Parallel Streaming Implementation of Online Time Series Correlation Discovery on Sliding Windows with Regression Capabilities

Boyan Kolev 1 Reza Akbarinia 1 Ricardo Jimenez-Peris 2 Oleksandra Levchenko 1 Florent Masseglia 1 Marta Patino Patrick Valduriez 1
1 ZENITH - Scientific Data Management
LIRMM - Laboratoire d'Informatique de Robotique et de Microélectronique de Montpellier, CRISAM - Inria Sophia Antipolis - Méditerranée
Abstract : This paper addresses the problem of continuously finding highly correlated pairs of time series over the most recent time window and possibly use the discovered correlations to select features for training a regression model for prediction. The implementation builds upon the ParCorr parallel method for online correlation discovery and is designed to run continuously on top of the UPM-CEP data streaming engine through efficient streaming operators.
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https://hal-lirmm.ccsd.cnrs.fr/lirmm-02265729
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Submitted on : Monday, August 12, 2019 - 10:10:41 AM
Last modification on : Friday, September 20, 2019 - 12:50:21 PM

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Boyan Kolev, Reza Akbarinia, Ricardo Jimenez-Peris, Oleksandra Levchenko, Florent Masseglia, et al.. Parallel Streaming Implementation of Online Time Series Correlation Discovery on Sliding Windows with Regression Capabilities. CLOSER: Cloud Computing and Services Science, May 2019, Heraklion, Greece. pp.681-687. ⟨lirmm-02265729⟩

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