Ma J, Perkins S. Online novelty detection on temporal sequences. In: Proceedings of the 9th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining. New York, USA: ACM, 2003. 613-618
[2]
Keogh E J, Lonardi S, Chiu B Y. Finding surprising patterns in a time series database in linear time and space. In: Proceedings of the 8th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining. Alberta, Canada: ACM, 2002. 550-556
[3]
Keogh E J, Lin J, Fu A W, Herle H V. Finding unusual medical time-series subsequences: algorithms and applications. IEEE Transactions on Information Technology in Biomedicine, 2006, 10(3): 429-439
[4]
Wu M R, Ye J P. A small sphere and large margin approach for novelty detection using training data with outliers. IEEE Transactions on Pattern Analysis and Machine Intelligence, 2009, 31(11): 2088-2092
[5]
Jiang M F, Tseng S S, Su C M. Two-phase clustering process for outliers detection. Pattern Recognition Letters, 2001, 22(6-7): 691-700
[6]
Chen Bin, Feng Ai-Min, Chen Song-Can, Li Bin. One-cluster clustering based data description. Chinese Journal of Computers, 2007, 30(8): 1325-1332(陈斌, 冯爱民, 陈松灿, 李斌. 基于单簇聚类的数据描述. 计算机学报, 2007, 30(8): 1325-1332)
[7]
Moody G B. MIT-BIH arrhythmia database directory [Online], available: http://www.physionet.org/physiobank/database/html/mitdbdir/intro.htm, January 31, 2011
[8]
Wei L, Kumar N, Lolla V N, Keogh E J, Lonardi S, Ratanamahatana C. Assumption-free anomaly detection in time series. In: Proceedings of the 17th International Scientific and Statistical Database Management. California, USA: Lawrence Berkeley Laboratory, 2005. 237-240
[9]
Yang J, Wang W, Yu P S. Mining surprising periodic patterns. Data Mining and Knowledge Discovery, 2004, 9(2): 189-216
[10]
Tax D M J. Data description tool-box (dd tools) [Online], available: http://homepage.tudelft.nl/n9d04/dd_tools.html, January 31, 2011
[11]
Cao L J, Lee H P, Chong W K. Modified support vector novelty detector using training data with outliers. Pattern Recognition Letters, 2003, 24(14): 2479-2487
[12]
Hochbaum D S, Shmoys D B. A best possible heuristic for the κ -center problem. Mathematics of Operations Research, 1985, 10(2): 180-184
[13]
Rebbapragada U, Protopapas P, Brodley C E, Alcock C R. Finding anomalous periodic time series. Machine Learning, 2009, 74(3): 281-313
