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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.  ...  While approximate methods exist, they are often inexact, lead to false positives or false dismissals, and do not generalize well to other time series data.  ...  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

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.  ...  Recent work has improved the scalability to the point where exact motifs can be computed on datasets with up to a million data points in tenable time.  ...  Our key observations here are:  The solution to the full exact 1NN time series join can be converted to the exact solution for any definition of time series motif [14] , with only trivial extra effort  ... 
doi:10.1109/icdm.2016.0085 dblp:conf/icdm/ZhuZSYFMBK16 fatcat:am6llbgs4nghnlsi3s3jsyp344

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.  ...  leading to an exact 2-motif discovery algorithm.  ... 
doi:10.1007/978-3-319-07467-2_44 fatcat:x2sst5c7lbh7ncqeahxxiamfl4

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, Gareth Funning, Abdullah Mueen, Philip Brisk, Eamonn Keogh
2017 Knowledge and Information Systems  
Our key observations follow below: • The solution to the full exact 1NN time series join can be converted to the exact solution for any definition of time series motif [19] with only trivial extra effort  ...  Time series motifs are approximately repeated subsequences found within a longer time series.  ...  He is especially interested in scalable algorithms for real-time data.  ... 
doi:10.1007/s10115-017-1138-x fatcat:p6zrlvn5wnfipk6yhi76pir6pu

High performance computing approach for DNA motif discovery

Deepti D. Shrimankar
2019 CSI Transactions on ICT  
Motif discovery has been one of the most widely studied problems in bioinformatics ever since genomic sequences have been available.  ...  strategy and suitable parallel computing paradigms are used.  ...  The current state-of-the-art in exact motif search is qPMS9, the most recent in a series of Planted Motif Search algorithms.  ... 
doi:10.1007/s40012-019-00235-w fatcat:qtctipasz5gchodt6q35p25vra

PMS6MC: A multicore algorithm for motif discovery

Shibdas Bandyopadhyay, Sartaj Sahni, Sanguthevar Rajasekaran
2013 2013 IEEE 3rd International Conference on Computational Advances in Bio and medical Sciences (ICCABS)  
We estimate that PMS6MC is 2 to 4 times faster than other parallel algorithms for motif search on large instances.  ...  PMS6MC is based on PMS6, which is currently the fastest single-core algorithm for motif discovery in large instances.  ...  Since exact algorithms for motif search are compute intensive, it is natural to attempt parallelizations that reduce the observed run time.  ... 
doi:10.1109/iccabs.2013.6629205 dblp:conf/iccabs/BandyopadhyaySR13 fatcat:5zjxxiqcmfddppldy7pangghpq

PMS6MC: A Multicore Algorithm for Motif Discovery

Shibdas Bandyopadhyay, Sartaj Sahni, Sanguthevar Rajasekaran
2013 Algorithms  
We estimate that PMS6MC is 2 to 4 times faster than other parallel algorithms for motif search on large instances.  ...  PMS6MC is based on PMS6, which is currently the fastest single-core algorithm for motif discovery in large instances.  ...  Since exact algorithms for motif search are compute intensive, it is natural to attempt parallelizations that reduce the observed run time.  ... 
doi:10.3390/a6040805 pmid:25309700 pmcid:PMC4193679 fatcat:6hoaivaynnbrhmjrxvwsof2vye

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.  ...  In this article, we propose an innovative standpoint and present a solution coming from it: an anytime multimodal optimization algorithm for time series motif discovery based on particle swarms.  ...  [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

Developing an Efficient Pattern Discovery Method for CPU Utilizations of Computers

Zhuoer Gu, Ligang He, Cheng Chang, Jianhua Sun, Hao Chen, Chenlin Huang
2016 International journal of parallel programming  
Many recently emerging applications running on high performance computing systems rely on motif discovery for various purposes, including efficient task scheduling, energy saving, etc.  ...  In this paper, we propose an efficient motif discovery framework for CPU host load. The framework is elaborately designed to take into account the important properties in host load data.  ...  Many applications rely on motifs discovery in time series data [4] , including (1) the algorithms for mining association rules in time series data based on pattern discovery [5, 17] , (2) classification  ... 
doi:10.1007/s10766-016-0439-0 fatcat:zshqpms3ejdwvbhiwt7x5vywma

