UCR Suite

UCR Suite: Software that enables ultrafast subsequence search under both Dynamic Time Warping (DTW) and Euclidean Distance (ED). The work first appeared in a SIGKDD 2012 paper: Rakthanmanon T, Campana B, Mueen A, Batista G, Westover B, Zhu Q, Zakaria J, Keogh E (2012) Searching and mining trillions of time series subsequences under dynamic time warping. Proceedings of the 18th ACM SIGKDD international conference on Knowledge discovery and data mining, pp 262--270


References in zbMATH (referenced in 23 articles )

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  1. Alaee, Sara; Mercer, Ryan; Kamgar, Kaveh; Keogh, Eamonn: Time series motifs discovery under DTW allows more robust discovery of conserved structure (2021)
  2. Chen, Ling; Chen, Donghui; Yang, Fan; Sun, Jianling: A deep multi-task representation learning method for time series classification and retrieval (2021)
  3. Herrmann, Matthieu; Webb, Geoffrey I.: Early abandoning and pruning for elastic distances including dynamic time warping (2021)
  4. Gharghabi, Shaghayegh; Imani, Shima; Bagnall, Anthony; Darvishzadeh, Amirali; Keogh, Eamonn: An ultra-fast time series distance measure to allow data mining in more complex real-world deployments (2020)
  5. Landaluce-Calvo, M. Isabel; Modroño-Herrán, Juan I.: Classification for time series data. An unsupervised approach based on reduction of dimensionality (2020)
  6. Mathew Schwartz; Todd C. Pataky; Cyril J. Donnelly: seg1d: A Python package for Automated segmentation of one-dimensional (1D) data (2020) not zbMATH
  7. Pérez-Chacón, R.; Asencio-Cortés, G.; Martínez-Álvarez, F.; Troncoso, A.: Big data time series forecasting based on pattern sequence similarity and its application to the electricity demand (2020)
  8. Shifaz, Ahmed; Pelletier, Charlotte; Petitjean, François; Webb, Geoffrey I.: TS-CHIEF: a scalable and accurate forest algorithm for time series classification (2020)
  9. Tan, Chang Wei; Petitjean, François; Webb, Geoffrey I.: FastEE: fast ensembles of elastic distances for time series classification (2020)
  10. Wan, Yuqing; Lau, Raymond Yiu Keung; Si, Yain-Whar: Mining subsequent trend patterns from financial time series (2020)
  11. Stübinger, Johannes: Statistical arbitrage with optimal causal paths on high-frequency data of the S&P 500 (2019)
  12. Silva, Diego F.; Giusti, Rafael; Keogh, Eamonn; Batista, Gustavo E. A. P. A.: Speeding up similarity search under dynamic time warping by pruning unpromising alignments (2018)
  13. Kostakis, Orestis; Papapetrou, Panagotis: On searching and indexing sequences of temporal intervals (2017)
  14. Baydogan, Mustafa Gokce; Runger, George: Time series representation and similarity based on local autopatterns (2016)
  15. Huang, Xiaohui; Ye, Yunming; Xiong, Liyan; Lau, Raymond Y. K.; Jiang, Nan; Wang, Shaokai: Time series (k)-means: a new (k)-means type smooth subspace clustering for time series data (2016)
  16. Philipp Boersch-Supan: rucrdtw: Fast time series subsequence search in R (2016) not zbMATH
  17. Schäfer, Patrick: Scalable time series classification (2016)
  18. Chen, Yanping; Hao, Yuan; Rakthanmanon, Thanawin; Zakaria, Jesin; Hu, Bing; Keogh, Eamonn: A general framework for never-ending learning from time series streams (2015)
  19. Schäfer, Patrick: The BOSS is concerned with time series classification in the presence of noise (2015)
  20. Batista, Gustavo E. A. P. A.; Keogh, Eamonn J.; Tataw, Oben Moses; de Souza, Vinícius M. A.: CID: an efficient complexity-invariant distance for time series (2014)

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