VisGuide: User-Oriented Recommendations for Data Event Extraction
Yu-Rong Cao, Xiao-Han Li, Jia-Yu Pan, Wen-Chieh Lin
摘要
Data exploration systems have become popular tools with which data analysts and others can explore raw data and organize their observations. 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 recommendations 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 meaningful data events.
问问这篇 Paper
问问你的智能体。
Lune 读过与它相关的顶会 Paper,每个回答都会注明依据哪几篇。
引用它的顶会 Paper4
- Diverse Interaction Recommendation for Public Users Exploring Multi-view Visualization using Deep LearningYixuan Li, Yusheng Qi, Yang Shi, Qing Chen 等IEEE VIS 2022 · 被引用 34 次
- Socrates: Data Story Generation via Adaptive Machine-Guided Elicitation of User FeedbackGuande Wu, Shunan Guo, Jane Hoffswell, Gromit Yeuk-Yin Chan 等IEEE VIS 2023 · 被引用 14 次
- Data-Semantics-Aware Recommendation of Diverse Pivot TablesWhanhee Cho, Anna FarihaSIGMOD 2026 · 被引用 4 次
- Facilitating Proactive and Reactive Guidance for Decision Making on the Web: A Design Probe with WebSeekYanwei Huang, Arpit NarechaniaCHI 2026 · 被引用 2 次
相关 Paper
- Supporting Guided Exploratory Visual Analysis on Time Series Data with Reinforcement LearningYang Shi, Bingchang Chen, Ying Chen, Zhuochen Jin 等IEEE VIS 2023 · 被引用 8 次
- GenoREC: A Recommendation System for Interactive Genomics Data VisualizationAditeya Pandey, Sehi L'Yi, Qianwen Wang, Michelle A. Borkin 等IEEE VIS 2022 · 被引用 27 次
- Learning to Recommend Visualizations from DataXin Qian, Ryan A. Rossi, Fan Du, Sungchul Kim 等KDD 2021 · 被引用 37 次
- LakeVisage: Towards Scalable, Flexible and Interactive Visualization Recommendation for Data Discovery over Data LakesYihao Hu, Jin Wang, Sajjadur RahmanVLDB 2025 · 被引用 3 次
- A Heuristic Approach for Dual Expert/End-User Evaluation of Guidance in Visual AnalyticsDavide Ceneda, Christopher Collins, Mennatallah El-Assady, Silvia Miksch 等IEEE VIS 2023 · 被引用 9 次
