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Exact Discovery of Time Series Motifs [chapter]

Abdullah Mueen, Eamonn Keogh, Qiang Zhu, Sydney Cash, Brandon Westover
2009 Proceedings of the 2009 SIAM International Conference on Data Mining  
In this work, for the first time, we show a tractable exact algorithm to find time series motifs.  ...  Time series motifs are pairs of individual time series, or subsequences of a longer time series, which are very similar to each other.  ...  These algorithms can be seen as two-dimensional analogues of time series motif discovery.  ... 
doi:10.1137/1.9781611972795.41 pmid:31656693 pmcid:PMC6814436 dblp:conf/sdm/MueenKZCW09 fatcat:vif6qlq2m5c6bebz7mm5xssxhm

Matrix Profile XXII: Exact Discovery of Time Series Motifs under DTW [article]

Sara Alaee, Kaveh Kamgar, Eamonn Keogh
2020 arXiv   pre-print
In this work, we present the first scalable exact method to discover time series motifs under DTW.  ...  Over the last decade, time series motif discovery has emerged as a useful primitive for many downstream analytical tasks, including clustering, classification, rule discovery, segmentation, and summarization  ...  (one-to-all search). • We introduce SWAMP, the first exact algorithm for DTW motif discovery that significantly outperforms brute force search by two or more orders of magnitude.  ... 
arXiv:2009.07907v1 fatcat:qfg5qyhsqrex3dkt4ecdblxqmi

STUMPY: A Powerful and Scalable Python Library for Time Series Data Mining

Sean Law
2019 Journal of Open Source Software  
The ability to accurately and efficiently compute the exact similarity join would enable, amongst other things, time series motif and time series discord discovery.  ...  However, the simplest and most intuitive approach of comparing all of the pairwise distances between each subsequence within a time series (i.e., a self-similarity join) has not seen much progress due  ...  The ability to accurately and efficiently compute the exact similarity join would enable, amongst other things, time series motif and time series discord discovery.  ... 
doi:10.21105/joss.01504 fatcat:ftxanvcjozc5xnukkymz5dwsc4

Unsupervised discovery of basic human actions from activity recording datasets

Yasser Mohammad, Toyoaki Nishida
2012 2012 IEEE/SICE International Symposium on System Integration (SII)  
This paper proposes the utilization of a novel motif discovery algorithm based on the exact MK algorithm to discover basic actions in activity records.  ...  The proposed system was evaluated on real records of full body motions and is shown in this paper to achieve high accuracy compared with a recently proposed motif discovery algorithm applied to the same  ...  To our best knowledge, this is the first application of an exact motif discovery algorithm to basic action discovery and first extension of it to multiple variable length motif discovery.  ... 
doi:10.1109/sii.2012.6426960 fatcat:4qcrv6tqqnehplkqf3ubblhqsq

Finding K Most Significant Motifs in Big Time Series Data

Zaher Al Aghbari, Ayoub Al-Hamadi
2020 Procedia Computer Science  
An efficient discovery algorithm of frequently occurring patterns, called motifs, in a time series would be useful as a tool for summarizing and visualizing big time series databases.  ...  Abstract An efficient discovery algorithm of frequently occurring patterns, called motifs, in a time series would be useful as a tool for summarizing and visualizing big time series databases.  ...  Finding exact motifs of a time series is quadratic in the number of possible subsequences that can be extracted from a time series, or the quadratic in the length of a single time series from which the  ... 
doi:10.1016/j.procs.2020.03.131 fatcat:ed6alkdsorck7nsgqkihwrebxa

Time Series Motifs Statistical Significance [chapter]

Nuno Castro, Paulo J. Azevedo
2011 Proceedings of the 2011 SIAM International Conference on Data Mining  
Time series motif discovery is the task of extracting previously unknown recurrent patterns from time series data. It is an important problem within applications that range from finance to health.  ...  Our proposal leverages work from the bioinformatics community by using a symbolic definition of time series motifs to derive each motif's p-value.  ...  Among those, exact algorithms [26] have been shown to be a sound contribution to the time series motif discovery problem.  ... 
doi:10.1137/1.9781611972818.59 dblp:conf/sdm/CastroA11 fatcat:l6bgcxtmi5bqfo2sqfxbu4mrfm

Online Discovery of Top-k Similar Motifs in Time Series Data [chapter]

Hoang Thanh Lam, Ninh Dang Pham, Toon Calders
2011 Proceedings of the 2011 SIAM International Conference on Data Mining  
A motif is a pair of non-overlapping sequences with very similar shapes in a time series. We study the online topk most similar motif discovery problem.  ...  We also show possible application of the top-k similar motifs discovery problem.  ...  Keogh for their released datasets, source code and useful discussion in the early stage of the project.  ... 
doi:10.1137/1.9781611972818.86 dblp:conf/sdm/LamCP11 fatcat:5xxoszjqfndjxfvmov6deqvu4u

Scale Invariant Multi-length Motif Discovery [chapter]

