Demo Data from EDBT 2026 / reviewers in the wild / expert
Aidan Shafran
dblp:178/8726
· DBLP profile ↗
1ranked-venue papers
1as first author
0since 2021 · last 2016
—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-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 |
Knowledge representation and reasoning · 100% |
Topics — the 2 heaviest of 2, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Knowledge, reasoning and agents › Knowledge representation and reasoning › nonmonotonic reasoning › preference handling › preference reasoning
CP-nets |
0.2 | 1 | 2016 | A Tool to Graphically Edit CP-Nets · AAAI 2016 |
Knowledge, reasoning and agents › Knowledge representation and reasoning › nonmonotonic reasoning › preference handling
preference reasoning |
0.2 | 1 | 2016 | A Tool to Graphically Edit CP-Nets · AAAI 2016 |
Methods — techniques the papers use, named apart from their topics
graphical interface · 0.2
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2016 | A Tool to Graphically Edit CP-NetsabstractConditional preference networks (CP-nets) are a mathematical formalism for compactly representing preferences over combinatorial domains. The software package presented allows editing of CP-nets through a graphical interface, loads and saves to an XML-based file format, and detects properties of the currently loaded CP-net. Aidan Shafran, Sam Saarinen, Judy Goldsmith |
AAAI | 1 |