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

• 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

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.