IDBR: Interaction-Aware Dual-Granularity Learning for Bundle Recommendation
In the recommendation system, bundle recommendation is a prevalent sales strategy in which a combination of diverse, related, or complementary products is suggested to consumers. Recent methodologies frequently utilize graph neural networks to capture information from user-bundle, user-item, and bun...
Saved in:
| Main Authors: | Jinqing Wang, Yuan Cao, Fan Zhang, Feifei Kou, Kaimin Wei, Jinghui Zhang, Jinpeng Chen |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Tsinghua University Press
2025-05-01
|
| Series: | Big Data Mining and Analytics |
| Subjects: | |
| Online Access: | https://www.sciopen.com/article/10.26599/BDMA.2025.9020016 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
News Recommendation Method Based on Candidate-Aware Long- and Short-Term Preference Modeling
by: Shuhao Jiang, et al.
Published: (2024-12-01) -
DMR: disentangled and denoised learning for multi-behavior recommendation
by: Yijia Zhang, et al.
Published: (2025-01-01) -
Attribute-Aware Graph Aggregation for Sequential Recommendation
by: Yiming Qu, et al.
Published: (2025-04-01) -
Strengthening of Copper during High-Speed Deformation
by: A.V. Volokitin, A.I. Denissova, and M.Ş. Sönmez
Published: (2025-06-01) -
User preference information recommendation based on DCGNN and GNNPK algorithms
by: Nannan Cheng, et al.
Published: (2025-12-01)