Demo Data from EDBT 2026 / reviewers in the wild / expert
Yu-Rong Cao
dblp:264/8088
· DBLP profile ↗
1ranked-venue papers
1as first author
1since 2021 · last 2022
—ORCID · none
Domains — the database's venue-derived domains; a paper can count in several
Human-computer interaction and ubiquitous computing · 1 · 1 first-author · 1 since 2021
Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.
| Computer graphics and multimedia
1 paper |
Visualization and visual analytics · 100% | |
| Databases, data mining, and information retrieval
1 paper |
Data mining · 100% |
Topics — the 1 heaviest of 2, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Visualization and visual analytics
data exploration |
0.6 | 1 | 2022 | VisGuide: User-Oriented Recommendations for Data Event Extraction · CHI 2022 |
Methods — techniques the papers use, named apart from their topics
recommender system · 1.1preference learning · 1.1
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2022 | VisGuide: User-Oriented Recommendations for Data Event ExtractionabstractData 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. Yu-Rong Cao, Xiao-Han Li, Jia-Yu Pan, Wen-Chieh Lin |
CHI | 1 |