Bingjun Qin
Biographic Data
| ID | 10054530 |
|---|---|
| NAME | Bingjun Qin |
| GIVEN NAMES | Bingjun |
| FAMILY NAME | Qin |
| SIGNATURE | QIN B |
| AFFILIATIONS | South China Normal University |
| ORCID | 0009-0001-8681-8828 |
| VERIFIED | Yes |
| TOTAL WORKS | 1 |
| TOTAL CITATIONS | 0 |
| WORKS AS AUTHOR | 1 |
| WORKS AS EDITOR | 0 |
| FIRST PUBLICATION YEAR | 2024 |
| LATEST PUBLICATION YEAR | 2024 |
| H-INDEX | 0 |
MetaGA
The recommendation of long-tail items has been a persistent issue in recommender system research. The primary reason for this problem is that the model cannot learn better item features due to the lack of interactive record data of tail items, which leads to a decline in the model's recommendation performance. Existing methods transfer the features of the head items to the tail items, thereby ignoring their differences and failing to produce a sa…
No prominent works on this page.
MetaGA
The recommendation of long-tail items has been a persistent issue in recommender system research. The primary reason for this problem is that the model cannot learn better item features due to the lack of interactive record data of tail items, which leads to a decline in the model's recommendation performance. Existing methods transfer the features of the head items to the tail items, thereby ignoring their differences and failing to produce a sa…
Advanced Graph Neural Networks (1 work) · Artificial Intelligence (1 work) · Computer Science (1 work) · Graph (1 work) · Recommender Systems and Techniques (1 work) · Stochastic Gradient Optimization Techniques (1 work) · Theoretical Computer Science (1 work)