Eamonn J. Keogh

Most-cited papers

The great time series classification bake off: a review and experimental evaluation of recent algorithmic advances
A. Bagnall, Jason Lines, A. Bostrom, J. Large +1 more
2016Data mining and knowledge discovery1,517 citations Open access
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The UCR time series archive
Dau Anh Hoang, A. Bagnall, Kaveh Kamgar, Chin-Chia Michael Yeh +4 more
2018IEEE/CAA Journal of Automatica Sinica1,198 citations Open access
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Matrix Profile I: All Pairs Similarity Joins for Time Series: A Unifying View That Includes Motifs, Discords and Shapelets
Chin-Chia Michael Yeh, Yan Zhu, Liudmila Ulanova, Nurjahan Begum +5 more
2016Industrial Conference on Data Mining738 citations
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The UEA multivariate time series classification archive, 2018
A. Bagnall, Dau Anh Hoang, Jason Lines, Michael Flynn +4 more
2018arXiv.org666 citations
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Current Time Series Anomaly Detection Benchmarks are Flawed and are Creating the Illusion of Progress
R. Wu, Eamonn J. Keogh
2020IEEE Transactions on Knowledge and Data Engineering371 citations Open access
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Generalizing DTW to the multi-dimensional case requires an adaptive approach
Mohammad Shokoohi-Yekta, Bing Hu, Hong-Xia Jin, Jun Wang +1 more
2016Data mining and knowledge discovery331 citations Open access
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Matrix Profile II: Exploiting a Novel Algorithm and GPUs to Break the One Hundred Million Barrier for Time Series Motifs and Joins
Yan Zhu, Zachary Zimmerman, N. S. Senobari, Chin-Chia Michael Yeh +4 more
2016Industrial Conference on Data Mining267 citations Open access
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Generating Synthetic Time Series to Augment Sparse Datasets
G. Forestier, F. Petitjean, Dau Anh Hoang, Geoffrey I. Webb +1 more
2017Industrial Conference on Data Mining180 citations
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Extracting Optimal Performance from Dynamic Time Warping
A. Mueen, Eamonn J. Keogh
2016Knowledge Discovery and Data Mining180 citations
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Time series joins, motifs, discords and shapelets: a unifying view that exploits the matrix profile
Chin-Chia Michael Yeh, Yan Zhu, Liudmila Ulanova, Nurjahan Begum +6 more
2017Data mining and knowledge discovery144 citations
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MERLIN: Parameter-Free Discovery of Arbitrary Length Anomalies in Massive Time Series Archives
Takaaki Nakamura, Makoto Imamura, Ryan Mercer, Eamonn J. Keogh
2020Industrial Conference on Data Mining126 citations
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Matrix Profile XI: SCRIMP++: Time Series Motif Discovery at Interactive Speeds
Yan Zhu, Chin-Chia Michael Yeh, Zachary Zimmerman, Kaveh Kamgar +1 more
2018Industrial Conference on Data Mining119 citations
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Matrix Profile VIII: Domain Agnostic Online Semantic Segmentation at Superhuman Performance Levels
Shaghayegh Gharghabi, Yifei Ding, Chin-Chia Michael Yeh, Kaveh Kamgar +2 more
2017Industrial Conference on Data Mining119 citations
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Matrix Profile VI: Meaningful Multidimensional Motif Discovery
Chin-Chia Michael Yeh, Nickolas Kavantzas, Eamonn J. Keogh
2017Industrial Conference on Data Mining114 citations
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Optimizing dynamic time warping’s window width for time series data mining applications
Dau Anh Hoang, Diego Furtado Silva, F. Petitjean, G. Forestier +3 more
2018Data mining and knowledge discovery102 citations Open access
Semantic Scholar
Matrix Profile X: VALMOD - Scalable Discovery of Variable-Length Motifs in Data Series
Michele Linardi, Yan Zhu, Themis Palpanas, Eamonn J. Keogh
2018SIGMOD Conference96 citations
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Reliable early classification of time series based on discriminating the classes over time
Usue Mori, A. Mendiburu, Eamonn J. Keogh, J. A. Lozano
2016Data mining and knowledge discovery91 citations
