BestTime: Finding Representatives in Time Series Datasets

Abstract

Given a set of time series, we aim at finding representatives which best comprehend the recurring temporal patterns contained in the data. We demonstrate BestTime, a Matlab application that uses recurrence quantification analysis to find time series representatives.

@incollection{
year={2014},
isbn={978-3-662-44844-1},
booktitle={Machine Learning and Knowledge Discovery in Databases},
volume={8726},
series={Lecture Notes in Computer Science},
editor={Calders, Toon and Esposito, Floriana and Hüllermeier, Eyke and Meo, Rosa},
doi={10.1007/978-3-662-44845-8_39},
title={BestTime: Finding Representatives in Time Series Datasets},
url={http://dx.doi.org/10.1007/978-3-662-44845-8_39},
publisher={Springer Berlin Heidelberg},
author={Spiegel, Stephan and Schultz, David and Albayrak, Sahin},
pages={477-480},
language={English}
}

Autoren:

Stephan Spiegel, David Schultz, Sahin Albayrak

Kategorie:

Demo Paper

Jahr:

2014

Ort:

ECML-PKDD-14: Lecture Notes in Artificial Intelligence (LNAI) Series, Springer

Link:

http://www.dai-labor.de/~spiegel/besttime.html