Clustering time series data using the popular subsequence (STS) technique has been widely used in the data mining and wider communities. Recently the conclusion was made that it i...
This paper presents a time series whole clustering system that incrementally constructs a tree-like hierarchy of clusters, using a top-down strategy. The Online Divisive-Agglomera...
The increasing interest in time series data mining has had surprisingly little impact on real world medical applications. Practitioners who work with time series on a daily basis ...
Li Wei, Nitin Kumar, Venkata Nishanth Lolla, Eamon...
Abstract: SumTime-Turbine produces textual summaries of archived timeseries data from gas turbines. These summaries should help experts understand large data sets that cannot be vi...
Jin Yu, Ehud Reiter, Jim Hunter, Somayajulu Sripad...
The segmentation of time-series is a constrained clustering problem: the data points should be grouped by their similarity, but with the constraint that all points in a cluster mus...