Thanawin Rakthanmanon
Thanawin Rakthanmanon
Dept. of Computer Engineering, Kasetsart University, Thailand
Verified email at ku.ac.th
Title
Cited by
Cited by
Year
Searching and mining trillions of time series subsequences under dynamic time warping
T Rakthanmanon, B Campana, A Mueen, G Batista, B Westover, Q Zhu, ...
Proceedings of the 18th ACM SIGKDD international conference on Knowledge …, 2012
7592012
Fast shapelets: A scalable algorithm for discovering time series shapelets
T Rakthanmanon, E Keogh
proceedings of the 2013 SIAM International Conference on Data Mining, 668-676, 2013
3112013
Addressing big data time series: Mining trillions of time series subsequences under dynamic time warping
T Rakthanmanon, B Campana, A Mueen, G Batista, B Westover, Q Zhu, ...
ACM Transactions on Knowledge Discovery from Data (TKDD) 7 (3), 1-31, 2013
1712013
Time series epenthesis: Clustering time series streams requires ignoring some data
T Rakthanmanon, EJ Keogh, S Lonardi, S Evans
2011 IEEE 11th International Conference on Data Mining, 547-556, 2011
1072011
Beyond one billion time series: indexing and mining very large time series collections with SAX2+
A Camerra, J Shieh, T Palpanas, T Rakthanmanon, E Keogh
Knowledge and information systems 39 (1), 123-151, 2014
962014
E-stream: Evolution-based technique for stream clustering
K Udommanetanakit, T Rakthanmanon, K Waiyamai
International conference on advanced data mining and applications, 605-615, 2007
952007
Discovering the intrinsic cardinality and dimensionality of time series using MDL
B Hu, T Rakthanmanon, Y Hao, S Evans, S Lonardi, E Keogh
2011 IEEE 11th International Conference on Data Mining, 1086-1091, 2011
662011
MDL-based time series clustering
T Rakthanmanon, EJ Keogh, S Lonardi, S Evans
Knowledge and information systems 33 (2), 371-399, 2012
502012
A novel approximation to dynamic time warping allows anytime clustering of massive time series datasets
Q Zhu, G Batista, T Rakthanmanon, E Keogh
Proceedings of the 2012 SIAM international conference on data mining, 999-1010, 2012
412012
Efficient proper length time series motif discovery
S Yingchareonthawornchai, H Sivaraks, T Rakthanmanon, ...
2013 IEEE 13th International Conference on Data Mining, 1265-1270, 2013
262013
Towards never-ending learning from time series streams
Y Hao, Y Chen, J Zakaria, B Hu, T Rakthanmanon, E Keogh
Proceedings of the 19th ACM SIGKDD international conference on Knowledge …, 2013
242013
Towards a minimum description length based stopping criterion for semi-supervised time series classification
N Begum, B Hu, T Rakthanmanon, E Keogh
2013 IEEE 14th International Conference on Information Reuse & Integration …, 2013
212013
Rapid annotation of interictal epileptiform discharges via template matching under dynamic time warping
J Jing, J Dauwels, T Rakthanmanon, E Keogh, SS Cash, MB Westover
Journal of neuroscience methods 274, 179-190, 2016
172016
Using the minimum description length to discover the intrinsic cardinality and dimensionality of time series
B Hu, T Rakthanmanon, Y Hao, S Evans, S Lonardi, E Keogh
Data Mining and Knowledge Discovery 29 (2), 358-399, 2015
142015
A minimum description length technique for semi-supervised time series classification
N Begum, B Hu, T Rakthanmanon, E Keogh
Integration of reusable systems, 171-192, 2014
142014
Image mining of historical manuscripts to establish provenance
B Hu, T Rakthanmanon, B Campana, A Mueen, E Keogh
Proceedings of the 2012 SIAM International Conference on Data Mining, 804-815, 2012
122012
Mining historical documents for near-duplicate figures
T Rakthanmanon, Q Zhu, EJ Keogh
2011 IEEE 11th International Conference on Data Mining, 557-566, 2011
122011
Data mining a trillion time series subsequences under dynamic time warping
T Rakthanmanon, E Keogh
Twenty-Third International Joint Conference on Artificial Intelligence, 2013
112013
A scalable framework for cross-lingual authorship identification
R Sarwar, Q Li, T Rakthanmanon, S Nutanong
Information Sciences 465, 323-339, 2018
92018
A general framework for never-ending learning from time series streams
Y Chen, Y Hao, T Rakthanmanon, J Zakaria, B Hu, E Keogh
Data mining and knowledge discovery 29 (6), 1622-1664, 2015
92015
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