Demo Data from EDBT 2026 / reviewers in the wild / expert
Loïc Fricoteaux
dblp:27/10370
· DBLP profile ↗
2ranked-venue papers
2as first author
0since 2021 · last 2014
—ORCID · none
Domains — the database's venue-derived domains; a paper can count in several
Artificial intelligence and machine learning · 1 · 1 first-authorGraphics, computer vision, multimedia, augmented reality and games · 1 · 1 first-authorHuman-computer interaction and ubiquitous computing · 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.
| Human-computer interaction and pervasive computing
1 paper |
Learning and educational technologies · 100% | |
| Computer graphics and multimedia
1 paper |
Virtual and augmented reality · 100% |
Topics — the 2 heaviest of 3, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Virtual and augmented reality › virtual environment
immersive virtual environments |
0.0 | 1 | 2013 | OSE: An adaptive user interface for fluvial navigation training · VR 2013 |
Virtual and augmented reality › virtual environment
virtual training environments |
0.0 | 1 | 2013 | OSE: An adaptive user interface for fluvial navigation training · VR 2013 |
Methods — techniques the papers use, named apart from their topics
visualization metaphors · 0.3decision making module · 0.3
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2014 | GULLIVER: A decision-making system based on user observation for an adaptive training in informed virtual environments
Loïc Fricoteaux, Indira Thouvenin, Daniel Mestre |
Eng. Appl. Artif. Intell. | 1 |
| 2013 | OSE: An adaptive user interface for fluvial navigation trainingabstractAs training systems are often designed for procedural task learning, we propose an adaptive training system (OSE) in this context to explore how informed interaction supported by a decision making module (GULLIVER) contributes to adaptive knowledge acquisition in a virtual environment. Visualization metaphors and audio messages are displayed as feedback to guide the learner, which is essential to this training. First results show that our system provides an adaptive guiding which is efficient for beginners. Though we focus on fluvial navigation training, the results may be relevant to other applications. Loïc Fricoteaux, Indira Thouvenin |
VR | 1 |