Yasser Mohammad, Toyoaki Nishida
2014 Lecture Notes in Computer Science  
Exact motif discovery was later defined as the problem of efficiently finding the most similar pairs of timeseries subsequences and can be used as a basis for discovering ARMs.  ...  Available exact solutions to the problem of finding top K similar subsequence pairs at multiple lengths (which can be the basis of ARM discovery) are not scale invariant.  ...  Evaluation We conducted a series of experiments to evaluate the proposed approach to existing state of the art exact motif discovery algorithms.  ... 
doi:10.1007/978-3-319-07467-2_44 fatcat:x2sst5c7lbh7ncqeahxxiamfl4

Approximate variable-length time series motif discovery using grammar inference

Yuan Li, Jessica Lin
2010 Proceedings of the Tenth International Workshop on Multimedia Data Mining - MDMKDD '10  
In addition, motifs of different lengths may co-exist in a time series dataset.  ...  In this work, we propose a novel approach, based on grammar induction, for approximate variable-length time series motif discovery.  ...  They present motif discovery as the problem of locating regions of high density in the space of all time series subsequences.  ... 
doi:10.1145/1814245.1814255 fatcat:ydvlsaax3vcypbqplrd7w6yaau

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, Nader Shakibay Senobari, Chin-Chia Michael Yeh, Gareth Funning, Abdullah Mueen, Philip Brisk, Eamonn Keogh
2016 2016 IEEE 16th International Conference on Data Mining (ICDM)  
We demonstrate the scalability of our ideas by finding the full set of exact motifs on a dataset with one hundred million subsequences, by far the largest dataset ever mined for time series motifs.  ...  This is perhaps due to the growing realization that they implicitly offer solutions to a host of time series problems, including rule discovery, anomaly detection, density estimation, semantic segmentation  ...  We gratefully acknowledge all the donors of the datasets.  ... 
doi:10.1109/icdm.2016.0085 dblp:conf/icdm/ZhuZSYFMBK16 fatcat:am6llbgs4nghnlsi3s3jsyp344

Efficient Discovery of Variable-length Time Series Motifs with Large Length Range in Million Scale Time Series [article]

Yifeng Gao, Jessica Lin
2018 arXiv   pre-print
We demonstrate that HIME can efficiently detect meaningful variable-length motifs in long, real world time series.  ...  Current state-of-the-art algorithm utilizes fixed-length motif discovery algorithm as a subroutine to enumerate variable-length motifs.  ...  While the algorithm is not an exact algorithm, in the experiments, it can find motifs of lengths from 300 to 3000 in a time series of length one million, with execution time of about 1 minute.  ... 
arXiv:1802.04883v1 fatcat:lz2bqvv7i5hlzezskqfoixbkxy

Significant motifs in time series

Nuno C. Castro, Paulo J. Azevedo
2012 Statistical analysis and data mining  
Time series motif discovery is the task of extracting previously unknown recurrent patterns from time series data. It is an important problem within applications that range from finance to health.  ...  Our proposal leverages work from the bioinformatics community by using a symbolic definition of time series motifs to derive each motif's p-value.  ...  Among those, exact algorithms [9] have been shown to be a sound contribution to the time series motif discovery problem.  ... 
doi:10.1002/sam.11134 fatcat:cy6t5fsalnhvlnntzimaclftya

Particle swarm optimization for time series motif discovery

Joan Serrà, Josep Lluis Arcos
2016 Knowledge-Based Systems  
All these qualities make the presented solution stand out as one of the most prominent candidates for motif discovery in long time series streams.  ...  Efficiently finding similar segments or motifs in time series data is a fundamental task that, due to the ubiquity of these data, is present in a wide range of domains and situations.  ...  In fact, until the work of Mueen et al. [17] , the exact identification of time series motifs was thought to be intractable for even time series of moderate length.  ... 
doi:10.1016/j.knosys.2015.10.021 fatcat:xfwnoy6lrnf2lm2fu5pzbob6s4

Effective and Efficient Variable-Length Data Series Analytics [article]

Michele Linardi
2020 arXiv   pre-print
In this Ph.D. work, we present the first solutions that inherently support scalable and variable-length similarity search in data series, applied to sequence/subsequences matching, motif and discord discovery  ...  In the last twenty years, data series similarity search has emerged as a fundamental operation at the core of several analysis tasks and applications related to data series collections.  ...  Exact Motif and Discord Discovery.  ... 
arXiv:2009.11648v1 fatcat:yh56dcspevcwxjoi4ifixginoa

Visualizing Variable-Length Time Series Motifs [chapter]

Yuan Li, Jessica Lin, Tim Oates
2012 Proceedings of the 2012 SIAM International Conference on Data Mining  
The problem of time series motif discovery has received a lot of attention from researchers in the past decade.  ...  Most existing work on finding time series motifs require that the length of the motifs be known in advance. However, such information is not always available.  ...  This raises the question of whether such precision or exact motif discovery is necessary, or even desirable.  ... 
doi:10.1137/1.9781611972825.77 dblp:conf/sdm/LiLO12 fatcat:briw6g5lrbddder5xyr7wqyn4m
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