Chotirat Ann Ratanamahatana
Chotirat Ann Ratanamahatana
Associate Professor, Dept. of Computer Engineering, Chulalongkorn University
Verified email at chula.ac.th
Title
Cited by
Cited by
Year
Exact indexing of dynamic time warping
E Keogh, CA Ratanamahatana
Knowledge and information systems 7 (3), 358-386, 2005
26452005
Towards parameter-free data mining
E Keogh, S Lonardi, CA Ratanamahatana
Proceedings of the tenth ACM SIGKDD international conference on Knowledge …, 2004
7142004
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
5832006
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
4452004
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
4052005
Everything you know about dynamic time warping is wrong
CA Ratanamahatana, E Keogh
Third workshop on mining temporal and sequential data 32, 2004
3592004
Scaling and time warping in time series querying
AWC Fu, E Keogh, LYH Lau, CA Ratanamahatana, RCW Wong
The VLDB Journal 17 (4), 899-921, 2008
2702008
The ucr time series classification/clustering home-page
E Keogh
http://www. cs. ucr. edu/~ eamonn/time_series_data/, 2006
2322006
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
2022005
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
1632005
Assumption-Free Anomaly Detection in Time Series.
L Wei, N Kumar, VN Lolla, EJ Keogh, S Lonardi, ...
SSDBM 5, 237-242, 2005
1492005
A novel bit level time series representation with implication of similarity search and clustering
C Ratanamahatana, E Keogh, AJ Bagnall, S Lonardi
Pacific-Asia conference on knowledge discovery and data mining, 771-777, 2005
1372005
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 (1), 99-129, 2007
1262007
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
1252007
Feature selection for the naive bayesian classifier using decision trees
C Ratanamahatana, D Gunopulos
Applied artificial intelligence 17 (5-6), 475-487, 2003
1162003
The UCR Time Series Classification
E Keogh, X Xi, L Wei, CA Ratanamahatana
Clustering Homepage: www. cs. ucr. edu/~ eamonn/time_series_data, 2011
1082011
A bit level representation for time series data mining with shape based similarity
A Bagnall, E Keogh, S Lonardi, G Janacek
Data Mining and Knowledge Discovery 13 (1), 11-40, 2006
942006
Scaling up the naive Bayesian classifier: Using decision trees for feature selection
CA Ratanamahatana, D Gunopulos
892002
The UCR time series classification/clustering homepage (2006)
E Keogh, X Xi, L Wei, CA Ratanamahatana
URL www. cs. ucr. edu/~ eamonn/time_ series_data, 2002
762002
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
692019
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