A General Framework for Density Based Time Series Clustering Exploiting a Novel Admissible Pruning Strategy

Time Series Clustering is an important subroutine in many higher-level data mining analyses, including data editing for classifiers, summarization, and outlier detection. It is well known that for similarity search the superiority of Dynamic Time Warping (DTW) over Euclidean distance gradually diminishes as we consider ever larger datasets... (read more)

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