Nearest prototype methods are a successful trend of many pattern classification tasks. However, they present several shortcomings such as time response, noise sensitivity, and Manu...
Knowledge Discovery in time series usually requires symbolic time series. Many discretization methods that convert numeric time series to symbolic time series ignore the temporal ...
Several important time series data mining problems reduce to the core task of finding approximately repeated subsequences in a longer time series. In an earlier work, we formalize...
Bill Yuan-chi Chiu, Eamonn J. Keogh, Stefano Lonar...
Efficiently and accurately searching for similarities among time series and discovering interesting patterns is an important and non-trivial problem. In this paper, we introduce a...
Managing large-scale time series databases has attracted significant attention in the database community recently. Related fundamental problems such as dimensionality reduction, tr...