地球信息科学学报 ›› 2017, Vol. 19 ›› Issue (6): 723-734.doi: 10.3724/SP.J.1047.2017.00723

• 地球信息科学理论与方法 •    下一篇

论地理知识图谱

陆锋1(), 余丽1,2, 仇培元1   

  1. 1. 中国科学院地理科学与资源研究所 资源与环境信息系统国家重点实验室,北京 100101
    2. 中国科学院文献情报中心, 北京 100190
  • 收稿日期:2017-04-28 修回日期:2017-05-25 出版日期:2017-06-20 发布日期:2017-06-20
  • 作者简介:

    作者简介:陆 锋(1970-),博士,研究员,博士生导师,中国GIS协会理论与方法委员会主任,ACM SIGSpatial China主席,主要从事空间数据模型、空间数据库、空间数据挖掘、知识图谱、导航与位置服务等研究。E-mail: luf@lreis.ac.cn

  • 基金资助:
    国家自然科学重点基金项目(41631177);中国科学院重点部署项目(ZDRW-ZS-2016-6-3)

On Geographic Knowledge Graph

LU Feng1,*(), YU Li1,2, QIU Peiyuan1   

  1. 1. State Key Lab of Resources and Environmental Information System, Institute of Geographic Sciences and Natural Resources Research,Beijing 100101, China
    2. National Science Library, Chinese Academy of Sciences, Beijing 100190, China
  • Received:2017-04-28 Revised:2017-05-25 Online:2017-06-20 Published:2017-06-20
  • Contact: LU Feng E-mail:luf@lreis.ac.cn

摘要:

网络文本蕴含大量隐式地理空间信息,为地理知识获取与知识服务提供了巨大潜能。地理知识图谱是将传统地理信息服务拓展到地理知识服务的关键,也是网络文本蕴含地理信息采集与处理的终极目标。本文系统评述了开放地理语义网、开放地理实体及关系抽取、地理语义网对齐、知识图谱存储方法等地理知识图谱相关主题的研究进展,从网络文本蕴含地理空间信息量与质量评价、地理信息语义理解、空间语义计算模型和异构地理语义网对齐等方面剖析了目前亟需解决的关键科学问题。

关键词: 语义网, 知识图谱, 自然语言理解, 地理信息抽取

Abstract:

Web texts contain a great deal of implicit geospatial information, which provide great potential for the geographic knowledge acquisition and service. Geographic knowledge graph is the key to extend traditional geographic information service to geographic knowledge service, and also the ultimate goal of the collection and processing of implicit geographic information from web texts. This paper systematically reviews the state of the arts of the researches on open geographic semantic web, geographic entity and relation extraction, geographic semantic web alignment, and knowledge graph storage methods. The pressing key scientific issues are also addressed, including the quality evaluation of geospatial information collected from web texts, geographic semantic understanding, spatial semantic computing model, and heterogeneous geographic semantic web alignment.

Key words: Semantic web, Knowledge graph, Natural language processing, Geographic information retrieval