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)...
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Main Authors: | , , |
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Format: | Conference or Workshop Item |
Language: | English |
Published: |
2024
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Online Access: | https://hdl.handle.net/10356/175884 |
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Institution: | Nanyang Technological University |
Language: | English |