Yu-Rong Cao, Xiao-Han Li, Jia-Yu Pan, Wen-Chieh Lin
CHI Conference on Human Factors in Computing Systems (CHI).
Article No.: 412, Pages 1–13, April 2022
Abstract
Data exploration systems have become popular tools with which data analysts and others can explore raw data and organize their ob- servations. However, users of such systems who are unfamiliar with their datasets face several challenges when trying to extract data events of interest to them. Those challenges include progressively discovering informative charts, organizing them into a logical order to depict a meaningful fact, and arranging one or more facts to illustrate a data event. To alleviate them, we propose VisGuide—a data exploration system that generates personalized recommenda- tions to aid users’ discovery of data events in breadth and depth by incrementally learning their data exploration preferences and recommending meaningful charts tailored to them. As well as user preferences, VisGuide’s recommendations simultaneously consider sequence organization and chart presentation. We conducted two user studies to evaluate 1) the usability of VisGuide and 2) user satisfaction with its recommendation system. The results of those studies indicate that VisGuide can effectively help users create coherent and user-oriented visualization trees that represent mean- ingful data events.