摘要
In this work, we present a self-driving data visualization system, called DeepEye, that automatically generates and recommends visualizations based on the idea of visualization by examples. We propose effective visualization recognition techniques to decide which visualizations are meaningful and visualization ranking techniques to rank the good visualizations. Furthermore, a main challenge of automatic visualization system is that the users may be misled by blindly suggesting visualizations without knowing the user's intent. To this end, we extend DeepEye to be easily steerable by allowing the user to use keyword search and providing click-based faceted navigation. Empirical results, using real-life data and use cases, verify the power of our proposed system.
源语言 | 英语 |
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页(从-至) | 475-490 |
页数 | 16 |
期刊 | IEEE Transactions on Knowledge and Data Engineering |
卷 | 34 |
期 | 1 |
DOI | |
出版状态 | 已出版 - 1 1月 2022 |
已对外发布 | 是 |