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A Visual Analytics Approach to Exploration of Hotels in Overlaid Drive-Time Polygons of Attractions

机译:一种可视化分析方法,用于探索景点的重叠开车时间多边形中的酒店

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Given multiple attractions to go to, choosing hotels is a Bichromatic Reverser k Nearest Neighbor searching problem. Many efforts have been made to address the problem in the domain of spatial databases. However, most of them suffer from the difficulty of visual selection and comparison. To integrate human intuition into the analysis process and facilitate information communication with users, geospatial visualization techniques have been developed. Unfortunately, too much information on the map, such as hotels and attractions, and drive-time polygons, could overwhelm users. Following the focus+context principle of information visualization, we propose a visual analytics approach to provide users with the flexibility of making their hotel choice. It consists of three main components: an overlap-free and space-efficient clustering algorithm to reduce the searching space for attractions in the map view (MapView), visual comparison of attraction-hotel drive-time in brush-able Small Multiples View (SMView), and the coordination between the two views. We demonstrate the utility of this approach and explain how MapView and SMView can help address the problem.
机译:给定多个景点,选择酒店是一个双色反向器k最近邻搜索问题。为了解决空间数据库领域中的问题,已经做出了许多努力。然而,它们中的大多数遭受视觉选择和比较的困难。为了将人类直觉整合到分析过程中并促进与用户的信息交流,已经开发了地理空间可视化技术。不幸的是,地图上的太多信息,例如酒店和景点以及行车时多边形,可能会使用户不知所措。遵循信息可视化的焦点+上下文原则,我们提出了一种可视化分析方法,以为用户提供做出酒店选择的灵活性。它由三个主要部分组成:无重叠且节省空间的聚类算法,可减少地图视图(MapView)中景点的搜索空间;可刷式小倍数视图(SMView)中景点酒店行驶时间的可视化比较),以及两个视图之间的协调。我们将演示此方法的实用性,并说明MapView和SMView如何帮助解决该问题。

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