Lost and Found: Predicting Airline Baggage At-risk of Being Mishandled

Herbert van Leeuwen, Yingqian Zhang, Kalliopi Zervanou, Shantanu Mullick, Uzay Kaymak, Tom de Ruijter

2020

Abstract

The number of bags mishandled while transferring to a connecting flight is high. Bags at-risk of missing their connections can be processed faster; however, identifying such bags at-risk is still done by simple business rules. This work researches a general model of baggage transfer process and proposes a Gradient Boosting Machine based prediction model for identifying the bags at-risk. Our prediction model is compared to the current rule based method and a benchmark using logistic regression. The results show that our model offers an increase in accuracy coupled with a marked increase in precision and recall when identifying bags that are transferred unsuccessfully.

Paper Citation

in Harvard Style

van Leeuwen H., Zhang Y., Zervanou K., Mullick S., Kaymak U. and de Ruijter T. (2020). Lost and Found: Predicting Airline Baggage At-risk of Being Mishandled. In Proceedings of the 12th International Conference on Agents and Artificial Intelligence - Volume 2: ICAART, ISBN 978-989-758-395-7, pages 172-181. DOI: 10.5220/0008977801720181

in Bibtex Style

@conference{icaart20,
author={Herbert van Leeuwen and Yingqian Zhang and Kalliopi Zervanou and Shantanu Mullick and Uzay Kaymak and Tom de Ruijter},
title={Lost and Found: Predicting Airline Baggage At-risk of Being Mishandled},
booktitle={Proceedings of the 12th International Conference on Agents and Artificial Intelligence - Volume 2: ICAART,},
year={2020},
pages={172-181},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0008977801720181},
isbn={978-989-758-395-7},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 12th International Conference on Agents and Artificial Intelligence - Volume 2: ICAART,
TI - Lost and Found: Predicting Airline Baggage At-risk of Being Mishandled
SN - 978-989-758-395-7
AU - van Leeuwen H.
AU - Zhang Y.
AU - Zervanou K.
AU - Mullick S.
AU - Kaymak U.
AU - de Ruijter T.
PY - 2020
SP - 172
EP - 181
DO - 10.5220/0008977801720181