计算机应用与软件2024，Vol.41Issue(1)：343-349,7.DOI:10.3969/j.issn.1000-386x.2024.01.050
基于BERT位置感知的旅游三元组知识抽取方法
A TRIPLET KNOWLEDGE EXTRACTION METHOD VIA LOCATION-WISE BASED ON BERT IN TOURISM SCENE
摘要
Abstract
The directly-acquired texts often have problems such as weak semantic connection,excessive length,and polysemy.Therefore,this paper proposes a two-stage triplet knowledge extraction method via location-wise based on BERT pre-training.The BERT-Span model was used to achieve entity recognition of tourism through boundary prediction.A relationship extraction model combining positional perception attention and head-tail entity type was constructed based on the character,semantics,location,and entity type characteristics.The experimental results on the Shanxi tourism data set show that the proposed method is superior to benchmark models in the F1 value.关键词
旅游知识图谱/三元组/实体识别/关系抽取/位置感知Key words
Tourism knowledge graph/Triplet/Entity recognition/Relationship extraction/Location-wise分类
信息技术与安全科学引用本文复制引用
张诺,王素格,李大宇..基于BERT位置感知的旅游三元组知识抽取方法[J].计算机应用与软件,2024,41(1):343-349,7.基金项目
山西省重点研发计划项目(201803D421024). （201803D421024）
