计算机与数字工程2024，Vol.52Issue(6)：1783-1787,5.DOI:10.3969/j.issn.1672-9722.2024.06.032
电梯安全事故领域命名实体识别研究
Research on Named Entity Recognition of Elevator Safety Accident Domain
摘要
Abstract
Knowledge map technology is an effective solution to solve the problem of multi-source heterogeneous data.It is ap-plied in many fields at present,and named entity recognition is a key step to automatically build the domain knowledge map.Howev-er,there is no related research on named entity recognition in the field of elevator safety accidents.Aiming at the application pur-pose of building the knowledge map of elevator safety accident field,this paper proposes a model based on the combination of BERT pre training model improved for Chinese text segmentation and BiLSTM-CRF to automatically extract entities from unstructured text in the field,and proposes a named entity recognition model suitable for elevator safety accident field.This paper collects and col-lates more than 500 elevator safety accident texts as the experimental corpus data set.Experiments show that compared with the tra-ditional named entity recognition model,the recognition effect of the model used in this paper is significantly improved.关键词
知识图谱/命名实体识别/电梯事故/BERTKey words
knowledge map/named entity recognition/elevator accident/BERT分类
数理科学引用本文复制引用
王鹏飞,谷林..电梯安全事故领域命名实体识别研究[J].计算机与数字工程,2024,52(6):1783-1787,5.
