TourBERT: A pretrained language model for the tourism industry
Not on the map. Why?
Abstract (arXiv)
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.
Key facts. Cited by 2 papers in the map (data through 14 Oct 2026). Builds on 8 of its 18 references that are in the map. First posted on arXiv 19 Jan 2022.
Builds on
8 of 18 references.
References · 8
- 2019ALBERT: A Lite BERT for Self-supervised Learning of Language Representationscited by 2,790
- 2019BioBERT: a pre-trained biomedical language representation model for biomedical text miningcited by 1,947
- 2020Don't Stop Pretraining: Adapt Language Models to Domains and Taskscited by 1,565
- 2019SciBERT: A Pretrained Language Model for Scientific Textcited by 1,414
- 2019BERT Rediscovers the Classical NLP Pipelinecited by 1,059
- 2019Publicly Available Clinical BERT Embeddingscited by 1,002
- 2019FinBERT: Financial Sentiment Analysis with Pre-trained Language Modelscited by 385
- 2020Top2Vec: Distributed Representations of Topicscited by 126
Built on by
Citing papers per year: 2023: 1; 2024: 0; 2025: 1.
2 papers.