%0 Journal Article %A GUO Zhendong %A LIN Min %A LI Chengcheng %A ZHAO Jiapeng %T Research on Domain-Specific Word Vector Generation Based on BERT-CRF %D 2022 %R 10.3778/j.issn.1002-8331.2103-0531 %J Computer Engineering and Applications %P 156-162 %V 58 %N 21 %X How to obtain a high-quality domain-specific word vector representation based on the Chinese BERT word vector for various text analysis tasks based on domain word segmentation is an urgent problem to be solved. This paper proposes a domain-specific word vector generation method based on BERT. A BERT-CRF domain-specific word segmenter is established, and the domain text is combined with the domain text to perform fine-tuning and domain word segmentation learning based on the pre-trained BERT word vector. The domain-specific word vector representation is further obtained through the domain-specific word segmentation decoding results. Experiments show that this method can learn a tokenizer model that meets the requirements of the domain task using only a small amount of domain text, and can obtain a higher-quality domain-specific word vector than the original BERT. %U http://cea.ceaj.org/EN/10.3778/j.issn.1002-8331.2103-0531