Quad-tier entity fusion contrastive representation learning for knowledge aware recommendation system
Knowledge graph (KG) has recently emerged as a powerful source of auxiliary information in the realm of knowledge-aware recommendation (KGR) systems. However, due to the lack of supervision signals caused by the sparse nature of user-item interactions, existing supervised graph neural network (GNN)...
Saved in:
Main Authors: | Ong, Kenneth Rongqing, Qiu, Wei, Khong, Andy Wai Hoong |
---|---|
Other Authors: | School of Electrical and Electronic Engineering |
Format: | Conference or Workshop Item |
Language: | English |
Published: |
2024
|
Subjects: | |
Online Access: | https://hdl.handle.net/10356/175884 |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Institution: | Nanyang Technological University |
Language: | English |
Similar Items
-
Improving knowledge-aware recommendation with multi-level interactive contrastive learning
by: ZOU, Ding, et al.
Published: (2022) -
Multi-level cross-view contrastive learning for knowledge-aware recommender system
by: ZOU, Ding, et al.
Published: (2022) -
Multi-level cross-view contrastive learning for knowledge-aware recommender system
by: ZOU, Ding, et al.
Published: (2022) -
Sequential recommendation: From representation learning to reasoning
by: WANG, Lei
Published: (2024) -
Explanation guided contrastive learning for sequential recommendation
by: WANG, Lei, et al.
Published: (2022)