Research on Recommendation Model Based on Multi-round Dialogue of Large Language Model
Recently, the recommendation method combined with large language model has shown obvious advantages in improving recommendation accuracy and enhancing user experience. However, these methods do not make full use of user information, and cannot learn the behavioral characteristics of multiple user in...
Saved in:
| Main Author: | CHANG Baofa, CHE Chao, LIANG Yan |
|---|---|
| Format: | Article |
| Language: | zho |
| Published: |
Journal of Computer Engineering and Applications Beijing Co., Ltd., Science Press
2025-02-01
|
| Series: | Jisuanji kexue yu tansuo |
| Subjects: | |
| Online Access: | http://fcst.ceaj.org/fileup/1673-9418/PDF/2407087.pdf |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
Leveraging multimodal large language model for multimodal sequential recommendation
by: Zhaoliang Wang, et al.
Published: (2025-08-01) -
Research Progress on Sequence Recommendation Based on Deep Learning and Large Language Model
by: XU Fengru, LI Bohan, XU Shuai
Published: (2025-02-01) -
A Hybrid MLP and CNN Architecture for Sequential Recommendation
by: Li Yuan, et al.
Published: (2025-01-01) -
Transformative Movie Discovery: Large Language Models for Recommendation and Genre Prediction
by: Subham Raj, et al.
Published: (2024-01-01) -
Position-Awareness and Hypergraph Contrastive Learning for Multi-Behavior Sequence Recommendation
by: Sitong Yan, et al.
Published: (2024-01-01)