Roberto Rodríguez UrquiagaReynaldo Alfonte ZapanaAna María Cuadros Valdivia2026-03-222026-03-22201810.1145/3177457.3177466https://doi.org/10.1145/3177457.3177466https://andeanlibrary.org/handle/123456789/66692High-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.enVisual analyticsComputer scienceVisualizationData miningSeries (stratigraphy)Tree (set theory)Dimensionality reductionTime seriesData visualizationSimilarity (geometry)article