Data-driven Relevancy Estimation for Event Logs Exploration and Preprocessing

Pierre Dagnely, Elena Tsiporkova, Tom Tourwé

2018

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 without losing information.

Paper Citation

in Harvard Style

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 2: ICAART, ISBN 978-989-758-275-2, pages 395-404. DOI: 10.5220/0006579503950404

in Bibtex Style

@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 2: ICAART,},
year={2018},
pages={395-404},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0006579503950404},
isbn={978-989-758-275-2},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 10th International Conference on Agents and Artificial Intelligence - Volume 2: 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