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Chotirat Ann Ratanamahatana
Chotirat Ann Ratanamahatana
Associate Professor, Dept. of Computer Engineering, Chulalongkorn University
Bestätigte E-Mail-Adresse bei chula.ac.th
Titel
Zitiert von
Zitiert von
Jahr
Exact indexing of dynamic time warping
E Keogh, CA Ratanamahatana
Knowledge and information systems 7, 358-386, 2005
34612005
Towards parameter-free data mining
E Keogh, S Lonardi, CA Ratanamahatana
Proceedings of the tenth ACM SIGKDD international conference on Knowledge …, 2004
8632004
The UCR time series archive
HA Dau, A Bagnall, K Kamgar, CCM Yeh, Y Zhu, S Gharghabi, ...
IEEE/CAA Journal of Automatica Sinica 6 (6), 1293-1305, 2019
8442019
Fast time series classification using numerosity reduction
X Xi, E Keogh, C Shelton, L Wei, CA Ratanamahatana
Proceedings of the 23rd international conference on Machine learning, 1033-1040, 2006
7132006
Making time-series classification more accurate using learned constraints
CA Ratanamahatana, E Keogh
Proceedings of the 2004 SIAM international conference on data mining, 11-22, 2004
5942004
Three myths about dynamic time warping data mining
CA Ratanamahatana, E Keogh
Proceedings of the 2005 SIAM international conference on data mining, 506-510, 2005
5452005
Everything you know about dynamic time warping is wrong
CA Ratanamahatana, E Keogh
Third workshop on mining temporal and sequential data 32, 2004
4742004
Scaling and time warping in time series querying
AWC Fu, E Keogh, LYH Lau, CA Ratanamahatana, RCW Wong
The VLDB Journal 17, 899-921, 2008
3132008
Mining time series data
CA Ralanamahatana, J Lin, D Gunopulos, E Keogh, M Vlachos, G Das
Data mining and knowledge discovery handbook, 1069-1103, 2005
2772005
The UCR time series classification archive
HA Dau, E Keogh, K Kamgar, CCM Yeh, Y Zhu, S Gharghabi, ...
URL https://www. cs. ucr. edu/~ eamonn/time_series_data_2018, 2018
2682018
On clustering multimedia time series data using k-means and dynamic time warping
V Niennattrakul, CA Ratanamahatana
2007 International Conference on Multimedia and Ubiquitous Engineering (MUE …, 2007
2522007
Time-series bitmaps: a practical visualization tool for working with large time series databases
N Kumar, VN Lolla, E Keogh, S Lonardi, CA Ratanamahatana, L Wei
Proceedings of the 2005 SIAM international conference on data mining, 531-535, 2005
2112005
Assumption-Free Anomaly Detection in Time Series.
L Wei, N Kumar, VN Lolla, EJ Keogh, S Lonardi, ...
SSDBM 5, 237-242, 2005
2102005
A novel bit level time series representation with implication of similarity search and clustering
C Ratanamahatana, E Keogh, AJ Bagnall, S Lonardi
Advances in Knowledge Discovery and Data Mining: 9th Pacific-Asia Conference …, 2005
1922005
Compression-based data mining of sequential data
E Keogh, S Lonardi, CA Ratanamahatana, L Wei, SH Lee, J Handley
Data Mining and Knowledge Discovery 14, 99-129, 2007
1862007
Yanping, Bing Hu, Nurjahan Begum, Anthony Bagnall, Abdullah Mueen, Gustavo Batista, and Hexagon-ML. The ucr time series classification archive, October 2018
HA Dau, E Keogh, K Kamgar, CCM Yeh, Y Zhu, S Gharghabi, ...
184*2018
Feature selection for the naive bayesian classifier using decision trees
C Ratanamahatana, D Gunopulos
Applied artificial intelligence 17 (5-6), 475-487, 2003
1432003
A bit level representation for time series data mining with shape based similarity
A Bagnall, CA Ratanamahatana, E Keogh, S Lonardi, G Janacek
Data mining and knowledge discovery 13 (1), 11-40, 2006
1212006
The UCR Time Series Classification
E Keogh, X Xi, L Wei, CA Ratanamahatana
Clustering Homepage, 2011
1172011
Scaling up the naive Bayesian classifier: Using decision trees for feature selection
CA Ratanamahatana, D Gunopulos
Proc. Workshop Data Cleaning and Preprocessing (DCAP'02), at IEEE Int'l Conf …, 2002
1092002
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