The Bidirectional Encoder Representations from Transformers (BERT) is currently one of the most important and state-of-the-art models for natural language. However, it has also been shown that for domain-specific tasks it is helpful to pretrain BERT on a domain-specific corpus. In this paper, we present TourBERT, a pretrained language model for tourism. We describe how TourBERT was developed and evaluated. The evaluations show that TourBERT is outperforming BERT in all tourism-specific tasks.
@article{arxiv.2201.07449,
title = {TourBERT: A pretrained language model for the tourism industry},
author = {Veronika Arefieva and Roman Egger},
journal= {arXiv preprint arXiv:2201.07449},
year = {2022}
}
Comments
Identified a mistake in our calculations. Will fix the problem within the next weeks and resubmit