通过地理视觉分析探索运动描述
Exploring Descriptions of Movement Through Geovisual Analytics
摘要：
利用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，我们解决了一个特定类型的信息抽取，即提取相关的运动描述的信息。聚集和理解与文本中指定的运动和缺乏运动的描述相关的信息可以导致对各种类型的运动现象的改进的理解和意义构建，我们介绍GeoMovement，这是一个基于结合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的系统。随着运动的描述，我们的工具可以提取和呈现缺乏运动。很少有现有的工作存在自动提取运动的描述，特别是否定和运动。除了解决这些问题，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GeoMovement的两个系统案例研究，展示了人类如何获得有意义的地理运动信息。GeoMovement可以补充精确的移动数据，例如，使用传感器获得，或在无法获得精确数据时自行使用。
英文摘要：
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.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
