Demo Data from EDBT 2026 / reviewers in the wild / expert
Tung-Yen Chuang
dblp:239/8042
· DBLP profile ↗
1ranked-venue papers
0as first author
0since 2021 · last 2019
—ORCID · none
Domains — the database's venue-derived domains; a paper can count in several
Human-computer interaction and ubiquitous computing · 1
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% | |
| Human-computer interaction and pervasive computing
1 paper |
Collaborative and social computing · 77% Interaction techniques and input · 23% |
Topics — the 4 heaviest of 4, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Visualization and visual analytics
text visualization |
0.4 | 1 | 2019 | TalkTraces: Real-Time Capture and Visualization of Verbal Content in Meetings · CHI 2019 |
Visualization and visual analytics › text visualization
topic visualization |
0.4 | 1 | 2019 | TalkTraces: Real-Time Capture and Visualization of Verbal Content in Meetings · CHI 2019 |
Collaborative and social computing › groupware
meeting support |
0.4 | 1 | 2019 | TalkTraces: Real-Time Capture and Visualization of Verbal Content in Meetings · CHI 2019 |
Interaction techniques and input
voice interaction |
0.1 | 1 | 2019 | TalkTraces: Real-Time Capture and Visualization of Verbal Content in Meetings · CHI 2019 |
Methods — techniques the papers use, named apart from their topics
word embedding · 0.8topic modeling · 0.8
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2019 | TalkTraces: Real-Time Capture and Visualization of Verbal Content in MeetingsabstractGroup Support Systems provide ways to review and edit shared content during meetings, but typically require participants to explicitly generate the content. Recent advances in speech-to-text conversion and language processing now make it possible to automatically record and review spoken information. We present the iterative design and evaluation of TalkTraces, a real-time visualization that helps teams identify themes in their discussions and obtain a sense of agenda items covered. We use topic modeling to identify themes within the discussions and word embeddings to compute the discussion "relatedness" to items in the meeting agenda. We evaluate TalkTraces iteratively: we first conduct a comparative between-groups study between two teams using TalkTraces and two teams using traditional notes, over four sessions. We translate the findings into changes in the interface, further evaluated by one team over four sessions. Based on our findings, we discuss design implications for real-time displays of discussion content. Senthil K. Chandrasegaran, Chris Bryan, Hidekazu Shidara, Tung-Yen Chuang, Kwan-Liu Ma |
CHI | 4 |