Chotirat Ann Ratanamahatana

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	All	Since 2019
Citations	12187	5130
h-index	36	26
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Eamonn KeoghDistinguished Professor of Computer Science, University of California - RiversideVerified email at cs.ucr.edu
Shaghayegh GharghabiDepartment of Electrical and Computer Engineering, University of California, RiversideVerified email at ucr.edu
Stefano LonardiProfessor of Computer Science, University of California, RiversideVerified email at cs.ucr.edu
Tony BagnallProfessor of Computer Science, University of SouthamptonVerified email at uea.ac.uk
Dimitrios GunopulosNational and Kapodistrian University of AthensVerified email at di.uoa.gr
Hoang Anh DauMachine Learning Research Engineer, UberVerified email at uber.com
Christian R. SheltonProfessor, University of California, RiversideVerified email at cs.ucr.edu
Dechawut WanichsanRambhai Barni Rajabhat UniversityVerified email at rbru.ac.th
Gautam DasDistinguished University Chair Professor, Associate Dean, University of Texas at ArlingtonVerified email at uta.edu
Vasileios MegalooikonomouProfessor of Computer Engineering and Informatics, University of PatrasVerified email at ceid.upatras.gr
Raymond Chi-Wing WongThe Hong Kong University of Science and TechnologyVerified email at cse.ust.hk
Ada Wai-Chee FuChinese University of Hong KongVerified email at cse.cuhk.edu.hk
Jessica LinGeorge Mason UniversityVerified email at gmu.edu
Michalis VlachosProfessor, HEC Lausanne, University of LausanneVerified email at unil.ch
LONGIN JAN LATECKIProfessor of Computer Science, Temple University, PhiladelphiaVerified email at temple.edu
Sang-Hee LeeProfessor of Anthropology, UC RiversideVerified email at ucr.edu
John C. HandleyUniversity of RochesterVerified email at rochester.edu
gareth janacekUeaVerified email at uea.ac.uk
Thanawin RakthanmanonDept. of Computer Engineering, Kasetsart University, ThailandVerified email at ku.ac.th
Supasate ChoochaisriChulalongkorn UniversityVerified email at student.chula.ac.th

Chotirat Ann Ratanamahatana

Associate Professor, Dept. of Computer Engineering, Chulalongkorn University

Verified email at chula.ac.th

Data Mining Time Series Mining Machine Learning Artificial Intelligence


Title Sort by citations Sort by year Sort by title	Cited by Cited by	Year
Exact indexing of dynamic time warping E Keogh, CA Ratanamahatana Knowledge and information systems 7, 358-386, 2005	3545	2005
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	946	2019
Towards parameter-free data mining E Keogh, S Lonardi, CA Ratanamahatana Proceedings of the tenth ACM SIGKDD international conference on Knowledge …, 2004	876	2004
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	725	2006
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	609	2004
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	553	2005
Everything you know about dynamic time warping is wrong CA Ratanamahatana, E Keogh Third workshop on mining temporal and sequential data 32, 2004	483	2004
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	316	2008
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	285	2005
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	281	2018
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	267	2007
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	215	2005
Assumption-Free Anomaly Detection in Time Series. L Wei, N Kumar, VN Lolla, EJ Keogh, S Lonardi, ... SSDBM 5, 237-242, 2005	212	2005
Hexagon-ML,“The ucr time series classification archive,” October 2018 HA Dau, E Keogh, K Kamgar, CCM Yeh, Y Zhu, S Gharghabi, ... URL https://www. cs. ucr. edu/~ eamonn/time_series_data_2018, 2018	199*	2018
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	193	2005
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	188	2007
Feature selection for the naive bayesian classifier using decision trees C Ratanamahatana, D Gunopulos Applied artificial intelligence 17 (5-6), 475-487, 2003	149	2003
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	122	2006
The UCR Time Series Classification E Keogh, X Xi, L Wei, CA Ratanamahatana Clustering Homepage, 2011	116	2011
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	110	2002

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