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Eamonn Keogh
Eamonn Keogh
Distinguished Professor of Computer Science, University of California - Riverside
Подтвержден адрес электронной почты в домене cs.ucr.edu - Главная страница
Название
Процитировано
Процитировано
Год
Exact indexing of dynamic time warping
E Keogh, CA Ratanamahatana
Knowledge and information systems 7, 358-386, 2005
35962005
A symbolic representation of time series, with implications for streaming algorithms
J Lin, E Keogh, S Lonardi, B Chiu
Proceedings of the 8th ACM SIGMOD workshop on Research issues in data mining …, 2003
28762003
Dimensionality reduction for fast similarity search in large time series databases
E Keogh, K Chakrabarti, M Pazzani, S Mehrotra
Knowledge and information Systems 3, 263-286, 2001
22472001
Experiencing SAX: a novel symbolic representation of time series
J Lin, E Keogh, L Wei, S Lonardi
Data Mining and knowledge discovery 15, 107-144, 2007
21782007
On the need for time series data mining benchmarks: a survey and empirical demonstration
E Keogh, S Kasetty
Proceedings of the eighth ACM SIGKDD international conference on Knowledge …, 2002
19062002
The great time series classification bake off: a review and experimental evaluation of recent algorithmic advances
A Bagnall, J Lines, A Bostrom, J Large, E Keogh
Data mining and knowledge discovery 31, 606-660, 2017
18852017
Querying and mining of time series data: experimental comparison of representations and distance measures
H Ding, G Trajcevski, P Scheuermann, X Wang, E Keogh
Proceedings of the VLDB Endowment 1 (2), 1542-1552, 2008
18472008
An online algorithm for segmenting time series
E Keogh, S Chu, D Hart, M Pazzani
Proceedings 2001 IEEE international conference on data mining, 289-296, 2001
17192001
Time series shapelets: a new primitive for data mining
L Ye, E Keogh
Proceedings of the 15th ACM SIGKDD international conference on Knowledge …, 2009
14132009
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
13662012
Locally adaptive dimensionality reduction for indexing large time series databases
E Keogh, K Chakrabarti, M Pazzani, S Mehrotra
Proceedings of the 2001 ACM SIGMOD international conference on Management of …, 2001
13142001
Hot sax: Efficiently finding the most unusual time series subsequence
E Keogh, J Lin, A Fu
Fifth IEEE International Conference on Data Mining (ICDM'05), 8 pp., 2005
11952005
Scaling up dynamic time warping for datamining applications
EJ Keogh, MJ Pazzani
Proceedings of the sixth ACM SIGKDD international conference on Knowledge …, 2000
11442000
Experimental comparison of representation methods and distance measures for time series data
X Wang, A Mueen, H Ding, G Trajcevski, P Scheuermann, E Keogh
Data Mining and Knowledge Discovery 26, 275-309, 2013
11392013
The UCR time series classification archive
Y Chen, E Keogh, B Hu, N Begum, A Bagnall, A Mueen, G Batista
July, 2015
10642015
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
10372019
Segmenting time series: A survey and novel approach
E Keogh, S Chu, D Hart, M Pazzani
Data mining in time series databases, 1-21, 2004
9602004
Clustering of time-series subsequences is meaningless: implications for previous and future research
E Keogh, J Lin
Knowledge and information systems 8, 154-177, 2005
8902005
Towards parameter-free data mining
E Keogh, S Lonardi, CA Ratanamahatana
Proceedings of the tenth ACM SIGKDD international conference on Knowledge …, 2004
8852004
Matrix profile I: all pairs similarity joins for time series: a unifying view that includes motifs, discords and shapelets
CCM Yeh, Y Zhu, L Ulanova, N Begum, Y Ding, HA Dau, DF Silva, ...
2016 IEEE 16th international conference on data mining (ICDM), 1317-1322, 2016
8652016
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