Managing large-scale time series databases has attracted significant attention in the database community recently. Related fundamental problems such as dimensionality reduction, tr...
The past decade has seen a wealth of research on time series representations, because the manipulation, storage, and indexing of large volumes of raw time series data is impractica...
Themis Palpanas, Michail Vlachos, Eamonn J. Keogh,...
Most financial time series processes are nonstationary and their frequency characteristics are time-dependant. In this paper we present a time series summarization and prediction ...
This paper describes our work in learning online models that forecast real-valued variables in a high-dimensional space. A 3GB database was collected by sampling 421 real-valued s...
Abstract. Massive data streams of positional updates become increasingly difficult to manage under limited memory resources, especially in terms of providing near real-time respons...
Michalis Potamias, Kostas Patroumpas, Timos K. Sel...