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
9012012
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
3812013
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
2152013
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
1252011
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
1152014
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
1102007
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
742011
MDL-based time series clustering
T Rakthanmanon, EJ Keogh, S Lonardi, S Evans
Knowledge and information systems 33 (2), 371-399, 2012
582012
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
452012
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
312013
Efficient proper length time series motif discovery
S Yingchareonthawornchai, H Sivaraks, T Rakthanmanon, ...
2013 IEEE 13th International Conference on Data Mining, 1265-1270, 2013
302013
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
232016
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
232013
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
182015
A fast LSH-based similarity search method for multivariate time series
C Yu, L Luo, LLH Chan, T Rakthanmanon, S Nutanong
Information Sciences 476, 337-356, 2019
172019
A scalable framework for cross-lingual authorship identification
R Sarwar, Q Li, T Rakthanmanon, S Nutanong
Information Sciences 465, 323-339, 2018
152018
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
152014
Mining historical documents for near-duplicate figures
T Rakthanmanon, Q Zhu, EJ Keogh
2011 IEEE 11th International Conference on Data Mining, 557-566, 2011
152011
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
142015
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
142012
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