Demo Data from SIGIR 2026 / reviewers in the wild / expert
Michael Cunanan
dblp:347/8177
· DBLP profile ↗
1ranked-venue papers
1as 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 first-author · 1 since 2021Graphics, computer vision, multimedia, augmented reality and games · 1 · 1 first-author · 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.
| Theoretical computer science
1 paper |
Algorithms and data structures · 100% |
Topics — the 2 heaviest of 2, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Algorithms and data structures › search algorithms › combinatorial search
guessing games |
0.7 | 1 | 2023 | On Optimal Strategies for Wordle and General Guessing Games · IJCAI 2023 |
Algorithms and data structures › search algorithms › combinatorial search
optimal strategies |
0.7 | 1 | 2023 | On Optimal Strategies for Wordle and General Guessing Games · IJCAI 2023 |
Methods — techniques the papers use, named apart from their topics
game theory · 0.7
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2023 | On Optimal Strategies for Wordle and General Guessing GamesabstractThe recent popularity of Wordle has revived interest in guessing games. We develop a general method for finding optimal strategies for guessing games while avoiding an exhaustive search. Our main contribution are several theorems that build towards a general theory to prove optimality of a strategy for a guessing game. This work is developed to apply to any guessing game, but we use Wordle as an example to present concrete results. Michael Cunanan, Michael Thielscher |
IJCAI | 1 |