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Reference TypeJournal Article
Sitemtc-m21c.sid.inpe.br
Holder Codeisadg {BR SPINPE} ibi 8JMKD3MGPCW/3DT298S
Identifier8JMKD3MGP3W34R/3UTSP6H
Repositorysid.inpe.br/mtc-m21c/2020/02.12.09.52   (restricted access)
Last Update2020:06.17.19.01.08 simone
Metadatasid.inpe.br/mtc-m21c/2020/02.12.09.52.01
Metadata Last Update2021:01.04.13.26.34 administrator
DOI10.4018/IJDWM.2020010102
ISSN1548-3924
Citation KeyMonteiroSantFerr:2020:MiPaTr
TitleMining partners in trajectories
Year2020
Monthjan./mar.
Access Date2021, Jan. 20
Type of Workjournal article
Number of Files1
Size2486 KiB
Context area
Author1 Monteiro, Diego Vilela
2 Santos, Rafael Duarte Coelho dos
3 Ferreira, Karine Reis
Resume Identifier1
2 8JMKD3MGP5W/3C9JJ4N
3 8JMKD3MGP5W/3C9JHKN
Group1 CAP-COMP-SESPG-INPE-MCTIC-GOV-BR
2 LABAC-COCTE-INPE-MCTIC-GOV-BR
3 DIDPI-CGOBT-INPE-MCTIC-GOV-BR
Affiliation1 Instituto Nacional de Pesquisas Espaciais (INPE)
2 Instituto Nacional de Pesquisas Espaciais (INPE)
3 Instituto Nacional de Pesquisas Espaciais (INPE)
Author e-Mail Address1
2 rafael.santos@inpe.br
3 karine.ferreira@inpe.br
JournalInternational Journal of Data Warehousing and Mining
Volume16
Number1
Pages22-38
Secondary TypePRE PI
History2020-02-12 09:52:18 :: simone -> administrator :: 2020
2020-02-14 22:51:47 :: administrator -> simone :: 2020
2020-06-17 19:01:08 :: simone -> administrator :: 2020
2021-01-04 13:26:34 :: administrator -> self-uploading-INPE-MCTI-GOV-BR :: 2020
Content and structure area
Is the master or a copy?is the master
Content Stagecompleted
Transferable1
Content TypeExternal Contribution
Version Typepublisher
KeywordsData Mining, Moving Objects, Pattern, R, Trajectory.
AbstractSpatiotemporal data is everywhere, being gathered from different devices such as Earth Observation and GPS satellites, sensor networks and mobile gadgets. Spatiotemporal data collected from moving objects is of particular interest for a broad range of applications. In the last years, such applications have motivated many pieces of research on moving object trajectory data mining. In this article, it is proposed an efficient method to discover partners in moving object trajectories. Such a method identifies pairs of trajectories whose objects stay together during certain periods, based on distance time series analysis. It presents two case studies using the proposed algorithm. This article also describes an R package, called TrajDataMining, that contains algorithms for trajectory data preparation, such as filtering, compressing and clustering, as well as the proposed method Partner.
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Languageen
Target Filemonteiro_data.pdf
User Groupsimone
Reader Groupadministrator
simone
Visibilityshown
Read Permissiondeny from all and allow from 150.163
Update Permissionnot transferred
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Next Higher Units8JMKD3MGPCW/3EQCCU5
8JMKD3MGPCW/3ESGTTP
8JMKD3MGPCW/3F2PHGS
DisseminationPORTALCAPES; SCOPUS.
Host Collectionurlib.net/www/2017/11.22.19.04
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