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.
翻译:变异器的双向编码器目前是自然语言的最重要和最先进的模型之一,但是,也已经表明,对于特定领域的任务来说,在特定领域对BERT进行预先培训是有帮助的。本文介绍TourBERT,一种经过预先培训的旅游语言模型。我们描述了TourBERT是如何发展和评估的。评价表明,TourBERT在所有具体旅游任务中都比BERT表现得好。