Demo Data from SIGIR 2026 / reviewers in the wild / expert
Elisabetta Fabrizi
dblp:31/2124
· DBLP profile ↗
1ranked-venue papers
1as first author
0since 2021 · last 2000
—ORCID · none
Domains — the database's venue-derived domains; a paper can count in several
Artificial intelligence and machine learning · 1 · 1 first-authorSystems, architecture and hardware · 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.
| Artificial intelligence
1 paper |
Robot navigation and mapping · 100% |
Topics — the 3 heaviest of 3, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Robotics › Robot navigation and mapping › robot mapping
map representation |
0.0 | 1 | 2000 | Extracting Topology-Based Maps from Gridmaps · ICRA 2000 |
Robotics › Robot navigation and mapping › robot mapping
topological map |
0.0 | 1 | 2000 | Extracting Topology-Based Maps from Gridmaps · ICRA 2000 |
Robotics › Robot navigation and mapping
occupancy grid mapping |
0.0 | 1 | 2000 | Extracting Topology-Based Maps from Gridmaps · ICRA 2000 |
Methods — techniques the papers use, named apart from their topics
image processing · 0.0fuzzy logic · 0.0
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2000 | Extracting Topology-Based Maps from GridmapsabstractWe propose topology-based maps as a new representation of the workspace of a mobile robot. These maps capture the structure of the free space in the environment in terms of the basic topological notions of connectivity and adjacency. Topology-based maps can be automatically extracted from an occupancy grid built from sensor data using techniques borrowed from the image processing field. Since these techniques can be soundly defined on fuzzy values, our approach is well suited to deal with the uncertainty inherent in the sensor data. Topology-based maps are fairly robust with respect to sensor noise and to small environmental changes, and have nice computational properties. Elisabetta Fabrizi, Alessandro Saffiotti |
ICRA | 1 |