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

doi:10.5220/0008977801720181

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

Data Intensive Systems

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Academic › peer-review

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.

Original language	English
Title of host publication	ICAART 2020 - Proceedings of the 12th International Conference on Agents and Artificial Intelligence
Editors	Ana Rocha, Luc Steels, Jaap van den Herik
Publisher	SciTePress
Pages	172-181
Number of pages	10
ISBN (Electronic)	9789897583957
DOIs	https://doi.org/10.5220/0008977801720181
Publication status	Published - 2020
Event	12th International Conference on Agents and Artificial Intelligence, ICAART 2020 - Valletta, Malta Duration: 22 Feb 2020 → 24 Feb 2020

Publication series

Name	ICAART 2020 - Proceedings of the 12th International Conference on Agents and Artificial Intelligence
Volume	2

Conference

Conference	12th International Conference on Agents and Artificial Intelligence, ICAART 2020
Country/Territory	Malta
City	Valletta
Period	22/02/20 → 24/02/20

Bibliographical note

Publisher Copyright:
© 2020 by SCITEPRESS - Science and Technology Publications, Lda. All rights reserved

Keywords

Baggage At-risk Prediction
Baggage Transfer Process Model
Gradient Boosting Machine

Access to Document

10.5220/0008977801720181Licence: CC BY-NC-ND

Cite this

van Leeuwen, H., Zhang, Y., Zervanou, K., Mullick, S., Kaymak, U., & de Ruijter, T. (2020). Lost and found: Predicting airline baggage at-risk of being mishandled. In A. Rocha, L. Steels, & J. van den Herik (Eds.), ICAART 2020 - Proceedings of the 12th International Conference on Agents and Artificial Intelligence (pp. 172-181). (ICAART 2020 - Proceedings of the 12th International Conference on Agents and Artificial Intelligence; Vol. 2). SciTePress. https://doi.org/10.5220/0008977801720181

van Leeuwen, Herbert ; Zhang, Yingqian ; Zervanou, Kalliopi et al. / Lost and found : Predicting airline baggage at-risk of being mishandled. ICAART 2020 - Proceedings of the 12th International Conference on Agents and Artificial Intelligence. editor / Ana Rocha ; Luc Steels ; Jaap van den Herik. SciTePress, 2020. pp. 172-181 (ICAART 2020 - Proceedings of the 12th International Conference on Agents and Artificial Intelligence).

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title = "Lost and found: Predicting airline baggage at-risk of being mishandled",

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.",

keywords = "Baggage At-risk Prediction, Baggage Transfer Process Model, Gradient Boosting Machine",

author = "\{van Leeuwen\}, Herbert and Yingqian Zhang and Kalliopi Zervanou and Shantanu Mullick and Uzay Kaymak and \{de Ruijter\}, Tom",

note = "Publisher Copyright: {\textcopyright} 2020 by SCITEPRESS - Science and Technology Publications, Lda. All rights reserved; 12th International Conference on Agents and Artificial Intelligence, ICAART 2020 ; Conference date: 22-02-2020 Through 24-02-2020",

year = "2020",

doi = "10.5220/0008977801720181",

language = "English",

series = "ICAART 2020 - Proceedings of the 12th International Conference on Agents and Artificial Intelligence",

publisher = "SciTePress",

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}

van Leeuwen, H, Zhang, Y, Zervanou, K, Mullick, S, Kaymak, U & de Ruijter, T 2020, Lost and found: Predicting airline baggage at-risk of being mishandled. in A Rocha, L Steels & J van den Herik (eds), ICAART 2020 - Proceedings of the 12th International Conference on Agents and Artificial Intelligence. ICAART 2020 - Proceedings of the 12th International Conference on Agents and Artificial Intelligence, vol. 2, SciTePress, pp. 172-181, 12th International Conference on Agents and Artificial Intelligence, ICAART 2020, Valletta, Malta, 22/02/20. https://doi.org/10.5220/0008977801720181

Lost and found: Predicting airline baggage at-risk of being mishandled. / van Leeuwen, Herbert; Zhang, Yingqian; Zervanou, Kalliopi et al.
ICAART 2020 - Proceedings of the 12th International Conference on Agents and Artificial Intelligence. ed. / Ana Rocha; Luc Steels; Jaap van den Herik. SciTePress, 2020. p. 172-181 (ICAART 2020 - Proceedings of the 12th International Conference on Agents and Artificial Intelligence; Vol. 2).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Academic › peer-review

TY - GEN

T1 - Lost and found

T2 - 12th International Conference on Agents and Artificial Intelligence, ICAART 2020

AU - van Leeuwen, Herbert

AU - Zhang, Yingqian

AU - Zervanou, Kalliopi

AU - Mullick, Shantanu

AU - Kaymak, Uzay

AU - de Ruijter, Tom

PY - 2020

Y1 - 2020

N2 - 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.

AB - 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.

KW - Baggage At-risk Prediction

KW - Baggage Transfer Process Model

KW - Gradient Boosting Machine

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U2 - 10.5220/0008977801720181

DO - 10.5220/0008977801720181

M3 - Conference contribution

AN - SCOPUS:85083102378

T3 - ICAART 2020 - Proceedings of the 12th International Conference on Agents and Artificial Intelligence

SP - 172

EP - 181

BT - ICAART 2020 - Proceedings of the 12th International Conference on Agents and Artificial Intelligence

A2 - Rocha, Ana

A2 - Steels, Luc

A2 - van den Herik, Jaap

PB - SciTePress

Y2 - 22 February 2020 through 24 February 2020

ER -

van Leeuwen H, Zhang Y, Zervanou K, Mullick S, Kaymak U, de Ruijter T. Lost and found: Predicting airline baggage at-risk of being mishandled. In Rocha A, Steels L, van den Herik J, editors, ICAART 2020 - Proceedings of the 12th International Conference on Agents and Artificial Intelligence. SciTePress. 2020. p. 172-181. (ICAART 2020 - Proceedings of the 12th International Conference on Agents and Artificial Intelligence). doi: 10.5220/0008977801720181

Lost and found: Predicting airline baggage at-risk of being mishandled

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Bibliographical note

Keywords

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