loading
Papers Papers/2022 Papers Papers/2022

Research.Publish.Connect.

Paper

Paper Unlock

Authors: Boyan Kolev 1 ; Reza Akbarinia 1 ; Ricardo Jimenez-Peris 2 ; Oleksandra Levchenko 1 ; Florent Masseglia 1 ; Marta Patino 3 and Patrick Valduriez 1

Affiliations: 1 Inria and LIRMM, Montpellier and France ; 2 LeanXcale, Madrid and Spain ; 3 Universidad Politecnica de Madrid (UPM), Madrid and Spain

Keyword(s): Time Series Correlation and Regression, Data Stream Processing, Distributed Computing.

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.

CC BY-NC-ND 4.0

Sign In Guest: Register as new SciTePress user now for free.

Sign In SciTePress user: please login.

PDF ImageMy Papers

You are not signed in, therefore limits apply to your IP address 3.147.47.177

In the current month:
Recent papers: 100 available of 100 total
2+ years older papers: 200 available of 200 total

Paper citation in several formats:
Kolev, B.; Akbarinia, R.; Jimenez-Peris, R.; Levchenko, O.; Masseglia, F.; Patino, M. and Valduriez, P. (2019). Parallel Streaming Implementation of Online Time Series Correlation Discovery on Sliding Windows with Regression Capabilities. In Proceedings of the 9th International Conference on Cloud Computing and Services Science - ADITCA; ISBN 978-989-758-365-0; ISSN 2184-5042, SciTePress, pages 681-687. DOI: 10.5220/0007843806810687

@conference{aditca19,
author={Boyan Kolev. and Reza Akbarinia. and Ricardo Jimenez{-}Peris. and Oleksandra Levchenko. and Florent Masseglia. and Marta Patino. and Patrick Valduriez.},
title={Parallel Streaming Implementation of Online Time Series Correlation Discovery on Sliding Windows with Regression Capabilities},
booktitle={Proceedings of the 9th International Conference on Cloud Computing and Services Science - ADITCA},
year={2019},
pages={681-687},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0007843806810687},
isbn={978-989-758-365-0},
issn={2184-5042},
}

TY - CONF

JO - Proceedings of the 9th International Conference on Cloud Computing and Services Science - ADITCA
TI - Parallel Streaming Implementation of Online Time Series Correlation Discovery on Sliding Windows with Regression Capabilities
SN - 978-989-758-365-0
IS - 2184-5042
AU - Kolev, B.
AU - Akbarinia, R.
AU - Jimenez-Peris, R.
AU - Levchenko, O.
AU - Masseglia, F.
AU - Patino, M.
AU - Valduriez, P.
PY - 2019
SP - 681
EP - 687
DO - 10.5220/0007843806810687
PB - SciTePress

- Science and Technology Publications, Lda.
RESOURCES

Proceedings

Papers

Authors

Ontology

CONTACTS

Science and Technology Publications, Lda
Avenida de S. Francisco Xavier, Lote 7 Cv. C,
2900-616 Setúbal, Portugal.

Phone: +351 265 520 185 (National fixed network call)
Fax: +351 265 520 186
Email: info@scitepress.org

EXTERNAL LINKS

PRIMORIS

INSTICC

SCITEVENTS

CROSSREF

PROCEEDINGS SUBMITTED FOR INDEXATION BY:

dblp

Ei Compendex

SCOPUS

Semantic Scholar

Google Scholar

Microsoft Academic