Demo Data from VLDB 2026 / reviewers in the wild / expert
Huanjing Gao
dblp:388/1968
· DBLP profile ↗
1ranked-venue papers
0as first author
1since 2021 · last 2024
—ORCID · none
Domains — the database's venue-derived domains; a paper can count in several
Artificial intelligence and machine learning · 1 · 1 since 2021Graphics, computer vision, multimedia, augmented reality and games · 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 |
Recommender systems · 100% |
Topics — the 2 heaviest of 3, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Recommender systems › representation learning for recommendation
contrastive learning for recommendation |
0.8 | 1 | 2024 | R2V-MIF: Rule-to-Vector Contrastive Learning and Multi-channel Information Fusion for Therapy Recommendation · IJCAI 2024 |
Recommender systems
recommendation |
0.8 | 1 | 2024 | R2V-MIF: Rule-to-Vector Contrastive Learning and Multi-channel Information Fusion for Therapy Recommendation · IJCAI 2024 |
Methods — techniques the papers use, named apart from their topics
multi-channel information fusion · 0.8contrastive learning · 0.8
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2024 | R2V-MIF: Rule-to-Vector Contrastive Learning and Multi-channel Information Fusion for Therapy Recommendation
Nengjun Zhu, Jieyun Huang, Jian Cao 0001, Liang Hu 0004, Zixuan Yuan, Huanjing Gao |
IJCAI | 6 |