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Visual and Interactive Exploration of a Large Collection of Open Datasets

机译:可视化和交互式探索大量开放数据集

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We deal in this paper with the problem of creating an interactive and visual map for a large collection of Open datasets. We first describe how to define a representation space for such data, using text mining techniques to create features. Then, with a similarity measure between Open datasets, we use the k-nearest neighbors method for building a proximity graph between datasets. We use a force-directed layout method to visualize the graph (Tulip Software). We present the results with a collection of 293,000 datasets from the French Open data web site, in which the display of the graph is limited to 151,000 datasets. We study the discovered clusters and we show how they can be used to browse this large collection.
机译:我们在本文中处理了为大量Open数据集创建交互式可视化地图的问题。我们首先描述如何使用文本挖掘技术创建特征来为此类数据定义表示空间。然后,通过Open数据集之间的相似性度量,我们使用k最近邻居方法在数据集之间建立邻近度图。我们使用力导向的布局方法来可视化图形(郁金香软件)。我们从法国公开赛数据网站上收集了293,000个数据集,展示了结果,其中图表的显示仅限于151,000个数据集。我们研究发现的集群,并展示如何将其用于浏览此大型集合。

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