Motif discovery algorithms in static and temporal networks: A survey

Ali Jazayeri, Christopher C Yang, Peter Holme
2020 Journal of Complex Networks  
The complexities associated with graph and subgraph isomorphism problems, as the core of frequent subgraph mining, directly impact the performance of motif discovery algorithms.  ...  In this article, we provide a survey of motif discovery algorithms proposed in the literature for mining static and temporal networks and review the corresponding algorithms based on their adopted strategies  ...  In [146] , two parallel strategies are proposed for the parallelization of FANMOD for approximate frequency (sampling-based) and exact frequency motif discovery.  ... 
doi:10.1093/comnet/cnaa031 fatcat:7hasephaffajdl5bn7gl33qn2a

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

A survey of exact motif finding algorithms

Ali Basim Yousif, Hussein Keitan Al-Khafaji, Thekra Abbas
2022 Indonesian Journal of Electrical Engineering and Computer Science  
<span lang="EN-US"><span lang="EN-US">Deoxyribonucleic </span>acid (DNA) motif finding (discovery/mining) in biological chains is the most recent challenging and interesting trend in bioinformatics.  ...  In this paper, we provide a survey of exact DNA motif finding algorithms and their working principles with a suitable comparison among these algorithms to provide an essential step for researchers in this  ...  EXACT DNA MOTIF DISCOVERY ALGORITHMS Mainly, there are two kinds of algorithms for motif discovery; the probabilistic approach and the enumerative approach.  ... 
doi:10.11591/ijeecs.v27.i2.pp1109-1118 fatcat:65uu4r7vnbebbiqjenit26clz4

Motif Discovery Algorithms in Static and Temporal Networks: A Survey [article]

Ali Jazayeri, Christopher C. Yang
2020 arXiv   pre-print
The complexities associated with graph and subgraph isomorphism problems, as the core of frequent subgraph mining, have direct impacts on the performance of motif discovery algorithms.  ...  In this paper, we provide a survey of motif discovery algorithms proposed in the literature for mining static and temporal networks and review the corresponding algorithms based on their adopted strategies  ...  In [127] , two parallel strategies are proposed for the parallelization of FANMOD for approximate frequency (sampling-based) and exact frequency motif discovery.  ... 
arXiv:2005.09721v1 fatcat:m7ytgi2kajcsdoj2cgz2nba6uy

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, Yifei Ding, Hoang Anh Dau, Zachary Zimmerman, Diego Furtado Silva, Abdullah Mueen, Eamonn Keogh
2017 Data mining and knowledge discovery  
We demonstrate the utility of our ideas for many time series data mining problems, including motif discovery, novelty discovery, shapelet discovery, semantic segmentation, density estimation, and contrast  ...  Definition 4 An all-subsequences set A of a time series T is an ordered set of all possible subsequences of T obtained by sliding a window of length m across T : A = {T 1,m, , T 2,m , . . ., T n−m+1,m  ...  A recent paper proposes to speed up discord discovery using Parallel Discord Discovery (PDD), which "divides the discord discovery problem in a combinable manner and solves its subproblems in parallel"  ... 
doi:10.1007/s10618-017-0519-9 fatcat:r6p5lk6td5dvfltcj2vlucnf3q

Discovering Multidimensional Motifs in Physiological Signals for Personalized Healthcare

Arvind Balasubramanian, Jun Wang, Balakrishnan Prabhakaran
2016 IEEE Journal on Selected Topics in Signal Processing  
In this paper, we propose an efficient real-time approach to MDM discovery in body sensor generated time series data for monitoring performance of patients during therapy.  ...  Performance evaluation using synthetic and real body sensor data in unsupervised motif discovery tasks shows that the approach is effective for (a) concurrent processing of multidimensional time series  ...  Unidimensional Motif Discovery For motif discovery in individual dimensions of the multidimensional time series, any stateof-the-art motif discovery technique could be used.  ... 
doi:10.1109/jstsp.2016.2543679 pmid:28191269 pmcid:PMC5298205 fatcat:ux3mrjpevffohka7qowrrw5i7i
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