Automata-based Explainable Representation for a Complex System of Multivariate Times Series

Ikram Chraibi Kaadoud, Lina Fahed, Tian Tian, Yannis Haralambous, Philippe Lenca

2022

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.

Paper Citation

in Harvard Style

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) - Volume 1: KDIR; ISBN 978-989-758-614-9, SciTePress, pages 170-179. DOI: 10.5220/0011363400003335

in Bibtex Style

@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) - Volume 1: KDIR},
year={2022},
pages={170-179},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0011363400003335},
isbn={978-989-758-614-9},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 14th International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management (IC3K 2022) - Volume 1: KDIR
TI - Automata-based Explainable Representation for a Complex System of Multivariate Times Series
SN - 978-989-758-614-9
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