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Original paper

A benchmark study on time series clustering

Volume: 1, Pages: 100001 - 100001
Published: Aug 3, 2020
Abstract
This paper presents the first time series clustering benchmark utilizing all time series datasets currently available in the University of California Riverside (UCR) archive — the state of the art repository of time series data. Specifically, the benchmark examines eight popular clustering methods representing three categories of clustering algorithms (partitional, hierarchical and density-based) and three types of distance measures (Euclidean,...
Paper Details
Title
A benchmark study on time series clustering
Published Date
Aug 3, 2020
Volume
1
Pages
100001 - 100001
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