An Interval Distribution Analysis for RTI+

Fabian Witter, Timo Klerx, Artus Krohn-Grimberghe

2017

Abstract

The algorithm RTI+ learns a Probabilistic Deterministic Real-Time Automaton (PDRTA) from unlabeled timed sequences. RTI+ is an efficient algorithm that runs in polynomial time and can be applied to a variety of real-world behavior identification problems. Nevertheless, we uncover a lack of accuracy in identifying the intervals (or time guards) of the PDRTA. This inaccuracy can lead to wrong predictions of timed sequences in the learned model. We show by example that segments in intervals that are not covered by training data are responsible for this effect. We call those segments gaps and name three types of gaps that can appear. Two of the types cause wrong predictions of sequences and should thus be removed from the model. Therefore, we introduce our novel Interval Distribution Analysis (IDA) which utilizes statistical outlier detection to identify and remove gaps. In the context of ATM fraud detection, we show that IDA can improve the results of RTI+ in a real-world scenario.

Paper Citation

in Harvard Style

Witter F., Klerx T. and Krohn-Grimberghe A. (2017). An Interval Distribution Analysis for RTI+ . In Proceedings of the 6th International Conference on Pattern Recognition Applications and Methods - Volume 1: ICPRAM, ISBN 978-989-758-222-6, pages 351-358. DOI: 10.5220/0006146603510358

in Bibtex Style

@conference{icpram17,
author={Fabian Witter and Timo Klerx and Artus Krohn-Grimberghe},
title={An Interval Distribution Analysis for RTI+},
booktitle={Proceedings of the 6th International Conference on Pattern Recognition Applications and Methods - Volume 1: ICPRAM,},
year={2017},
pages={351-358},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0006146603510358},
isbn={978-989-758-222-6},
}

in EndNote Style

TY - CONF
JO - Proceedings of the 6th International Conference on Pattern Recognition Applications and Methods - Volume 1: ICPRAM,
TI - An Interval Distribution Analysis for RTI+
SN - 978-989-758-222-6
AU - Witter F.
AU - Klerx T.
AU - Krohn-Grimberghe A.
PY - 2017
SP - 351
EP - 358
DO - 10.5220/0006146603510358