A survey on automatic dashboard recommendation systems

IF 3.8 3区计算机科学 Q2 COMPUTER SCIENCE, INFORMATION SYSTEMS Visual Informatics Pub Date : 2024-03-01 DOI:10.1016/j.visinf.2024.01.002

Praveen Soni , Cyril de Runz , Fatma Bouali , Gilles Venturini

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Abstract

This paper presents a survey on automatic or semi-automatic recommendation systems that help users create dashboards. It starts by showing the important role that dashboards play in data science, and give an informal definition of dashboards, i.e., a set of visualizations possibly with linkage, a screen layout and user feedback. We are mainly interested in systems that use a fully or partially automatic mechanism to recommend dashboards to users. This automation includes the suggestion of data and visualizations, the optimization of the layout and the use of user feedback. We position our work with respect to existing surveys. Starting from a set of over 1000 papers, we have selected and analyzed 19 papers/systems along several dimensions. The main dimensions were the set of considered visualizations, the suggestion method, the utility/objective functions, the layout, and the user interface. We conclude by highlighting the main achievements in this domain and by proposing perspectives.

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仪表盘自动推荐系统调查

本文对帮助用户创建仪表盘的自动或半自动推荐系统进行了调查。本文首先展示了仪表盘在数据科学中扮演的重要角色，并给出了仪表盘的非正式定义，即一组可视化（可能带有链接、屏幕布局和用户反馈）。我们主要关注使用完全或部分自动机制向用户推荐仪表盘的系统。这种自动化包括数据和可视化的建议、布局的优化以及用户反馈的使用。我们将我们的工作定位在现有的调查之上。从 1000 多篇论文开始，我们从多个维度选择并分析了 19 篇论文/系统。主要维度包括所考虑的可视化集合、建议方法、实用/目标功能、布局和用户界面。最后，我们强调了这一领域的主要成就，并提出了展望。

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