Deepeye: towards automatic data visualization

Yuyu Luo, Xuedi Qin, Nan Tang, Guoliang Li

Research output: Chapter in Book/Report/Conference proceedingConference contribution

12 Citations (Scopus)


Data visualization is invaluable for explaining the significance of data to people who are visually oriented. The central task of automatic data visualization is, given a dataset, to visualize its compelling stories by transforming the data (e.g., selecting attributes, grouping and binning values) and deciding the right type of visualization (e.g., bar or line charts). We present DEEPEYE, a novel system for automatic data visualization that tackles three problems: (1) Visualization recognition: given a visualization, is it 'good or 'bad'? (2) Visualization ranking: given two visualizations, which one is 'better'? And (3) Visualization selection: given a dataset, how to find top-k visualizations? DEEPEYE addresses (1) by training a binary classifier to decide whether a particular visualization is good or bad. It solves (2) from two perspectives: (i) Machine learning: it uses a supervised learning-To-rank model to rank visualizations; and (ii) Expert rules: it relies on experts' knowledge to specify partial orders as rules. Moreover, a 'boring' dataset may become interesting after data transformations (e.g., binning and grouping), which forms a large search space. We also discuss optimizations to efficiently compute top-k visualizations, for approaching (3). Extensive experiments verify the effectiveness of DEEPEYE.

Original languageEnglish
Title of host publicationProceedings - IEEE 34th International Conference on Data Engineering, ICDE 2018
PublisherInstitute of Electrical and Electronics Engineers Inc.
Number of pages12
ISBN (Electronic)9781538655207
Publication statusPublished - 24 Oct 2018
Event34th IEEE International Conference on Data Engineering, ICDE 2018 - Paris, France
Duration: 16 Apr 201819 Apr 2018


Other34th IEEE International Conference on Data Engineering, ICDE 2018



  • Automatic
  • data visualization

ASJC Scopus subject areas

  • Information Systems
  • Information Systems and Management
  • Hardware and Architecture

Cite this

Luo, Y., Qin, X., Tang, N., & Li, G. (2018). Deepeye: towards automatic data visualization. In Proceedings - IEEE 34th International Conference on Data Engineering, ICDE 2018 (pp. 101-112). [8509240] Institute of Electrical and Electronics Engineers Inc..