InstitucionesPeriodo de publicación recogido
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Introducing time series snippets: a new primitive for summarizing long time series
Shima Imani, Frank Madrid, Wei Ding, Scott E. Crouter, Eamonn Keogh
Data mining and knowledge discovery, ISSN 1384-5810, Vol. 34, Nº 6, 2020, págs. 1713-1743
The Swiss army knife of time series data mining: ten useful things you can do with the matrix profile and ten lines of code
Yan Zhu, Shaghayegh Gharghabi, Diego F. Silva, Hoang Dau, Chin-Chia Yeh, Nader Shakibay Senobari, Abdulaziz Almaslukh, Kaveh Kamgar, Zachary Zimmerman, Gareth Funning, Abdullah Mueen, Eamonn Keogh
Data mining and knowledge discovery, ISSN 1384-5810, Vol. 34, Nº 4, 2020, págs. 949-979
Matrix profile goes MAD: variable-length motif and discord discovery in data series
Michele Linardi, Yan Zhu, Themis Palpanas, Eamonn Keogh
Data mining and knowledge discovery, ISSN 1384-5810, Vol. 34, Nº 4, 2020, págs. 1022-1071
Correction to: Domain agnostic online semantic segmentation for multi-dimensional time series.
Shaghayegh Gharghabi, Chin-Chia Yeh, Yifei Ding, Wei Ding, Paul Hibbing, Samuel LaMunion, Andrew Kaplan, Scott E. Crouter, Eamonn Keogh
Data mining and knowledge discovery, ISSN 1384-5810, Vol. 33, Nº 6, 2019, pág. 1981
Domain agnostic online semantic segmentation for multi-dimensional time series
Shaghayegh Gharghabi, Chin-Chia Yeh, Yifei Ding, Wei Ding, Paul Hibbing, Samuel LaMunion, Andrew Kaplan, Scott E. Crouter, Eamonn Keogh
Data mining and knowledge discovery, ISSN 1384-5810, Vol. 33, Nº 1, 2019, págs. 96-130
EPeeding up similarity search under dynamic time warping by pruning unpromising alignments
D.F. Silva, R. Giusti, Gustavo E .A. P. A. Batista, Eamonn Keogh
Data mining and knowledge discovery, ISSN 1384-5810, Vol. 32, Nº 4, 2018, págs. 988-1016
Optimizing dynamic time warping’s window width for time series data mining applications
Hoang Dau, Eamonn Keogh, Diego F. Silva, François Petitjean, G. Forestier, A. Bagnall, Abdullah Mueen
Data mining and knowledge discovery, ISSN 1384-5810, Vol. 32, Nº 4, 2018, págs. 1074-1120
Time series joins, motifs, discords and shapelets: a unifying view that exploits the matrix profile
Chin-Chia Yeh, Yan Zhu, Liudmila Ulanova, Nurjahan Begum, Yifei Ding, Hoang Dau, Zachary Zimmerman, Diego F. Silva, Abdullah Mueen, Eamonn Keogh
Data mining and knowledge discovery, ISSN 1384-5810, Vol. 32, Nº 1, 2018, págs. 83-123
The great time series classification bake off: a review and experimental evaluation of recent algorithmic advances
Anthony Bagnall, Jason Lines, Aaron Bostrom, James Large, Eamonn Keogh
Data mining and knowledge discovery, ISSN 1384-5810, Vol. 31, Nº 3, 2017, págs. 606-660
Generalizing DTW to the multi-dimensional case requires an adaptive approach
Mohammad Shokoohi-Yekta, Bing Hu, Hongxia Jin, Jun Wang, Eamonn Keogh
Data mining and knowledge discovery, ISSN 1384-5810, Vol. 31, Nº 1, 2017, págs. 1-31
Irrevocable-choice algorithms for sampling from a stream
Yan Zhu, Eamonn Keogh
Data mining and knowledge discovery, ISSN 1384-5810, Vol. 30, Nº 5, 2016, págs. 998-1023
Classification of streaming time series under more realistic assumptions
Bing Hu, Yanping Chen, Eamonn Keogh
Data mining and knowledge discovery, ISSN 1384-5810, Vol. 30, Nº 2, 2016, págs. 403-437
Accelerating the discovery of unsupervised-shapelets
Jesin Zakaria, Abdullah Mueen, Eamonn Keogh, Neal Young
Data mining and knowledge discovery, ISSN 1384-5810, Vol. 30, Nº 1, 2016, págs. 243-281
A general framework for never-ending learning from time series streams
Yanping Chen, Yuan Hao, Thanawin Rakthanmanon, Jesin Zakaria, Bing Hu, Eamonn Keogh
Data mining and knowledge discovery, ISSN 1384-5810, Vol. 29, Nº 6, 2015, págs. 1622-1664
CID: an efficient complexity-invariant distance for time series
Gustavo Batista, Eamonn Keogh, Oben Tataw, Vinícius M.A. Souza
Data mining and knowledge discovery, ISSN 1384-5810, Vol. 28, Nº 3, 2014, págs. 634-669
Experimental comparison of representation methods and distance measures for time series data
Xiaoyue Wang, Abdullah Mueen, Hui Ding, Goce Trajcevski, Peter Scheuermann, Eamonn Keogh
Data mining and knowledge discovery, ISSN 1384-5810, Vol. 26, Nº 2, 2013, págs. 275-309
A disk-aware algorithm for time series motif discovery
Abdullah Mueen, Eamonn Keogh, Qiang Zhu, Sydney Cash, M. Westover, Nima Bigdely-Shamlo
Data mining and knowledge discovery, ISSN 1384-5810, Vol. 22, Nº 1-2, 2011, págs. 73-105
Time series shapelets: a novel technique that allows accurate, interpretable and fast classification
Lexiang Ye, Eamonn Keogh
Data mining and knowledge discovery, ISSN 1384-5810, Vol. 22, Nº 1-2, 2011, págs. 149-182
An efficient and effective similarity measure to enable data mining of petroglyphs
Qiang Zhu, Xiaoyue Wang, Eamonn Keogh, Sang Hee Lee
Data mining and knowledge discovery, ISSN 1384-5810, Vol. 23, Nº 1, 2011, págs. 91-127
iSAX: disk-aware mining and indexing of massive time series datasets
Jin Shieh, Eamonn Keogh
Data mining and knowledge discovery, ISSN 1384-5810, Vol. 19, Nº 1, 2009, págs. 24-57
Efficiently finding unusual shapes in large image databases
Li Wei, Eamonn Keogh, Xiaoping Xu, Melissa Yoder
Data mining and knowledge discovery, ISSN 1384-5810, Vol. 17, Nº 3, 2008, págs. 343-376
Compression-based data mining of sequential data
Eamonn Keogh, Stefano Lonardi, Chotirat Ann Ratanamahatana, Li Wei, Sang Hee Lee, John Handley
Data mining and knowledge discovery, ISSN 1384-5810, Vol. 14, Nº 1, 2007, págs. 99-129
Experiencing SAX: a novel symbolic representation of time series
Jessica Lin, Eamonn Keogh, Li Wei, Stefano Lonardi
Data mining and knowledge discovery, ISSN 1384-5810, Vol. 15, Nº 2, 2007, págs. 107-144
On the Need for Time Series Data Mining Benchmarks: A Survey and Empirical Demonstration
Shruti Kasetty, Eamonn Keogh
Data mining and knowledge discovery, ISSN 1384-5810, Vol. 7, Nº 4, 2003, págs. 349-371
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