Introducing Mplots

Bibliographic Details
Main Author: Shahcheraghi, Maryam
Publication Date: 2024
Other Authors: Mercer, Ryan, Rodrigues, João Manuel de Almeida, Der, Audrey, Gamboa, Hugo Filipe Silveira, Zimmerman, Zachary, Mauck, Kerry, Keogh, Eamonn
Format: Article
Language: eng
Source: Repositórios Científicos de Acesso Aberto de Portugal (RCAAP)
Download full: http://hdl.handle.net/10362/178758
Summary: Funding Information: We gratefully acknowledge funding from Accenture, Mitsubishi Labs and NSF Award 2103976. Publisher Copyright: © The Author(s) 2024.
id RCAP_0790f2a1cf90d39e9c9e70e2b731fbe3
oai_identifier_str oai:run.unl.pt:10362/178758
network_acronym_str RCAP
network_name_str Repositórios Científicos de Acesso Aberto de Portugal (RCAAP)
repository_id_str https://opendoar.ac.uk/repository/7160
spelling Introducing Mplotsscaling time series recurrence plots to massive datasetsAnomaliesSimilarity matrixTime seriesInformation SystemsHardware and ArchitectureComputer Networks and CommunicationsInformation Systems and ManagementFunding Information: We gratefully acknowledge funding from Accenture, Mitsubishi Labs and NSF Award 2103976. Publisher Copyright: © The Author(s) 2024.Time series similarity matrices (informally, recurrence plots or dot-plots), are useful tools for time series data mining. They can be used to guide data exploration, and various useful features can be derived from them and then fed into downstream analytics. However, time series similarity matrices suffer from very poor scalability, taxing both time and memory requirements. In this work, we introduce novel ideas that allow us to scale the largest time series similarity matrices that can be examined by several orders of magnitude. The first idea is a novel algorithm to compute the matrices in a way that removes dependency on the subsequence length. This algorithm is so fast that it allows us to now address datasets where the memory limitations begin to dominate. Our second novel contribution is a multiscale algorithm that computes an approximation of the matrix appropriate for the limitations of the user’s memory/screen-resolution, then performs a local, just-in-time recomputation of any region that the user wishes to zoom-in on. Given that this largely removes time and space barriers, human visual attention then becomes the bottleneck. We further introduce algorithms that search massive matrices with quadrillions of cells and then prioritize regions for later examination by either humans or algorithms. We will demonstrate the utility of our ideas for data exploration, segmentation, and classification in domains as diverse as astronomy, bioinformatics, entomology, and wildlife monitoring.LIBPhys-UNLFaculdade de Ciências e Tecnologia (FCT)RUNShahcheraghi, MaryamMercer, RyanRodrigues, João Manuel de AlmeidaDer, AudreyGamboa, Hugo Filipe SilveiraZimmerman, ZacharyMauck, KerryKeogh, Eamonn2025-02-10T21:17:05Z2024-122024-12-01T00:00:00Zinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articleapplication/pdfhttp://hdl.handle.net/10362/178758eng2196-1115PURE: 106889615https://doi.org/10.1186/s40537-024-00954-1info:eu-repo/semantics/openAccessreponame:Repositórios Científicos de Acesso Aberto de Portugal (RCAAP)instname:FCCN, serviços digitais da FCT – Fundação para a Ciência e a Tecnologiainstacron:RCAAP2025-02-24T01:41:40Zoai:run.unl.pt:10362/178758Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireinfo@rcaap.ptopendoar:https://opendoar.ac.uk/repository/71602025-05-28T20:39:30.430166Repositórios Científicos de Acesso Aberto de Portugal (RCAAP) - FCCN, serviços digitais da FCT – Fundação para a Ciência e a Tecnologiafalse
dc.title.none.fl_str_mv Introducing Mplots
scaling time series recurrence plots to massive datasets
title Introducing Mplots
spellingShingle Introducing Mplots
Shahcheraghi, Maryam
Anomalies
Similarity matrix
Time series
Information Systems
Hardware and Architecture
Computer Networks and Communications
Information Systems and Management
title_short Introducing Mplots
title_full Introducing Mplots
title_fullStr Introducing Mplots
title_full_unstemmed Introducing Mplots
title_sort Introducing Mplots
author Shahcheraghi, Maryam
author_facet Shahcheraghi, Maryam
Mercer, Ryan
Rodrigues, João Manuel de Almeida
Der, Audrey
Gamboa, Hugo Filipe Silveira
Zimmerman, Zachary
Mauck, Kerry
Keogh, Eamonn
author_role author
author2 Mercer, Ryan
Rodrigues, João Manuel de Almeida
Der, Audrey
Gamboa, Hugo Filipe Silveira
Zimmerman, Zachary
Mauck, Kerry
Keogh, Eamonn
author2_role author
author
author
author
author
author
author
dc.contributor.none.fl_str_mv LIBPhys-UNL
Faculdade de Ciências e Tecnologia (FCT)
RUN
dc.contributor.author.fl_str_mv Shahcheraghi, Maryam
Mercer, Ryan
Rodrigues, João Manuel de Almeida
Der, Audrey
Gamboa, Hugo Filipe Silveira
Zimmerman, Zachary
Mauck, Kerry
Keogh, Eamonn
dc.subject.por.fl_str_mv Anomalies
Similarity matrix
Time series
Information Systems
Hardware and Architecture
Computer Networks and Communications
Information Systems and Management
topic Anomalies
Similarity matrix
Time series
Information Systems
Hardware and Architecture
Computer Networks and Communications
Information Systems and Management
description Funding Information: We gratefully acknowledge funding from Accenture, Mitsubishi Labs and NSF Award 2103976. Publisher Copyright: © The Author(s) 2024.
publishDate 2024
dc.date.none.fl_str_mv 2024-12
2024-12-01T00:00:00Z
2025-02-10T21:17:05Z
dc.type.status.fl_str_mv info:eu-repo/semantics/publishedVersion
dc.type.driver.fl_str_mv info:eu-repo/semantics/article
format article
status_str publishedVersion
dc.identifier.uri.fl_str_mv http://hdl.handle.net/10362/178758
url http://hdl.handle.net/10362/178758
dc.language.iso.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv 2196-1115
PURE: 106889615
https://doi.org/10.1186/s40537-024-00954-1
dc.rights.driver.fl_str_mv info:eu-repo/semantics/openAccess
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv application/pdf
dc.source.none.fl_str_mv reponame:Repositórios Científicos de Acesso Aberto de Portugal (RCAAP)
instname:FCCN, serviços digitais da FCT – Fundação para a Ciência e a Tecnologia
instacron:RCAAP
instname_str FCCN, serviços digitais da FCT – Fundação para a Ciência e a Tecnologia
instacron_str RCAAP
institution RCAAP
reponame_str Repositórios Científicos de Acesso Aberto de Portugal (RCAAP)
collection Repositórios Científicos de Acesso Aberto de Portugal (RCAAP)
repository.name.fl_str_mv Repositórios Científicos de Acesso Aberto de Portugal (RCAAP) - FCCN, serviços digitais da FCT – Fundação para a Ciência e a Tecnologia
repository.mail.fl_str_mv info@rcaap.pt
_version_ 1833598778413678592

Similar Items