EDBT 2026 Demo / reviewers in the wild / expert
Yuya Matsuo
dblp:77/453
· DBLP profile ↗
1ranked-venue papers
1as first author
0since 2021 · last 2002
—ORCID · none
Domains — the database's venue-derived domains; a paper can count in several
Graphics, computer vision, multimedia, augmented reality and games · 1 · 1 first-author
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.
| Databases, data mining, and information retrieval
1 paper |
Data mining · 100% | |
| Computer graphics and multimedia
1 paper |
Multimedia analysis and retrieval · 100% |
Topics — the 2 heaviest of 2, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Data mining
pattern mining |
0.0 | 1 | 2002 | Mining video editing rules in video streams · ACM Multimedia 2002 |
Multimedia analysis and retrieval › video content analysis
video stream analysis |
0.0 | 1 | 2002 | Mining video editing rules in video streams · ACM Multimedia 2002 |
Methods — techniques the papers use, named apart from their topics
data mining · 0.1
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2002 | Mining video editing rules in video streamsabstractData mining is a technique to discover useful patterns or patterns of special interest as explicit knowledge from a vast quantity of data. In video editing, there are a lot of editing patterns. According to the editor's preferences, different editing patterns give the opportunity to achieve a variety of effects. Discovering the editing patterns is required, because it is useful to find each editor's skills and to use them for editing new video material. In this paper, we propose the methods of extracting editing rules from video stream by introducing data mining technique. We can edit a video material by applying the extracted rules. The edited video may produce the same quality as the video from which we extracted the patterns. Yuya Matsuo, Miki Amano, Kuniaki Uehara |
ACM Multimedia | 1 |