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TripAdvisor^{N-D}: A Tourism-Inspired High-Dimensional Space Exploration Framework with Overview and Detail

机译:TripAdvisor ^ {N-D}:一个旅游灵感的高维度空间探索框架,概述和详细

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Gaining a true appreciation of high-dimensional space remains difficult since all of the existing high-dimensional space exploration techniques serialize the space travel in some way. This is not so foreign to us since we, when traveling, also experience the world in a serial fashion. But we typically have access to a map to help with positioning, orientation, navigation, and trip planning. Here, we propose a multivariate data exploration tool that compares high-dimensional space navigation with a sightseeing trip. It decomposes this activity into five major tasks: 1) Identify the sights: use a map to identify the sights of interest and their location; 2) Plan the trip: connect the sights of interest along a specifyable path; 3) Go on the trip: travel along the route; 4) Hop off the bus: experience the location, look around, zoom into detail; and 5) Orient and localize: regain bearings in the map. We describe intuitive and interactive tools for all of these tasks, both global navigation within the map and local exploration of the data distributions. For the latter, we describe a polygonal touchpad interface which enables users to smoothly tilt the projection plane in high-dimensional space to produce multivariate scatterplots that best convey the data relationships under investigation. Motion parallax and illustrative motion trails aid in the perception of these transient patterns. We describe the use of our system within two applications: 1) the exploratory discovery of data configurations that best fit a personal preference in the presence of tradeoffs and 2) interactive cluster analysis via cluster sculpting in N-D.
机译:由于所有现有的高维空间探索技术都以某种方式将空间旅行序列化,因此很难获得对高维空间的真正了解。这对我们来说并不陌生,因为我们在旅行时也会以连续的方式体验世界。但是,我们通常可以访问地图以帮助进行定位,方向,导航和旅行计划。在这里,我们提出了一种多元数据探索工具,该工具将高维空间导航与观光旅行进行了比较。它将该活动分解为五个主要任务:1)识别景点:使用地图识别感兴趣的景点及其位置; 2)计划行程:沿着指定的路线连接名胜古迹; 3)继续旅行:沿着路线旅行; 4)下车:体验位置,环顾四周,放大细节; 5)定位和定位:重新获得地图中的方位。我们描述了用于所有这些任务的直观和交互式工具,包括地图内的全局导航和数据分布的本地浏览。对于后者,我们描述了一个多边形的触摸板界面,该界面使用户可以在高维空间中平滑地倾斜投影平面,以生成可以最好地传达所研究数据关系的多元散点图。运动视差和示例性运动轨迹有助于感知这些瞬态模式。我们在两个应用程序中描述了系统的使用:1)在权衡的情况下探索最适合个人喜好的数据配置的探索性发现; 2)通过N-D中的群集雕刻进行交互式群集分析。

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