• 中国计算机学会会刊
  • 中国科技核心期刊
  • 中文核心期刊

计算机工程与科学

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地理信息检索关键技术研究综述

王志宝1,夏昊2,王成波2   

  1. (1.东北石油大学计算机与信息技术学院,黑龙江 大庆 163318;2.中国科学院遥感与数字地球研究所,北京 100101)
  • 收稿日期:2016-06-30 修回日期:2016-11-04 出版日期:2018-03-25 发布日期:2018-03-25

Review of the key techniques of
geographic information retrieval

WANG Zhibao1,XIA Hao2,WANG Chengbo2   

  1. (1.College of Computer and  Information Technology,Northeast Petroleum University,Daqing 163318;
    2.Institute of Remote Sensing and Digital Earth,Chinese Academy of Sciences,Beijing 100101,China)
  • Received:2016-06-30 Revised:2016-11-04 Online:2018-03-25 Published:2018-03-25

摘要:

互联网上大部分的数字化信息都与地球上的地点和位置关联,信息检索查询中大量地包含地理信息,传统的基于关键字匹配方法没有考虑检索中的空间关系,无法满足此类检索需求。地理信息检索根据地理范围从文档中获取空间语义匹配的地理知识文档,成为国内外信息检索和GIS领域的热点研究方向。提出了一个地理信息检索的基本系统框架,依据该框架对地理信息知识库、地理信息抽取、地理信息检索模型、混合索引和检索可视化等关键性技术进行了分类概括总结。在对已有技术进行深入对比分析的基础上,指出了该领域未来的研究工作和面临的挑战,并提供了大量的参考文献。

关键词: 地理信息检索, 地理信息抽取, 混合索引结构, 地理信息检索模型, 地理信息检索可视化

Abstract:

Most of the available digital information is associated with locations or places on the Earth. Although queries submitted to search engines often contain geographic information, the traditional information retrieval methods based on keywords are not effective, as they neglect the spatial relationship in the queries. Geographic information retrieval outputs results by spatial semantic match between queries and documents set, so it becomes a research hotspot in information retrieval and geographic information science. A framework of geographic information retrieval system is proposed, and the key techniques such as geographic knowledge base, geographic information extraction, geographic information retrieval model, hybrid index structure, and visualization of information retrieval are classified and surveyed according to this framework. Based on the comprehensive comparison and analysis of existed researches, some suggestions are presented for future research, and a lot of references are provided.
 

Key words: geographic information retrieval, geographic information extraction, hybrid index structure, geographic information retrieval model, visualization of geographic information retrieval