VizML: A Machine Learning Approach to Visualization Recommendation 论文详解
本文发表于CHI 2019. 作者来自MIT Media Lab和MIT CSAIL. 简介与背景 很多可视化工具学习曲线很陡, 往往需要人为指定: 如写代码或各种点击. 然而, 在初步的数据探索以及创建基本可视化的时候, 往往探索的速度与广度比人为指定的定制性更重要. 可视化系统可以利用“数据集的性质会影响它被如何可视化”来支持这些基本需求. 现有的可视化推荐系统分为两类: 基于规则的与基于机器
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