AviBERT: Transformer-based Aircraft Text Classification AviBERT: Transformer Tabanli Hava Araci Metni Siniflandirma

Date

2025-01-01

Author

Unal, Muhammed Cihat
Yurtalan, Gokhan
Karatas, Yahya Bahadir
Karamanlıoğlu, Alper
Demirel, Berkan

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This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

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In recent years, transformer-based models pre-trained on extensive corpora have played a critical role in the advancement of Natural Language Processing methodologies. Particularly, methods based on BERT have demonstrated remarkable performance across various tasks by offering robust capabilities in deeply understanding texts semantically. However, despite these advancements, there is a notable scarcity of studies applying these technologies in the aviation sector. This paper develops a multi-class classification model for aviation-specific texts using variants of BERT. The study encompasses the processes of collecting web content related to aircraft, labeling and model training. The details of the dataset are explained and the outcomes of the study are assessed based on the macro F1-score and accuracy of different models.

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https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=105015382990&origin=inward
https://hdl.handle.net/11511/115792

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Department of Computer Engineering, Conference / Seminar