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Time Series Join on Subsequence Correlation

Abdullah Mueen, Hossein Hamooni, Trilce Estrada
2014 2014 IEEE International Conference on Data Mining  
We consider the problem of joining two long time series based on their most correlated segments. Two time series can be joined at any locations and for arbitrary length.  ...  We show three independent uses of time series join on correlation which are made possible by our algorithm.  ...  If we use the content of the time series, we can join on highly correlated subsequences of the two time series.  ... 
doi:10.1109/icdm.2014.52 dblp:conf/icdm/MueenHE14 fatcat:3f3btewqczfuliwzymxhszczti

Temporal Patterns in Bot Activities

Nikan Chavoshi, Hossein Hamooni, Abdullah Mueen
2017 Proceedings of the 26th International Conference on World Wide Web Companion - WWW '17 Companion  
Correlated or synchronized bots commonly exist in social media sites such as Twitter.  ...  In this paper, we perform temporal pattern mining on bot activities in Twitter.  ...  Time Series Join Time Series Join on subsequences identifies segments of two time series that are very similar at an arbitrary lag.  ... 
doi:10.1145/3041021.3051114 dblp:conf/www/ChavoshiHM17a fatcat:eaasl37dkfadfmbycvb73r5u2a

Determining significant connectivity by 4D spatiotemporal wavelet packet resampling of functional neuroimaging data

Rajan S. Patel, Dimitri Van De Ville, F. DuBois Bowman
2006 NeuroImage  
and through each voxel time series, while excluding the specific correlations due to true functional relationships.  ...  When determining whether two brain regions exhibit significant correlation due to true functional connectivity, one must account for the background spatial correlation inherent in neuroimaging data.  ...  Resampling time series. We randomize the specific temporal correlations by performing a 1D wavelet packet resampling for each voxel's time series.  ... 
doi:10.1016/j.neuroimage.2006.01.012 pmid:16546405 fatcat:los5gig3gbhjbnejwv5d2gqhrq

Matrix Profile XII: MPdist: A Novel Time Series Distance Measure to Allow Data Mining in More Challenging Scenarios

Shaghayegh Gharghabi, Shima Imani, Anthony Bagnall, Amirali Darvishzadeh, Eamonn Keogh
2018 2018 IEEE International Conference on Data Mining (ICDM)  
At their core, many time series data mining algorithms can be reduced to reasoning about the shapes of time series subsequences.  ...  The undue faith in these measures derives from an overreliance on benchmark datasets and self-selection bias.  ...  The similarity join set is defined on a set of all possible subsequences of a time series, referred to as the All-Subsequences Set.  ... 
doi:10.1109/icdm.2018.00119 dblp:conf/icdm/GharghabiIBDK18 fatcat:mydnmm52ffd55msepvzfnqgbhi

Page 169 of The Journal of Animal Ecology Vol. 73, Issue 1 [page]

2004 The Journal of Animal Ecology  
In hierarchical clustering, time series are placed in clus- ters by first joining two most similar time series, and then continuing, in a stepwise manner, to join a time series to another time series,  ...  Cross-correlations were calculated after eliminating possible trends in the time series by using  ... 

Robustness and sensitivity analysis of a virtual process chain using the S-rail specimen applying random fields

T. Konrad, S. Wolff, K. Wiegand, M. Merklein
2016 Journal of Physics, Conference Series  
Subsequently computing the eigenvalues of the correlation matrix of nodal coordinate deviations, with the eigenvectors or “scatter shapes” represents their spatial correlation.  ...  Forming and joining process chain of the S-rail specimen in LS-DYNA Additionally to previous investigations, both a laser cutting operation and the subsequent steps of a joining process chain are performed  ... 
doi:10.1088/1742-6596/734/3/032126 fatcat:yyzr7ou52ngmjkymyypkpi42xu

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  
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  ...  With the defined join function, a similarity join set can be generated by applying the similarity join operator on two input all-subsequence sets.  ...  similarity join on the comparison of multiple time series.  ... 
doi:10.1007/s10618-017-0519-9 fatcat:r6p5lk6td5dvfltcj2vlucnf3q

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

Yan Zhu, Shaghayegh Gharghabi, Diego Furtado Silva, Hoang Anh Dau, Chin-Chia Michael Yeh, Nader Shakibay Senobari, Abdulaziz Almaslukh, Kaveh Kamgar, Zachary Zimmerman, Gareth Funning, Abdullah Mueen, Eamonn Keogh
2020 Data mining and knowledge discovery  
The recently introduced data structure, the Matrix Profile, annotates a time series by recording the location of and distance to the nearest neighbor of every subsequence.  ...  This information trivially provides answers to queries for both time series motifs and time series discords, perhaps two of the most frequently used primitives in time series data mining.  ...  We can extract all the subsequences from a given time series by sliding a window of size m across the time series.  ... 
doi:10.1007/s10618-019-00668-6 fatcat:ahq7vze57fgc3kghnnpng5zyla

