A visual analytics approach for exploration of high-dimensional time series based on Neighbor-Joining Tree

Roberto Rodríguez; Reynaldo Alfonte; Ana María Cuadros Valdivia

doi:10.1145/3177457.3177466

A visual analytics approach for exploration of high-dimensional time series based on Neighbor-Joining Tree

Roberto Rodríguez, Reynaldo Alfonte, Ana María Cuadros Valdivia

Resultado de la investigación: Capítulo del libro/informe/acta de congreso › Contribución a la conferencia › revisión exhaustiva

Resumen

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 wellknown similarity measures and interaction mechanisms to do exploratory analysis of high-dimensional time series data interactively.

Idioma original	Inglés
Título de la publicación alojada	Proceedings of the 10th International Conference on Computer Modeling and Simulation, ICCMS 2018
Editorial	Association for Computing Machinery
Páginas	44-48
Número de páginas	5
ISBN (versión digital)	9781450363396
DOI	https://doi.org/10.1145/3177457.3177466
Estado	Publicada - 8 ene. 2018
Publicado de forma externa	Sí
Evento	10th International Conference on Computer Modeling and Simulation, ICCMS 2018 - Sydney, Australia Duración: 8 ene. 2018 → 10 ene. 2018

Serie de la publicación

Nombre	ACM International Conference Proceeding Series

Conferencia

Conferencia	10th International Conference on Computer Modeling and Simulation, ICCMS 2018
País/Territorio	Australia
Ciudad	Sydney
Período	8/01/18 → 10/01/18

Nota bibliográfica

Publisher Copyright:
© 2018 Association for Computing Machinery.

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10.1145/3177457.3177466

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Rodríguez, R., Alfonte, R., & Cuadros Valdivia, A. M. (2018). A visual analytics approach for exploration of high-dimensional time series based on Neighbor-Joining Tree. En Proceedings of the 10th International Conference on Computer Modeling and Simulation, ICCMS 2018 (pp. 44-48). (ACM International Conference Proceeding Series). Association for Computing Machinery. https://doi.org/10.1145/3177457.3177466

Rodríguez, Roberto ; Alfonte, Reynaldo ; Cuadros Valdivia, Ana María. / A visual analytics approach for exploration of high-dimensional time series based on Neighbor-Joining Tree. Proceedings of the 10th International Conference on Computer Modeling and Simulation, ICCMS 2018. Association for Computing Machinery, 2018. pp. 44-48 (ACM International Conference Proceeding Series).

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abstract = "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 wellknown similarity measures and interaction mechanisms to do exploratory analysis of high-dimensional time series data interactively.",

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Rodríguez, R, Alfonte, R & Cuadros Valdivia, AM 2018, A visual analytics approach for exploration of high-dimensional time series based on Neighbor-Joining Tree. En Proceedings of the 10th International Conference on Computer Modeling and Simulation, ICCMS 2018. ACM International Conference Proceeding Series, Association for Computing Machinery, pp. 44-48, 10th International Conference on Computer Modeling and Simulation, ICCMS 2018, Sydney, Australia, 8/01/18. https://doi.org/10.1145/3177457.3177466

A visual analytics approach for exploration of high-dimensional time series based on Neighbor-Joining Tree. / Rodríguez, Roberto; Alfonte, Reynaldo; Cuadros Valdivia, Ana María.

Proceedings of the 10th International Conference on Computer Modeling and Simulation, ICCMS 2018. Association for Computing Machinery, 2018. p. 44-48 (ACM International Conference Proceeding Series).

Resultado de la investigación: Capítulo del libro/informe/acta de congreso › Contribución a la conferencia › revisión exhaustiva

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AU - Cuadros Valdivia, Ana María

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Y1 - 2018/1/8

N2 - 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 wellknown similarity measures and interaction mechanisms to do exploratory analysis of high-dimensional time series data interactively.

AB - 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 wellknown similarity measures and interaction mechanisms to do exploratory analysis of high-dimensional time series data interactively.

KW - High dimensional

KW - Neighbor-Joining Tree

KW - Time series

KW - Visual analytics

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M3 - Contribución a la conferencia

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Rodríguez R, Alfonte R, Cuadros Valdivia AM. A visual analytics approach for exploration of high-dimensional time series based on Neighbor-Joining Tree. En Proceedings of the 10th International Conference on Computer Modeling and Simulation, ICCMS 2018. Association for Computing Machinery. 2018. p. 44-48. (ACM International Conference Proceeding Series). doi: 10.1145/3177457.3177466

A visual analytics approach for exploration of high-dimensional time series based on Neighbor-Joining Tree

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