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Authors: Ikram Chraibi Kaadoud ; Lina Fahed ; Tian Tian ; Yannis Haralambous and Philippe Lenca

Affiliation: IMT Atlantique, Lab-STICC, UMR CNRS 6285, F-29238 Brest, France

Keyword(s): Multivariate Time Series, Representation, Explainability, Finite-state Automata, Complex System.

Abstract: Complex systems represented by multivariate time series are ubiquitous in many applications, especially in industry. Understanding a complex system, its states and their evolution over time is a challenging task. This is due to the permanent change of contextual events internal and external to the system. We are interested in representing the evolution of a complex system in an intelligible and explainable way based on knowledge extraction. We propose XR-CSB (eXplainable Representation of Complex System Behavior) based on three steps: (i) a time series vertical clustering to detect system states, (ii) an explainable visual representation using unfolded finite-state automata and (iii) an explainable pre-modeling based on an enrichment via exploratory metrics. Four representations adapted to the expertise level of domain experts for acceptability issues are proposed. Experiments show that XR-CSB is scalable. Qualitative evaluation by experts of different expertise levels shows that XR- CSB meets their expectations in terms of explainability, intelligibility and acceptability. (More)

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Paper citation in several formats:
Chraibi Kaadoud, I.; Fahed, L.; Tian, T.; Haralambous, Y. and Lenca, P. (2022). Automata-based Explainable Representation for a Complex System of Multivariate Times Series. In Proceedings of the 14th International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management (IC3K 2022) - KDIR; ISBN 978-989-758-614-9; ISSN 2184-3228, SciTePress, pages 170-179. DOI: 10.5220/0011363400003335

@conference{kdir22,
author={Ikram {Chraibi Kaadoud}. and Lina Fahed. and Tian Tian. and Yannis Haralambous. and Philippe Lenca.},
title={Automata-based Explainable Representation for a Complex System of Multivariate Times Series},
booktitle={Proceedings of the 14th International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management (IC3K 2022) - KDIR},
year={2022},
pages={170-179},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0011363400003335},
isbn={978-989-758-614-9},
issn={2184-3228},
}

TY - CONF

JO - Proceedings of the 14th International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management (IC3K 2022) - KDIR
TI - Automata-based Explainable Representation for a Complex System of Multivariate Times Series
SN - 978-989-758-614-9
IS - 2184-3228
AU - Chraibi Kaadoud, I.
AU - Fahed, L.
AU - Tian, T.
AU - Haralambous, Y.
AU - Lenca, P.
PY - 2022
SP - 170
EP - 179
DO - 10.5220/0011363400003335
PB - SciTePress

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