Demo Data from EDBT 2026 / reviewers in the wild / expert
Olivier Van Acker
dblp:207/9299
· DBLP profile ↗
1ranked-venue papers
0as first author
1since 2021 · last 2023
—ORCID · none
Domains — the database's venue-derived domains; a paper can count in several
Artificial intelligence and machine learning · 1 · 1 since 2021
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 integration and cleaning · 100% | |
| Theoretical computer science
1 paper |
Graph algorithms and graph theory · 100% |
Topics — the 2 heaviest of 2, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Data integration and cleaning › data generation
synthetic data generation |
0.7 | 1 | 2023 | Synthetic Data Generation of Many-to-Many Datasets via Random Graph Generation · ICLR 2023 |
Graph algorithms and graph theory
random graph generation |
0.7 | 1 | 2023 | Synthetic Data Generation of Many-to-Many Datasets via Random Graph Generation · ICLR 2023 |
Methods — techniques the papers use, named apart from their topics
random graph model · 1.3
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2023 | Synthetic Data Generation of Many-to-Many Datasets via Random Graph Generation
Georgi Ganev, Emile Joubert, Rees Davison, Olivier Van Acker, Luke Robinson |
ICLR | 5 |