Steerable Self-Driving Data Visualization

Yuyu Luo, Xuedi Qin, Chengliang Chai*, Nan Tang, Guoliang Li*, Wenbo Li

*此作品的通讯作者

科研成果: 期刊稿件文章同行评审

22 引用 (Scopus)

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
页(从-至)475-490
页数16
期刊IEEE Transactions on Knowledge and Data Engineering
34
1
DOI
出版状态已出版 - 1 1月 2022
已对外发布

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引用此

Luo, Y., Qin, X., Chai, C., Tang, N., Li, G., & Li, W. (2022). Steerable Self-Driving Data Visualization. IEEE Transactions on Knowledge and Data Engineering, 34(1), 475-490. https://doi.org/10.1109/TKDE.2020.2981464