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Speeding up similarity search under dynamic time warping by pruning unpromising alignments
Diego Furtado Silva, Rafael Giusti, Eamonn J. Keogh, Gustavo E. A. P. A. Batista
2018Data mining and knowledge discovery82 citations
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Matrix Profile V: A Generic Technique to Incorporate Domain Knowledge into Motif Discovery
Dau Anh Hoang, Eamonn J. Keogh
2017Knowledge Discovery and Data Mining74 citations
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Matrix profile goes MAD: variable-length motif and discord discovery in data series
Michele Linardi, Yan Zhu, Themis Palpanas, Eamonn J. Keogh
2020Data mining and knowledge discovery73 citations Open access
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Matrix Profile XXIV: Scaling Time Series Anomaly Detection to Trillions of Datapoints and Ultra-fast Arriving Data Streams
Yuelin Lu, R. Wu, A. Mueen, Maria A. Zuluaga +1 more
2022Knowledge Discovery and Data Mining70 citations Open access
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Matrix Profile XIV: Scaling Time Series Motif Discovery with GPUs to Break a Quintillion Pairwise Comparisons a Day and Beyond
Zachary Zimmerman, Kaveh Kamgar, N. S. Senobari, Brian Crites +3 more
2019ACM Symposium on Cloud Computing67 citations Open access
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Domain agnostic online semantic segmentation for multi-dimensional time series
Shaghayegh Gharghabi, Chin-Chia Michael Yeh, Yifei Ding, W. Ding +5 more
2018Data mining and knowledge discovery67 citations Open access
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FastDTW is Approximate and Generally Slower Than the Algorithm it Approximates
R. Wu, Eamonn J. Keogh
2022IEEE Transactions on Knowledge and Data Engineering56 citations Open access
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Matrix Profile XII: MPdist: A Novel Time Series Distance Measure to Allow Data Mining in More Challenging Scenarios
Shaghayegh Gharghabi, Shima Imani, A. Bagnall, Amirali Darvishzadeh +1 more
2018Industrial Conference on Data Mining56 citations
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SiMPle: Assessing Music Similarity Using Subsequences Joins
Diego Furtado Silva, Chin-Chia Michael Yeh, Gustavo E. A. P. A. Batista, Eamonn J. Keogh
2016International Society for Music Information Retrieval Conference53 citations
Semantic Scholar
Time series motifs discovery under DTW allows more robust discovery of conserved structure
S. Alaee, Ryan Mercer, Kaveh Kamgar, Eamonn J. Keogh
2021Data mining and knowledge discovery48 citations
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Parasitic mites alter chicken behaviour and negatively impact animal welfare
A. Murillo, Alireza Abdoli, R. Blatchford, Eamonn J. Keogh +1 more
2020Scientific Reports47 citations Open access
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Matrix Profile XX: Finding and Visualizing Time Series Motifs of All Lengths using the Matrix Profile
Frank Madrid, Shima Imani, Ryan Mercer, Zachary Zimmerman +2 more
2019International Conference on Big Knowledge47 citations
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Matrix Profile VII: Time Series Chains: A New Primitive for Time Series Data Mining (Best Student Paper Award)
Yan Zhu, Makoto Imamura, D. Nikovski, Eamonn J. Keogh
2017Industrial Conference on Data Mining47 citations
Semantic Scholar
Matrix Profile XIII: Time Series Snippets: A New Primitive for Time Series Data Mining
Shima Imani, Frank Madrid, W. Ding, Scott E. Crouter +1 more
2018International Conference on Big Knowledge46 citations
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Exploiting a novel algorithm and GPUs to break the ten quadrillion pairwise comparisons barrier for time series motifs and joins
Yan Zhu, Zachary Zimmerman, Nader Shakibay Senobari, Chin-Chia Michael Yeh +4 more
2017Knowledge and Information Systems39 citations Open access
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Introducing time series chains: a new primitive for time series data mining
Yan Zhu, Makoto Imamura, D. Nikovski, Eamonn J. Keogh
2018Knowledge and Information Systems38 citations
