RESUS: Warm-up Cold Users via Meta-learning Residual User Preferences in CTR Prediction
Click-through Rate (CTR) prediction on cold users is a challenging task in recommender systems. Recent researches have resorted to meta-learning to tackle the cold-user challenge, which either perform few-shot user representation learning or adopt optimization-based meta-learning. However, existing...
| Main Authors: | , , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Association for Computing Machinery
2023
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| Subjects: | |
| Online Access: | View Fulltext in Publisher View in Scopus |