| Autor: |
Luo, Tianze, Liu, Yong, Pan, Sinno Jialin |
| Zdroj: |
ACM Transactions on Information Systems; Nov2024, Vol. 42 Issue 6, p1-27, 27p |
| Abstrakt: |
The article presents a sequential recommendation framework that enhances recommendation accuracy by capturing both individual user behavior patterns and collaborative information from other users. Topics include the limitations of current recommendation models that rely on single-user behavior sequences, the proposed use of hierarchical graph networks to aggregate multi-hop item relationships, and the integration of graph neural networks with transformers for efficient and robust prediction. |
| Databáze: |
Complementary Index |
| Externí odkaz: |
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