Keogh, Eamonn

Experiencing SAX: A novel symbolic representation of time series

Lin, J., Keogh, E., Wei, L., & Lonardi, S. (2007) · Data Mining and Knowledge Discovery

Time Series Analysis and ForecastingData Mining Algorithms and Applications

Cited by 1,618

The great time series classification bake off: a review and experimental evaluation of recent algorithmic advances

Bagnall, A., Lines, J., Bostrom, A., Large, J., & Keogh, E. (2017) · Data Mining and Knowledge Discovery

Time Series Analysis and ForecastingMusic and Audio Processing

Cited by 1,377

An online algorithm for segmenting time series

Keogh, E., Chu, S., Hart, D., & Pazzani, M. (2002) · Proceedings 2001 IEEE International Conference on Data Mining

Time Series Analysis and ForecastingData Mining Algorithms and Applications

Cited by 1,149

The UCR time series archive

Dau, H. A., Bagnall, A., Kamgar, K., Yeh, C.-C. M., Zhu, Y., Gharghabi, S., Ratanamahatana, C. A., & Keogh, E. (2019) · IEEE/CAA Journal of Automatica Sinica

Time Series Analysis and ForecastingData Mining and Machine Learning Applications

Cited by 1,128

Time series shapelets: a novel technique that allows accurate, interpretable and fast classification

Ye, L., & Keogh, E. (2011) · Data Mining and Knowledge Discovery

Time Series Analysis and ForecastingImage Retrieval and Classification Techniques

Cited by 406

A Complexity-Invariant Distance Measure for Time Series

Batista, G. E. A. P. A., Wang, X., & Keogh, E. J. (2011) · Proceedings of the 2011 SIAM International Conference on Data Mining

Time Series Analysis and ForecastingData Mining Algorithms and Applications

Cited by 329

The UEA multivariate time series classification archive, 2018

Bagnall, A., Dau, H. A., Lines, J., Flynn, M., Large, J., Bostrom, A., Southam, P., & Keogh, E. (2018) · arXiv

Time Series Analysis and ForecastingMusic and Audio Processing

Cited by 87