1. Bifet, A., Holmes, G., Kirkby, R., et al.: MOA: massive online analysis. J. Mach. Learn. Res. 11(2), 1601–1604 (2010)
2. Chen, H.L., Chen, M.S., Lin, S.C.: Catching the trend: a framework for clustering concept-drifting categorical data. IEEE Trans. Knowl. Data Eng. 21(5), 652–665 (2009)
3. Qi, J.P., Zhang, Q., Zhu, Y., Qi, J.: A novel method for fast change-point detection on simulated time series and electrocardiogram data. PLoS ONE 9(4), 1–15 (2014)
4. Baikovicius, J., Gerencser, L.: Change point detection in a stochastic complexity framework. In: 1990 29th IEEE Conference on Decision and Control, Honolulu, USA, pp. 3554–3555 (1990)
5. Yoshinobu, K., Masashi, S.: Change-point detection in time-series data by direct density-ratio estimation. In: 2009 SIAM International Conference on Data Mining, pp. 389–400 (2009)