节点文献

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

  • 推荐 CAJ下载
  • PDF下载
  • 不支持迅雷等下载工具,请取消加速工具后下载。

【作者】 任延辉苗立志黄毅汤晟张朋东

【Author】 REN Yanhui;MIAO Lizhi;HUANG Yi;TANG Sheng;ZHANG Pengdong;School of Geographic and Biologic Information,Nanjing University of Posts and Telecommunications;Smart Health Big Data Analysis and Location Services Engineering Research Center of Jiangsu Province;

【机构】 南京邮电大学地理与生物信息学院江苏省智慧健康大数据分析与位置服务工程研究中心

【摘要】 地理知识图谱是提供地理知识服务的关键技术,实现其自动化构建对发展地理人工智能应用具有非常重要的意义。为解决地理知识图谱自动化构建的问题,提出了一种基于BiLSTM-CRF网络提取地理实体和Bert-BiGRU-Attention网络提取方位关系构建领域地理知识图谱的方法。实验结果表明,基于该方法所自动构建的领域地理知识图谱地理实体及其方位信息较为完整,召回率和精确率较高,能够满足知识图谱构建需求,可充分表达现实世界中地理实体及其复杂的方位关系。

【Abstract】 Geographic knowledge graph is a key technology to provide geographic knowledge services,and its automatic construction is of great significance for developing geographic artificial intelligence applications. In order to address the problem of automatic 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 requirements of graph construction and can fully describe the geographic entities and their complex orientation relationships in the real world.

【基金】 江苏省“双创博士”项目(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
  • 【文献出处】 计算机与数字工程 ,Computer & Digital Engineering , 编辑部邮箱 ,2024年10期
  • 【分类号】P208;TP18;TP391.1
  • 【下载频次】111
节点文献中: 

本文链接的文献网络图示:

本文的引文网络