地球信息科学学报 ›› 2018, Vol. 20 ›› Issue (8): 1037-1046.doi: 10.12082/dqxxkx.2018.180094

• 地球信息科学理论与方法 •    下一篇

基于Web文本的灾害事件信息获取进展

韩雪华1,2(), 王卷乐1,5,*(), 卜坤3, 王玉洁1,4   

  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. 中国科学院大学,北京 100049
    3. 中国科学院东北地理与农业生态研究所,长春 130102
    4. 山东理工大学,淄博 255049
    5. 江苏省地理信息资源开发与利用协同创新中心,南京 210023
  • 收稿日期:2018-02-25 修回日期:2018-03-31 出版日期:2018-08-25 发布日期:2018-08-24
  • 通讯作者: 王卷乐 E-mail:hanxh@lreis.ac.cn;wangjl@igsnrr.ac.cn
  • 作者简介:

    作者简介:韩雪华(1992-),女,硕士生,研究方向为数据共享与灾害知识服务。E-mail: hanxh@lreis.ac.cn

  • 基金资助:
    中国工程院防灾减灾知识中心建设项目(CKCEST-2018-2-8);中国科学院战略性先导科技专项(A类)资助(XDA19040501);大数据驱动的资源学科领域创新示范平台(XXH13503-07)

Progress in Information Acquisition of Disaster Events from Web Texts

HAN Xuehua1,2(), WANG Juanle1,5,*(), BU Kun3, WANG Yujie1,4   

  1. 1. State Key Laboratory of Resources and Environmental Information System, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China
    2. University of Chinese Academy of Sciences, Beijing 100049, China
    3. Northeast Institute of Geography and Agroecology, Chinese Academy of Sciences, Changchun 130102, China
    4.Shandong University of Technology, Zibo 255049, China
    5. Jiangsu Center for Collaborative Innovation in Geographical Information Resource Development and Application, Nanjing 210023, China
  • Received:2018-02-25 Revised:2018-03-31 Online:2018-08-25 Published:2018-08-24
  • Contact: WANG Juanle E-mail:hanxh@lreis.ac.cn;wangjl@igsnrr.ac.cn
  • Supported by:
    China Academy of Engineering Disaster Risk Reduction Knowledge Service System, No.CKCEST-2018-2-8;Chinese Academy of Sciences Strategic Pilot Science and Technology Project, No.XDA19040501;Specific Informatization Scientific Research Science Program of the Chinese Academy of Sciences, No.XXH13503-07.

摘要:

大数据时代海量网络文本中蕴含的灾害事件信息是防灾减灾研究和应用的重要资源。从异构的Web文本中快速、准确抽取灾害事件时空信息和属性信息,分析其时空动态变化模式与趋势并进行可视化表达,是当前地理信息与灾害信息领域关注的热点。本文从Web文本挖掘的整体技术框架、灾害主题页面抓取、灾害事件信息解析与抽取、灾害事件信息空间展示分析、以及防灾减灾应用系统等方面调研和综述了相关进展。针对防灾减灾领域的Web文本信息获取未来趋势,分析概括了全流程的Web文本灾害事件信息提取适用技术,并指出未来研究趋势:① 重点开展全球灾害信息全景式获取分析,实现全球灾害事件信息的自动化获取、分析及可视化展示;② 向联合国可持续发展目标(SDGs)和中国“一带一路”倡议,加强典型热点区域的Web灾害事件信息获取分析应用研究并形成示范系统;③ 按照数据、信息、知识的应用层次,建立以大数据挖掘和分析技术支撑的新型防灾减灾知识服务系统。

关键词: 防灾减灾, 灾害事件, Web文本, 信息提取, 时空信息

Abstract:

In this era of big data transfer and use, the extraction of disaster event information from huge quantities of network data is important to facilitate research on disaster prevention and reduction. In comparison with traditional disaster information, disaster information based on Web text is dynamic, heterogeneous, and massive, has space-time aspects, and accesses multiple sources. How to extract and visualize the spatio temporal and attribute information of disaster events from Web text, and track dynamic change patterns and trends of such events over space and time, is a growing area of research in geographic and disaster information systems. This study reviews the progress of relevant researchs including network data mining technology frameworks, disaster theme web page crawling, the extraction of disaster event information, the visualization and spatial distribution characteristics analysis of disaster events and the application system for disaster prevention and reduction. By examining the trend of disaster information acquisition for disaster prevention and reduction from the internet, this study analyzed and summarized the appropriate technologies of information extraction from Web text and discussed the development trends in the following three aspects: (1) Focusing on global disaster information acquisition and analysis. The fundamental trend is to realize the automatic acquisition, analysis, and visualization of global disaster event information to ensure disaster prevention and reduction. (2) To realize the United Nations' 2030 Agenda for Sustainable Development and China's "the Belt and Road" strategy, strengthening of the disaster event information analysis research and its application to typical regions is one of the research hotspots in the field of Web disaster information acquisition and application. (3) Establishing a new disaster prevention and reduction knowledge service system supported by big data mining and analysis technologies according to the application level of data, information, and knowledge will be one of the future research trends.

Key words: disaster prevention reduction, disaster event, Web texts, information extraction, spatio-temporal and attribute information