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Time series motif discovery: dimensions and applications

Wiley interdisciplinary reviews. Data mining and knowledge discovery, 2014-03, Vol.4 (2), p.152-159

Mueen, Abdullah

2014

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Experimental comparison of representation methods and distance measures for time series data

Data mining and knowledge discovery, 2013-03, Vol.26 (2), p.275-309

2013

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The Swiss army knife of time series data mining: ten useful things you can do with the matrix profile and ten lines of code

Data mining and knowledge discovery, 2020-07, Vol.34 (4), p.949-979

2020

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Enumeration of Time Series Motifs of All Lengths

2013 IEEE 13th International Conference on Data Mining, 2013, p.547-556

Mueen, Abdullah

2013

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Efficient unsupervised drift detector for fast and high-dimensional data streams

Knowledge and information systems, 2021-06, Vol.63 (6), p.1497-1527

2021

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MASS: distance profile of a query over a time series

Data mining and knowledge discovery, 2024-05, Vol.38 (3), p.1466-1492

2024

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On the Care and Feeding of Virtual Assistants: Automating Conversation Review with AI

The AI magazine, 2022-01, Vol.42 (4), p.29-42

2022

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On the care and feeding of virtual assistants: Automating conversation review with AI

The AI magazine, 2021-12, Vol.42 (4), p.29-42

2021

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Extracting Optimal Performance from Dynamic Time Warping

Proceedings of the 22nd ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, 2016, p.2129-2130

2016

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The Patient Repository for EEG Data + Computational Tools (PRED+CT)

Frontiers in neuroinformatics, 2017-11, Vol.11, p.67-67

2017

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Matrix Profile IX: Admissible Time Series Motif Discovery With Missing Data

IEEE transactions on knowledge and data engineering, 2021-06, Vol.33 (6), p.2616-2626

2021

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Searching and mining trillions of time series subsequences under dynamic time warping

Proceedings of the 18th ACM SIGKDD international conference on Knowledge discovery and data mining, 2012-08, p.262-270

2012

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Experimental comparison of representation methods and distance measures for time series data

Data mining and knowledge discovery, 2013-03, Vol.26 (2), p.275-309

2013

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Enumeration of time series motifs of all lengths

Knowledge and information systems, 2015-10, Vol.45 (1), p.105-132

2015

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Primitives in time series mining: Algorithms and applications

The Journal of the Acoustical Society of America, 2016-10, Vol.140 (4), p.3378-3378

Mueen, Abdullah A.

2016

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Identify Significant Phenomenon-Specific Variables for Multivariate Time Series

IEEE transactions on knowledge and data engineering, 2021-03, Vol.33 (3), p.1019-1031

2021

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Diminished EEG habituation to novel events effectively classifies Parkinson’s patients

Clinical neurophysiology, 2018-02, Vol.129 (2), p.409-418

2018

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Experimental Comparison and Survey of Twelve Time Series Anomaly Detection Algorithms

The Journal of artificial intelligence research, 2021-01, Vol.72, p.849-899

2021

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Addressing Big Data Time Series: Mining Trillions of Time Series Subsequences Under Dynamic Time Warping

ACM transactions on knowledge discovery from data, 2013-09, Vol.7 (3), p.1-31

2013

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Inferring the Focal Depths of Small Earthquakes in Southern California Using Physics-Based Waveform Features

Bulletin of the Seismological Society of America, 2024-05

2024

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Matrix Profile XXIV: Scaling Time Series Anomaly Detection to Trillions of Datapoints and Ultra-fast Arriving Data Streams

Proceedings of the 28th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2022, p.1173-1182

2022

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DAMP: accurate time series anomaly detection on trillions of datapoints and ultra-fast arriving data streams

Data mining and knowledge discovery, 2023-03, Vol.37 (2), p.627-669

2023

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Combining Filtering and Cross-Correlation Efficiently for Streaming Time Series

ACM transactions on knowledge discovery from data, 2022-10, Vol.16 (5), p.1-24

2022

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Identifying Correlated Bots in Twitter

Social Informatics, p.14-21

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Accelerating the discovery of unsupervised-shapelets

Data mining and knowledge discovery, 2016-01, Vol.30 (1), p.243-281

2016

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Time series motif discovery: dimensions and applications

Experimental comparison of representation methods and distance measures for time series data

The Swiss army knife of time series data mining: ten useful things you can do with the matrix profile and ten lines of code

Enumeration of Time Series Motifs of All Lengths

Efficient unsupervised drift detector for fast and high-dimensional data streams

MASS: distance profile of a query over a time series

On the Care and Feeding of Virtual Assistants: Automating Conversation Review with AI

On the care and feeding of virtual assistants: Automating conversation review with AI

Extracting Optimal Performance from Dynamic Time Warping

The Patient Repository for EEG Data + Computational Tools (PRED+CT)

Matrix Profile IX: Admissible Time Series Motif Discovery With Missing Data

Searching and mining trillions of time series subsequences under dynamic time warping

Experimental comparison of representation methods and distance measures for time series data

Enumeration of time series motifs of all lengths

Primitives in time series mining: Algorithms and applications

Identify Significant Phenomenon-Specific Variables for Multivariate Time Series

Diminished EEG habituation to novel events effectively classifies Parkinson’s patients

Experimental Comparison and Survey of Twelve Time Series Anomaly Detection Algorithms

Addressing Big Data Time Series: Mining Trillions of Time Series Subsequences Under Dynamic Time Warping

Inferring the Focal Depths of Small Earthquakes in Southern California Using Physics-Based Waveform Features

Matrix Profile XXIV: Scaling Time Series Anomaly Detection to Trillions of Datapoints and Ultra-fast Arriving Data Streams

DAMP: accurate time series anomaly detection on trillions of datapoints and ultra-fast arriving data streams

Combining Filtering and Cross-Correlation Efficiently for Streaming Time Series

Identifying Correlated Bots in Twitter

Accelerating the discovery of unsupervised-shapelets

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