Leveraging RAG With Transformer for Context-Based Personalized Recommendations
Recent advancements in large language models (LLMs) have shown significant progress in addressing challenges related to data sparsity and the cold-start problem. In e-commerce, recommendation systems are widely used as strategic tools to boost sales and enhance the customer experience by helping use...
Saved in:
| Main Authors: | Faten S. Alamri, Amjad Rehman, Bayan Alghofaily, Adeel Ahmed, Khalid Saleem |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
IEEE
2025-01-01
|
| Series: | IEEE Access |
| Subjects: | |
| Online Access: | https://ieeexplore.ieee.org/document/11016029/ |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
Personalised context-aware re-ranking in recommender system
by: Xiangyong Liu, et al.
Published: (2022-12-01) -
Leveraging multimodal large language model for multimodal sequential recommendation
by: Zhaoliang Wang, et al.
Published: (2025-08-01) -
Context-Aware Negative Sampling for Sequential Recommendation
by: Jinseok Seol, et al.
Published: (2025-01-01) -
Application of the FEA consumer needs model in e-commerce: a conversational recommendation system for fashion products
by: Hyeryeon Park, 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)