Hierarchical Multilabel Classification for Fine-Level Event Extraction from Aviation Accident Reports
Published Online:17 Oct 2024https://doi.org/10.1287/ijds.2022.0032
- Cited by
- Engineering Applications of Artificial Intelligence, Vol. 173
- 27 May 2026 | PLOS One, Vol. 21, No. 5
- 7 December 2025 | Electronics, Vol. 14, No. 24
- 12 August 2025 | Applied Sciences, Vol. 15, No. 16
- Expert Systems with Applications, Vol. 257
Volume 4, Issue 1
January-March 2025
Pages 1-99, C2
Article Information
Supplemental Material
Metrics
Information
- Received:November 04, 2022
- Accepted:March 07, 2024
- Published Online:October 17, 2024
Copyright © 2024, INFORMS
Cite as
Xinyu Zhao; , Hao Yan; , Yongming Liu (2024) Hierarchical Multilabel Classification for Fine-Level Event Extraction from Aviation Accident Reports. INFORMS Journal on Data Science 4(1):51-66.
https://doi.org/10.1287/ijds.2022.0032
Keywords
The authors thank two experts in aviation accident report and safety analysis: Dan Larson, an aviation analyst from Metron Aviation, and Xue Ping, a computational linguist from Boeing (retired). They have worked with the team in supervising the research development and helping the team understand the current National Transportation Safety Board coding system.
