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Authors: Fabian Witter ; Timo Klerx and Artus Krohn-Grimberghe

Affiliation: Paderborn University, Germany

ISBN: 978-989-758-222-6

ISSN: 2184-4313

Keyword(s): Statistical Distribution Analysis, Outlier Detection, Deterministic Real-Time Automata, Sequence-based Anomaly Detection, ATM Fraud Detection.

Related Ontology Subjects/Areas/Topics: Applications ; Graphical and Graph-Based Models ; Learning in Process Automation ; Pattern Recognition ; Software Engineering ; Theory and Methods

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.

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Paper citation in several formats:
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, ISSN 2184-4313, pages 351-358. DOI: 10.5220/0006146603510358

@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},
}

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

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