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TSSEARCH

2022-06Artigo científico Acesso aberto
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dc.contributor.authorFolgado, Duarte
dc.contributor.authorBarandas, Marília
dc.contributor.authorAntunes, Margarida
dc.contributor.authorNunes, Maria Lua
dc.contributor.authorLiu, Hui
dc.contributor.authorHartmann, Yale
dc.contributor.authorSchultz, Tanja
dc.contributor.authorGamboa, Hugo
dc.contributor.institutionLIBPhys-UNL
dc.contributor.pblElsevier BV
dc.date.accessioned2022-08-26T22:17:22Z
dc.date.available2022-08-26T22:17:22Z
dc.date.issued2022-06
dc.description
dc.description.abstractSubsequence search and distance measures are crucial tools in time series data mining. This paper presents our Python package entitled TSSEARCH, which provides a comprehensive set of methods for subsequence search and similarity measurement in time series. These methods are user-customizable for more flexibility and efficient integration into real deployment scenarios. TSSEARCH enables fast exploratory time series data analysis and was validated in the context of human activity recognition and indoor localization.en
dc.description.versionpublishersversion
dc.description.versionpublished
dc.format.extent5
dc.format.extent550399
dc.identifier.doi10.1016/j.softx.2022.101049
dc.identifier.issn2352-7110
dc.identifier.otherPURE: 45154650
dc.identifier.otherPURE UUID: 6c4ef2ee-625c-416f-9452-e50eab58f806
dc.identifier.otherWOS: 000786596600001
dc.identifier.otherScopus: 85127238013
dc.identifier.otherORCID: /0000-0002-4022-7424/work/117952332
dc.identifier.urihttp://hdl.handle.net/10362/143322
dc.language.isoeng
dc.peerreviewedyes
dc.relationinfo:eu-repo/grantAgreement/EC/H2020/646858/EU
dc.relationVolcano dome growth, collapse and coupled processes
dc.subjectTime series
dc.subjectSubsequence search
dc.subjectDistances
dc.subjectSimilarity measurements
dc.subjectQuery-based search
dc.subjectSegmentation
dc.subjectPython package
dc.titleTSSEARCHen
dc.title.subtitleTime Series Subsequence Search Libraryen
dc.typejournal article
degois.publication.firstPage1
degois.publication.lastPage5
degois.publication.titleSoftwareX
degois.publication.volume18
dspace.entity.typePublication
oaire.awardNumber646858
oaire.awardTitleVolcano dome growth, collapse and coupled processes
oaire.awardURIinfo:eu-repo/grantAgreement/EC/H2020/646858/EU
oaire.fundingStreamH2020
project.funder.identifierhttp://doi.org/10.13039/501100008530
project.funder.nameEuropean Commission
rcaap.rightsopenAccess
relation.isProjectOfPublication85b57087-8103-4986-b36f-5437b4b1116e
relation.isProjectOfPublication.latestForDiscovery85b57087-8103-4986-b36f-5437b4b1116e

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