dau HA, Keogh E, Kamgar K, Yeh C-CM, Zhu Y, Gharghabi S, Ratanamahatana CA, Yanping Hu B, Begum N, Bagnall A, Mueen A, Batista G (2018) The UCR time series classification archive. https://www.cs.ucr.edu/~eamonn/time_series_data_2018/
5. Dau HA, Keogh E (2017) Matrix profile V: a generic technique to incorporate domain knowledge into motif discovery. In: Proceedings of the 23rd ACM SIGKDD international conference on knowledge discovery and data mining, pp 125-134. https://doi.org/10.1145/3097983.3097993
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