Enhancing CDR with adaptive fusion of positive and negative feedback (IMAGE)
Caption
The Deep User Preference Gating Transfer for Cross-Domain Recommendation (DUPGT-CDR) framework improves CDR by separately encoding high and low user feedback from the source domain and adaptively fusing these signals using a gating network. This mechanism enables more accurate transfer of user preferences to the target domain, improving recommendation performance in cold-start scenarios and outperforming existing CDR methods across multiple real-world datasets.
Credit
Associate Professor Keiko Ono from Doshisha University, Japan
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Credit must be given to the creator. Only noncommercial uses of the work are permitted. No derivatives or adaptations of the work are permitted.
License
CC BY-NC-ND