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2020 IEEE International Conference on Big Data (Big Data)
This paper proposes a simple method to extract from a set of multiple related time series a compressed representation for each time series based on statistics for the entire set of all time series. This is achieved by a hierarchical algorithm that first generates an alphabet of shapelets based on the segmentation of centroids for clustered data, before labels of these shapelets are assigned to the segmentation of each single time series via nearest neighbor search using unconstrained dynamicdoi:10.1109/bigdata50022.2020.9377823 fatcat:5rxzvz6zzrdrznryiokgnhseuy