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

机译:覆盖景点覆盖机多边形酒店探索的视觉分析方法

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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 brushable 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:鉴于多次景点去,选择酒店是一位双关权Reverser K最近的邻居搜索问题。已经努力解决空间数据库领域的问题。然而,大多数人都遭受了视觉选择和比较的困难。为了将人类的直觉整合到分析过程中,促进与用户的信息通信,已经开发了地理空间可视化技术。不幸的是,关于地图的太多信息,例如酒店和景点以及开车时间多边形,可能会压倒用户。遵循信息可视化信息的焦点+上下文原则,我们提出了一种视觉分析方法,为用户提供了制定酒店选择的灵活性。它由三个主要组成部分组成:无重叠和空间高效的聚类算法,以减少地图视图中的景点搜索空间(MapView),可绘制的小倍数视图(SMView)中的吸引力 - 酒店开车时间的视觉比较(SMView),和两个观点之间的协调。我们展示了这种方法的效用,并解释了MapView和SMView如何有助于解决问题。

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