计算机与数字工程2024，Vol.52Issue(10)：3042-3046,5.DOI:10.3969/j.issn.1672-9722.2024.10.033
基于深度学习的地理知识图谱构建方法研究
Research on the Construction Method of Geographic Knowledge Graph Based on BiLSTM-CRF and Bert-BiGRU-Attention Network
摘要
Abstract
Geographic knowledge graph is a key technology to provide geographic knowledge services,and its automatic con-struction is of great significance for developing geographic artificial intelligence applications.In order to address the problem of auto-matic construction of geographic knowledge graph,a method is proposed to construct domain geographic knowledge graph based on BiLSTM-CRF network for extracting geographic entities and Bert-BiGRU-Attention network for extracting orientation relations.The experimental results show that the entities and their orientation information in geographic knowledge graph constructed based on the proposed method are relatively complete with high recall and precision.The method proposed in this paper can meet the require-ments of graph construction and can fully describe the geographic entities and their complex orientation relationships in the real world.关键词
地理知识图谱/BiLSTM-CRF/地理实体/Bert-BiGRU-Attention/方位关系Key words
geographic knowledge graph/BiLSTM-CRF/geographic entities/Bert-BiGRU-Attention/orientation relation-ships分类
信息技术与安全科学引用本文复制引用
任延辉,苗立志,黄毅,汤晟,张朋东..基于深度学习的地理知识图谱构建方法研究[J].计算机与数字工程,2024,52(10):3042-3046,5.基金项目
江苏省"双创博士"项目(编号:CZ032SC20025) （编号:CZ032SC20025）
江苏省智慧健康大数据分析与位置服务工程实验室开放基金项目(编号:SHEL221002)资助. （编号:SHEL221002）
