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Authors: Pierre Dagnely ; Elena Tsiporkova and Tom Tourwé

Affiliation: Sirris, Belgium

ISBN: 978-989-758-275-2

Keyword(s): Event Relevancy Estimation, Data Reduction, Industrial Event Logs, Data Preprocessing.

Related Ontology Subjects/Areas/Topics: Artificial Intelligence ; Bioinformatics ; Biomedical Engineering ; Biomedical Signal Processing ; Data Manipulation ; Data Mining ; Databases and Information Systems Integration ; Enterprise Information Systems ; Health Engineering and Technology Applications ; Human-Computer Interaction ; Industrial Applications of AI ; Methodologies and Methods ; Neurocomputing ; Neurotechnology, Electronics and Informatics ; Pattern Recognition ; Physiological Computing Systems ; Sensor Networks ; Signal Processing ; Soft Computing ; Visualization

Abstract: With the realization of the industrial IoT, more and more industrial assets are continuously monitored by loggers that report events (states, warnings and failures) occurring in or around these devices. Unfortunately, the amount of events in these event logs prevent an efficient exploration, visualization and advanced exploitation of this data. Therefore, a method that could estimate the relevancy of an event is crucial. In this paper, we propose 10 methods, inspired from various research fields, to estimate event relevancy. These methods have been benchmarked on two industrial datasets composed of event logs from two photovoltaic plants. We have demonstrated that a combination of methods can detect irrelevant events (which can correspond to up to 90% of the data). Hence, this is a promising preprocessing step that can help domain experts to explore the logs in a more efficient way and can optimize the performance of analytical methods by reducing the training dataset size wi thout losing information. (More)

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Paper citation in several formats:
Dagnely, P.; Tsiporkova, E. and Tourwé, T. (2018). Data-driven Relevancy Estimation for Event Logs Exploration and Preprocessing.In Proceedings of the 10th International Conference on Agents and Artificial Intelligence - Volume 1: ICAART, ISBN 978-989-758-275-2, pages 395-404. DOI: 10.5220/0006579503950404

@conference{icaart18,
author={Pierre Dagnely. and Elena Tsiporkova. and Tom Tourwé.},
title={Data-driven Relevancy Estimation for Event Logs Exploration and Preprocessing},
booktitle={Proceedings of the 10th International Conference on Agents and Artificial Intelligence - Volume 1: ICAART,},
year={2018},
pages={395-404},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0006579503950404},
isbn={978-989-758-275-2},
}

TY - CONF

JO - Proceedings of the 10th International Conference on Agents and Artificial Intelligence - Volume 1: ICAART,
TI - Data-driven Relevancy Estimation for Event Logs Exploration and Preprocessing
SN - 978-989-758-275-2
AU - Dagnely, P.
AU - Tsiporkova, E.
AU - Tourwé, T.
PY - 2018
SP - 395
EP - 404
DO - 10.5220/0006579503950404

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