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temporal patterns in a corresponding dataset. Although BestTime was originally
designed to analyze vehicular sensor data [
32
], our extended version [
36
] can be
used to find representatives in arbitrary sets of single- or multi-dimensional time
series of variable length.
Worthwhile future work includes (1) the investigation of RQA measures which
quantify recurring patterns with uniform scaling, (2) the application of speed-up
techniques for RP computations, and (3) the formalization/analysis of a RP-based
distance metric.
Acknowledgments
The proposed recurrence plot-based distance measure for clustering multivari-
ate time series was developed in cooperation with the Volkswagen AG, Wolfsburg. Thanks to Bernd
Werther and Matthias Pries (from the Volkswagen AG) for their contribution of expert knowledge
and their help in recording vehicular sensor data. The presented BestTime applicationwas developed
in cooperation with David Schultz at DAI-Labor.
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