Torwards visual analytics for the exploration of large sets of time series

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Abstract

In this chapter, we discuss the scientific question whether the clustering of time series based on RQA measures leads to an interpretable clustering structure when analyzed by human experts. We are not aware of studies answering this scientific question. Answering it is the crucial first step in the development of a Visual Analytics approach that support users to explore large sets of time series.

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Sips, M., Witt, C., Rawald, T., & Marwan, N. (2016). Torwards visual analytics for the exploration of large sets of time series. In Springer Proceedings in Physics (Vol. 180, pp. 3–17). Springer Science and Business Media, LLC. https://doi.org/10.1007/978-3-319-29922-8_1

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