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

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.

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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