The following papers use shapelets or develop the shapelet algorithm. We provide a bibtex file here. Please feel free to email Tony ( if you notice an omission.


  1. Ye, L. and Keogh, E., Time series shapelets: a new primitive for data mining. Proceedings of the 15th ACM SIGKDD international conference on Knowledge discovery and data mining, 2009.
  2. Mueen, A., Keogh, E., and Young, N., Logical-shapelets: an expressive primitive for time series classification. Proceedings of the 17th ACM SIGKDD international conference on Knowledge discovery and data mining, 2011.
  3. Xing, Z., Pei, J., Yu, P., and Wang, K., Extracting interpretable features for early classification on time series. Proceedings of the 11th SIAM International Conference on Data Mining (SDM), 2011.
  4. Chang, K-W., Deka, B., Hwu, W-M., and Roth, D., Efficient Pattern-Based Time Series Classification on GPU. Proceedings of the 12th IEEE International Conference on Data Mining (ICDM), 2012.
  5. Gordon, D., Hendler, D., and Rokach, L., Fast Randomized Model Generation for Shapelet-Based Time Series Classification. arXiv preprint arXiv:1209.5038, 2012.
  6. He, Q., Zhuang, F., Shang, T., and Shi, Z., Fast Time Series Classification Based on Infrequent Shapelets. Proceedings of 11th International Conference on Machine Learning and Applications (ICMLA), 2012.
  7. Lines, J. and Bagnall, A.,  Alternative Quality Measures for Time Series Shapelets. Lecture Notes in Computer Science, 7435. pp. 475-483.  preprint.pdf , 2012.
  8. Lines, J., Davis, L., Hills, J., and Bagnall, A.,  A Shapelet Transform for Time Series Classification  Proceedings of the 18th International Conference on Knowledge Discovery in Data and Data Mining. preprint.pdf, 2012.
  9. Xing, Z., Pei, J., and Yu, P.S.,  Early classification on time series. Knowledge and information systems 31(1), 2012.
  10. Zakaria, J., Mueen, A., and Keogh, E. (2012): Clustering Time Series using Unsupervised-Shapelets. Proceedings of the 12th IEEE International Conference on Data Mining (ICDM), 2012.
  11. Hills, J., Lines, J., Baranauskas, E., Mapp, J., and Bagnall, A., Time Series Classification with Shapelets, Journal of Data Mining and Knowledge Discovery.  online first preprint.pdf, 2012.
  12. Rakthanmanon, T. and Keogh, E., Fast Shapelets: A Scalable Algorithm for Discovering Time Series Shapelets. Proceedings of the 13th SIAM International Conference on Data Mining (SDM), 2013.


  1. Hartmann, B. and Link, N., Gesture recognition with inertial sensors and optimized dtw prototypes, Proceedings of IEEE International Conference on Systems Man and Cybernetics (SMC), 2010.
  2. Hartmann, B., Schwab, I., and Link, N., Prototype optimization for temporarily and spatially distorted time series. AAAI Spring Symposia, 2010.
  3. Liu, J., Zhong, L., Wickramasuriya, J., and Vasudevan, V.,  uWave: Accelerometer-based personalized gesture recognition and its applications. Pervasive and Mobile Computing 5(6), 2009.
  4. McGovern, A., Rosendahl, D.H., Brown, R.A., and Droegemeier, K.K., Identifying predictive multi-dimensional time series motifs: an application to severe weather prediction. Data Mining and Knowledge Discovery. 22(1), 2011.
  5. Reiss, A., Weber, M., and Stricker, D., Exploring and extending the boundaries of physical activity recognition Proceedings of IEEE International Conference on Systems Man and Cybernetics (SMC), 2011.
  6. Sivakumar, P.B. and Shajina, T.,  Human Gait Recognition and Classification Using Time Series Shapelets Proceedings of Advances in Computing and Communications (ICACC), 2012.
  7. Contreras, S and Sundararajan V (2012).   Visual Imagery Classification

    Using Shapelets of EEG Signals. Proceedings of the ASME 2012 International Design Engineering Technical Conferences & Computers and Information in Engineering Conference.( IDETC/CIE)

Code and/or Data has been downloaded by:

Kanhaiya Kuma


Qiusheng YE

Fuzhou University, China

Vojtech Kopal

Utrech, Netherlands

Andre Coelho

University of Fortaleza, Brazil

Carlo Launer


Patrick Schäfer

Zuse-Institut Berlin

Martin Wistuba

University of Hildesheim

Daniel Gordon

Ben Gurion University, Isreal

Zhao zhihong

Shijiazhuang Tiedao University

Puneet Singh

TCS innovation labs Delhi

Jose Ramon Villar

University of Oviedo

Abhishek Anand


Meng Li

University of Magdeburd

Denes Toth

Hungarian Academy of Sciences



Carlos Sanchez

University of Oklahoma

Jie Yang


Pavel Senin

University of Hawaii

V. AnanthaNatarajan

Annamalai University

Xu Meng

Nanyang Technological University Singapore

Jidong Yuan

Beijing Jiaotong University

Willian Zalewski

Parana Federal University

Athanasios Koutras

Technical Educational Institute of Western Greece

Mustafa Sinan Çetin

University of New Mexico

Ehtesham Hassan

Innovation Labs TCS


Washington University in St.Louis