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Super‐Efficient Cross‐Correlation (SEC‐C): A Fast Matched Filtering Code Suitable for Desktop Computers
N. S. Senobari, G. Funning, Eamonn J. Keogh, Yan Zhu +3 more
2018Seismological Research Letters37 citations Open access
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Semi-Supervision Dramatically Improves Time Series Clustering under Dynamic Time Warping
Dau Anh Hoang, Nurjahan Begum, Eamonn J. Keogh
2016International Conference on Information and Knowledge Management36 citations
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Time series classification for varying length series
Chang-Wei Tan, F. Petitjean, Eamonn J. Keogh, Geoffrey I. Webb
2019arXiv.org35 citations
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An ultra-fast time series distance measure to allow data mining in more complex real-world deployments
Shaghayegh Gharghabi, Shima Imani, A. Bagnall, Amirali Darvishzadeh +1 more
2020Data mining and knowledge discovery34 citations
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VALMOD: A Suite for Easy and Exact Detection of Variable Length Motifs in Data Series
Michele Linardi, Yan Zhu, Themis Palpanas, Eamonn J. Keogh
2018SIGMOD Conference34 citations
Semantic Scholar
Matrix Profile XXII: Exact Discovery of Time Series Motifs under DTW
S. Alaee, Kaveh Kamgar, Eamonn J. Keogh
2020Industrial Conference on Data Mining33 citations Open access
Semantic Scholar
Time Series Classification to Improve Poultry Welfare
Alireza Abdoli, A. Murillo, Chin-Chia Michael Yeh, A. Gerry +1 more
2018International Conference on Machine Learning and Applications33 citations Open access
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Matrix Profile III: The Matrix Profile Allows Visualization of Salient Subsequences in Massive Time Series
Chin-Chia Michael Yeh, Helga Van Herle, Eamonn J. Keogh
2016Industrial Conference on Data Mining32 citations
Semantic Scholar
Matrix Profile IV: Using Weakly Labeled Time Series to Predict Outcomes
Chin-Chia Michael Yeh, Nickolas Kavantzas, Eamonn J. Keogh
2017Proceedings of the VLDB Endowment31 citations
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Fast Similarity Matrix Profile for Music Analysis and Exploration
Diego Furtado Silva, Chin-Chia Michael Yeh, Yan Zhu, Gustavo E. A. P. A. Batista +1 more
2019IEEE transactions on multimedia29 citations Open access
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Current Time Series Anomaly Detection Benchmarks are Flawed and are Creating the Illusion of Progress (Extended Abstract)
R. Wu, Eamonn J. Keogh
2022IEEE International Conference on Data Engineering26 citations
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Fitbit for Chickens?: Time Series Data Mining Can Increase the Productivity of Poultry Farms
Alireza Abdoli, S. Alaee, Shima Imani, A. Murillo +3 more
2020Knowledge Discovery and Data Mining24 citations Open access
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Generalized Dynamic Time Warping: Unleashing the Warping Power Hidden in Point-Wise Distances
Rodica Neamtu, Ramoza Ahsan, Elke A. Rundensteiner, G. Sárközy +4 more
2018IEEE International Conference on Data Engineering24 citations
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Judicious setting of Dynamic Time Warping's window width allows more accurate classification of time series
Dau Anh Hoang, Diego Furtado Silva, F. Petitjean, G. Forestier +2 more
20172017 IEEE International Conference on Big Data (Big Data)24 citations Open access
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Matrix Profile IX: Admissible Time Series Motif Discovery With Missing Data
Yan Zhu, A. Mueen, Eamonn J. Keogh
2021IEEE Transactions on Knowledge and Data Engineering23 citations Open access
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When is Early Classification of Time Series Meaningful?
R. Wu, Audrey Der, Eamonn J. Keogh
2021IEEE Transactions on Knowledge and Data Engineering23 citations Open access
Semantic Scholar
DAMP: accurate time series anomaly detection on trillions of datapoints and ultra-fast arriving data streams
Yuelin Lu, R. Wu, A. Mueen, Maria A. Zuluaga +1 more
2023Data mining and knowledge discovery21 citations
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