Exploring Descriptions of Movement Through Geovisual Analytics.
Exploring Descriptions of Movement Through Geovisual Analytics.
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DOI：
10.1007/s42489-022-00098-3
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发表时间：
2022
影响因子：
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通讯作者：
MacEachren AM
中科院分区：
文献类型：
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作者：
Pezanowski S;Mitra P;MacEachren AM
使用从文本中自动提取的信息进行意义建构是一个具有挑战性的问题。在本文中，我们讨论一种特定类型的信息提取，即提取与运动描述相关的信息。聚合和理解与文本中指定的运动描述和缺乏运动相关的信息可以提高对各种类型运动现象的理解和意义，例如人和动物的迁徙、COVID-19导致的旅行障碍等。我们提出了 GeoMovement，这是一个基于机器学习和基于规则的运动相关信息提取与最先进的可视化技术相结合的系统。除了运动的描述之外，我们的工具还可以提取并呈现运动的缺乏。之前很少有关于自动提取运动描述的工作，尤其是否定和运动。除了解决这些问题之外，GeoMovement 还提供了一个新颖的集成框架，用于将这些提取模块与可视化相结合。我们包括两个关于 GeoMovement 的系统案例研究，展示了人类如何获取有意义的地理运动信息。 GeoMovement 可以补充精确的运动数据，例如使用传感器获得的数据，或者在精确数据不可用时单独使用。在线版本包含可在 10.1007/s42489-022-00098-3 获取的补充材料。
Sensemaking using automatically extracted information from text is a challenging problem. In this paper, we address a specific type of information extraction, namely extracting information related to descriptions of movement. Aggregating and understanding information related to descriptions of movement and lack of movement specified in text can lead to an improved understanding and sensemaking of movement phenomena of various types, e.g., migration of people and animals, impediments to travel due to COVID-19, etc. We present GeoMovement, a system that is based on combining machine learning and rule-based extraction of movement-related information with state-of-the-art visualization techniques. Along with the depiction of movement, our tool can extract and present a lack of movement. Very little prior work exists on automatically extracting descriptions of movement, especially negation and movement. Apart from addressing these, GeoMovement also provides a novel integrated framework for combining these extraction modules with visualization. We include two systematic case studies of GeoMovement that show how humans can derive meaningful geographic movement information. GeoMovement can complement precise movement data, e.g., obtained using sensors, or be used by itself when precise data is unavailable. The online version contains supplementary material available at 10.1007/s42489-022-00098-3.