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.  ...  Time series motifs have been in the literature for about fifteen years, but have only recently begun to receive significant attention in the research community.  ...  The STAMP algorithm computes time series subsequence joins with an efficient anytime algorithm [23] .  ... 
doi:10.1109/icdm.2016.0085 dblp:conf/icdm/ZhuZSYFMBK16 fatcat:am6llbgs4nghnlsi3s3jsyp344

Trend Motif: A Graph Mining Approach for Analysis of Dynamic Complex Networks

Ruoming Jin, Scott McCallen, Eivind Almaas
2007 Seventh IEEE International Conference on Data Mining (ICDM 2007)  
Furthermore, these weights are often not static, instead changing with time and forming a time series.  ...  Hence, to fully understand the dynamics of the complex network, we have to consider both network topology and related time series data.  ...  Intuitively, we consider a trend as a subsequence of a time series that shows a consistent increase or decrease.  ... 
doi:10.1109/icdm.2007.92 dblp:conf/icdm/JinMA07 fatcat:vh7boid5rfamllpicrtigg33oy

Time Series Mining at Petascale Performance [chapter]

Amir Raoofy, Roman Karlstetter, Dai Yang, Carsten Trinitis, Martin Schulz
2020 Lecture Notes in Computer Science  
Finally, we demonstrate our solution on a 128-dimensional time series dataset of 1 million records, solving 274 trillion sorts at a sustained 1.3 Petaflop/s performance on the SuperMUC-NG system. D.  ...  time series with a large dimensionality.  ...  (https://www.gauss-centre.eu) for funding this work by providing computing time on the GCS Supercomputer SuperMUC-NG at Leibniz Supercomputing Centre (LRZ).  ... 
doi:10.1007/978-3-030-50743-5_6 fatcat:y5kkrc5pdrbotin7h7gilqigam

Pointcut Rejuvenation: Recovering Pointcut Expressions in Evolving Aspect-Oriented Software

Raffi Khatchadourian, Phil Greenwood, Awais Rashid, Guoqing Xu
2012 IEEE Transactions on Software Engineering  
The results show that our parameterized heuristic algorithm was able to automatically infer new join points in subsequent versions with an average recall of 0.93.  ...  Moreover, these join points appeared, on average, in the top 4 th percentile of the suggestions, indicating that the results were precise.  ...  Moreover, if such characteristics are shared between program elements corresponding to join points selected by a PCE in one base-code version, it is conceivable that these relationships persist in subsequent  ... 
doi:10.1109/tse.2011.21 fatcat:pmfqvuhavrgjvonffvaadqc4vm

Pointcut Rejuvenation: Recovering Pointcut Expressions in Evolving Aspect-Oriented Software

Raffi Khatchadourian, Phil Greenwood, Awais Rashid, Guoqing Xu
2009 2009 IEEE/ACM International Conference on Automated Software Engineering  
The results show that our parameterized heuristic algorithm was able to automatically infer new join points in subsequent versions with an average recall of 0.93.  ...  Moreover, these join points appeared, on average, in the top 4 th percentile of the suggestions, indicating that the results were precise.  ...  Moreover, if such characteristics are shared between program elements corresponding to join points selected by a PCE in one base-code version, it is conceivable that these relationships persist in subsequent  ... 
doi:10.1109/ase.2009.37 dblp:conf/kbse/KhatchadourianGRX09 fatcat:jeeoxlj3zbgc7pl7jzfhoj4c2u

Scale Invariance in the Nonstationarity of Human Heart Rate

Pedro Bernaola-Galván, Plamen Ch. Ivanov, Luís A. Nunes Amaral, H. Eugene Stanley
2001 Physical Review Letters  
We introduce a segmentation algorithm to probe temporal organization of heterogeneities in human heartbeat interval time series.  ...  This scale-invariant structure is not a simple consequence of the long-range correlations present in the data.  ...  A time series is stationary if the mean, standard deviation, and all higher moments, as well as the correlation functions, are invariant under time translation [1] .  ... 
doi:10.1103/physrevlett.87.168105 pmid:11690251 fatcat:apacrltvpffg7hzqyxqbcnb2r4

Inductive Game Theory and the Dynamics of Animal Conflict

Simon DeDeo, David C. Krakauer, Jessica C. Flack, Christophe Fraser
2010 PLoS Computational Biology  
We develop a technique, Inductive Game Theory, to extract directly from time-series data the decision-making strategies used by individuals and groups.  ...  We find individuals base their decision to fight on memory of social factors, not on short timescale ecological resource competition.  ...  Acknowledgments We thank our three referees for detailed comments on our manuscript. We thank D.  ... 
doi:10.1371/journal.pcbi.1000782 pmid:20485557 pmcid:PMC2869306 fatcat:z2424erf6jesngjavglnj5jfv4
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