高技术通讯2023，Vol.33Issue(11)：1136-1145,10.DOI:10.3772/j.issn.1002-0470.2023.11.002
基于BERT提示的矿产资源管理规则检测方法研究
Research on detection method of mineral resources regulatory rules based on BERT with prompts
摘要
Abstract
Regulatory rules detection in policy text is an emerging natural language processing task,which has important application value for policy conflict detection,policy intelligent retrieval,regulatory compliance inspection,and e-government system requirements engineering.This paper takes the detection of mineral resources regulatory rules as the research goal,and proposes a detection method based on bidirectional encoder representation from transform-ers(BERT)with prompts.By constructing a prompt template with[MASK],which incorporates regulatory rules information,the proposed method can give full play to the auto-encoding advantages of the mask language model,effectively stimulate BERT model to extract text features related to regulatory rules and increase the stability of the model.A new application mode of regulatory rules detection based on BERT model is proposed,which uses the[MASK]hidden vector instead of the[CLS]hidden vector for classification and prediction.The experimental re-sults on the dataset of mineral resources regulatory rules show that the accuracy,macro-average F1 score and weigh-ted-average F1 score of this method are better than the baseline methods.The experimental results on the public dataset also show the effectiveness of the proposed method.关键词
矿产资源/管理规则/文本分类/基于转换器的双向编码表征(BERT)/提示学习Key words
mineral resources/regulatory rule/text classification/bidirectional encoder representation from transformers(BERT)/prompt-based learning引用本文复制引用
胡容波,张广发,王雅雯,方金云..基于BERT提示的矿产资源管理规则检测方法研究[J].高技术通讯,2023,33(11):1136-1145,10.基金项目
北京科技攻关项目(A201908230146)和河北省重点研发计划(20310106D)资助项目. （A201908230146）
