Demo Data from EDBT 2026 / reviewers in the wild / expert
Sridatt Bhamidipati
dblp:218/8194
· DBLP profile ↗
1ranked-venue papers
0as first author
0since 2021 · last 2018
—ORCID · none
Domains — the database's venue-derived domains; a paper can count in several
Graphics, computer vision, multimedia, augmented reality and games · 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 |
Multimedia analysis and retrieval · 100% | |
| Human-computer interaction and pervasive computing
1 paper |
Collaborative and social computing · 100% |
Topics — the 2 heaviest of 2, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Multimedia analysis and retrieval › multimodal summarization
meeting summarization |
0.3 | 1 | 2018 | MeetingVis: Visual Narratives to Assist in Recalling Meeting Context and Content · IEEE Trans. Vis. Comput. Graph. 2018 |
Collaborative and social computing › groupware
meeting support |
0.3 | 1 | 2018 | MeetingVis: Visual Narratives to Assist in Recalling Meeting Context and Content · IEEE Trans. Vis. Comput. Graph. 2018 |
Methods — techniques the papers use, named apart from their topics
storyline visualization · 0.7audio processing · 0.7
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2018 | MeetingVis: Visual Narratives to Assist in Recalling Meeting Context and ContentabstractIn team-based workplaces, reviewing and reflecting on the content from a previously held meeting can lead to better planning and preparation. However, ineffective meeting summaries can impair this process, especially when participants have difficulty remembering what was said and what its context was. To assist with this process, we introduce MeetingVis, a visual narrative-based approach to meeting summarization. MeetingVis is composed of two primary components: (1) a data pipeline that processes the spoken audio from a group discussion, and (2) a visual-based interface that efficiently displays the summarized content. To design MeetingVis, we create a taxonomy of relevant meeting data points, identifying salient elements to promote recall and reflection. These are mapped to an augmented storyline visualization, which combines the display of participant activities, topic evolutions, and task assignments. For evaluation, we conduct a qualitative user study with five groups. Feedback from the study indicates that MeetingVis effectively triggers the recall of subtle details from prior meetings: all study participants were able to remember new details, points, and tasks compared to an unaided, memory-only baseline. This visual-based approaches can also potentially enhance the productivity of both individuals and the whole team. Yang Shi 0007, Chris Bryan, Sridatt Bhamidipati, Ying Zhao 0001, Yaoxue Zhang, Kwan-Liu Ma |
IEEE Trans. Vis. Comput. Graph. | 3 |