A visual analytics approach for exploration of high-dimensional time series based on neighbor-joining tree

Descripción del Articulo

High-dimensional time series analysis through visual techniques poses many challenges due to the visualization solutions proposed until now for exploratory tasks are not well-oriented to high volume of data. When the data sets grow large, the visual alternatives do not allow for a good association b...

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Detalles Bibliográficos
Autores: Rodriguez Urquiaga, Roberto, Cuadros Valdivia, Ana María, Alfonte Zapana, Reynaldo
Formato: artículo
Fecha de Publicación:2018
Institución:Universidad La Salle
Repositorio:ULASALLE-Institucional
Lenguaje:inglés
OAI Identifier:oai:repositorio.ulasalle.edu.pe:20.500.12953/25
Enlace del recurso:http://repositorio.ulasalle.edu.pe/handle/20.500.12953/25
Nivel de acceso:acceso restringido
Materia:Research Subject Categories::TECHNOLOGY
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dc.title.es_ES.fl_str_mv A visual analytics approach for exploration of high-dimensional time series based on neighbor-joining tree
title A visual analytics approach for exploration of high-dimensional time series based on neighbor-joining tree
spellingShingle A visual analytics approach for exploration of high-dimensional time series based on neighbor-joining tree
Rodriguez Urquiaga, Roberto
Research Subject Categories::TECHNOLOGY
Research Subject Categories::TECHNOLOGY
title_short A visual analytics approach for exploration of high-dimensional time series based on neighbor-joining tree
title_full A visual analytics approach for exploration of high-dimensional time series based on neighbor-joining tree
title_fullStr A visual analytics approach for exploration of high-dimensional time series based on neighbor-joining tree
title_full_unstemmed A visual analytics approach for exploration of high-dimensional time series based on neighbor-joining tree
title_sort A visual analytics approach for exploration of high-dimensional time series based on neighbor-joining tree
author Rodriguez Urquiaga, Roberto
author_facet Rodriguez Urquiaga, Roberto
Cuadros Valdivia, Ana María
Alfonte Zapana, Reynaldo
author_role author
author2 Cuadros Valdivia, Ana María
Alfonte Zapana, Reynaldo
author2_role author
author
dc.contributor.author.fl_str_mv Rodriguez Urquiaga, Roberto
Cuadros Valdivia, Ana María
Alfonte Zapana, Reynaldo
dc.subject.es_ES.fl_str_mv Research Subject Categories::TECHNOLOGY
topic Research Subject Categories::TECHNOLOGY
Research Subject Categories::TECHNOLOGY
dc.subject.ocde.es_ES.fl_str_mv Research Subject Categories::TECHNOLOGY
description High-dimensional time series analysis through visual techniques poses many challenges due to the visualization solutions proposed until now for exploratory tasks are not well-oriented to high volume of data. When the data sets grow large, the visual alternatives do not allow for a good association between similar time series. With the aim to increase more alternatives, we introduce a visual analytic approach based on Neighbor-Joining similarity tree. The proposed approach internally consists of five time series dimension reduction techniques widely used, two well-known similarity measures and interaction mechanisms to do exploratory analysis of high-dimensional time series data interactively.
publishDate 2018
dc.date.accessioned.none.fl_str_mv 2018-11-21T16:42:45Z
dc.date.available.none.fl_str_mv 2018-11-21T16:42:45Z
dc.date.issued.fl_str_mv 2018-06-21
dc.type.es_ES.fl_str_mv info:eu-repo/semantics/article
format article
dc.identifier.isbn.none.fl_str_mv 978-1-5386-4662-5
dc.identifier.uri.none.fl_str_mv http://repositorio.ulasalle.edu.pe/handle/20.500.12953/25
dc.identifier.journal.es_ES.fl_str_mv 2017 IEEE International Symposium on Signal Processing and Information Technology (ISSPIT)
dc.identifier.doi.es_ES.fl_str_mv 10.1109/ISSPIT.2017.8388663
identifier_str_mv 978-1-5386-4662-5
2017 IEEE International Symposium on Signal Processing and Information Technology (ISSPIT)
10.1109/ISSPIT.2017.8388663
url http://repositorio.ulasalle.edu.pe/handle/20.500.12953/25
dc.language.iso.eng_US.fl_str_mv eng
language eng
dc.relation.es_ES.fl_str_mv info:eu-repo/semantics/article
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dc.format.eng_US.fl_str_mv application/msword
dc.publisher.es_ES.fl_str_mv Universidad La Salle
dc.source.es_ES.fl_str_mv Universidad La Salle
dc.source.none.fl_str_mv reponame:ULASALLE-Institucional
instname:Universidad La Salle
instacron:ULASALLE
instname_str Universidad La Salle
instacron_str ULASALLE
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reponame_str ULASALLE-Institucional
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spelling Rodriguez Urquiaga, RobertoCuadros Valdivia, Ana MaríaAlfonte Zapana, Reynaldo2018-11-21T16:42:45Z2018-11-21T16:42:45Z2018-06-21978-1-5386-4662-5http://repositorio.ulasalle.edu.pe/handle/20.500.12953/252017 IEEE International Symposium on Signal Processing and Information Technology (ISSPIT)10.1109/ISSPIT.2017.8388663High-dimensional time series analysis through visual techniques poses many challenges due to the visualization solutions proposed until now for exploratory tasks are not well-oriented to high volume of data. When the data sets grow large, the visual alternatives do not allow for a good association between similar time series. With the aim to increase more alternatives, we introduce a visual analytic approach based on Neighbor-Joining similarity tree. The proposed approach internally consists of five time series dimension reduction techniques widely used, two well-known similarity measures and interaction mechanisms to do exploratory analysis of high-dimensional time series data interactively.Trabajo de investigaciónDoble ciegoapplication/mswordengUniversidad La Salleinfo:eu-repo/semantics/articleinfo:eu-repo/semantics/restrictedAccessUniversidad La Sallereponame:ULASALLE-Institucionalinstname:Universidad La Salleinstacron:ULASALLEResearch Subject Categories::TECHNOLOGYResearch Subject Categories::TECHNOLOGYA visual analytics approach for exploration of high-dimensional time series based on neighbor-joining treeinfo:eu-repo/semantics/articleORIGINALlink_articulo.txtlink_articulo.txttext/plain45http://repositorio.ulasalle.edu.pe/bitstream/20.500.12953/25/1/link_articulo.txt84e543aff5b998b5b498f5b8eeff87f4MD51LICENSElicense.txtlicense.txttext/plain; charset=utf-81748http://repositorio.ulasalle.edu.pe/bitstream/20.500.12953/25/2/license.txt8a4605be74aa9ea9d79846c1fba20a33MD52TEXTlink_articulo.txt.txtlink_articulo.txt.txtExtracted texttext/plain45http://repositorio.ulasalle.edu.pe/bitstream/20.500.12953/25/3/link_articulo.txt.txt3a604ffac0b5570258ef76234644bf26MD5320.500.12953/25oai:repositorio.ulasalle.edu.pe:20.500.12953/252021-06-11 14:39:34.33Repositorio Institucional de la Universidad La Sallerepositorio@ulasalle.edu.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A visual analytics approach for exploration of high-dimensional time series based on neighbor-joining tree
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