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RESUS: Warm-up Cold Users via Meta-learning Residual User Preferences in CTR Prediction
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What this work says
Outgoing claims: the papers this work cites, builds on, or argues with.
inferredcites →https://doi.org/10.1109/tkde.2017.2698461openalex-snapshot
Injection: Toward Effective Collaborative Filtering Using Uninteresting Items
inferredcites →https://doi.org/10.1145/2976737openalex-snapshot
Learning Informative Priors from Heterogeneous Domains to Improve Recommendation in Cold-Start User Domains
inferredcites →https://doi.org/10.1145/2988450.2988454openalex-snapshot
Wide & Deep Learning for Recommender Systems
inferredcites →https://doi.org/10.1145/3017429openalex-snapshot
Cross-Platform App Recommendation by Jointly Modeling Ratings and Texts
inferredcites →https://doi.org/10.1145/3397271.3401252openalex-snapshot
A Heterogeneous Graph Neural Model for Cold-start Recommendation
inferredcites →https://doi.org/10.1214/aos/1013203451openalex-snapshot
Greedy function approximation: A gradient boosting machine.
inferredcites →https://doi.org/10.24963/ijcai.2017/239openalex-snapshot
DeepFM: A Factorization-Machine based Neural Network for CTR Prediction
What points at this work
Incoming claims: where this work appears in other papers’ reference lists and arguments.
inferred← citeshttps://doi.org/10.1002/cpe.70716openalex-snapshot
A Dual‐Path Framework Based on Meta‐Learning and Attention Mechanism for Click‐Through Rate Prediction in Cold‐Start Scenarios
inferred← citeshttps://doi.org/10.1007/s10115-024-02316-yopenalex-snapshot
Federated cross-domain recommendation system based on bias eliminator and personalized extractor
inferred← citeshttps://doi.org/10.1007/s10844-025-00999-5openalex-snapshot
Predicting residents’ travel mode choice based on MAML
inferred← citeshttps://doi.org/10.1016/j.knosys.2026.116967openalex-snapshot
Two-stream product interaction network with state-adaptive gating for CTR prediction
inferred← citeshttps://doi.org/10.1016/j.procs.2026.07.279openalex-snapshot
Construction and Optimization of Consumer Preference Prediction Model Driven by Deep Learning
inferred← citeshttps://doi.org/10.1109/access.2023.3338705openalex-snapshot
User Cold Start Problem in Recommendation Systems: A Systematic Review
inferred← citeshttps://doi.org/10.1145/3652600openalex-snapshot
SPContrastNet: A Self-Paced Contrastive Learning Model for Few-Shot Text Classification
inferred← citeshttps://doi.org/10.1145/3681785openalex-snapshot
AdaGIN: Adaptive Graph Interaction Network for Click-Through Rate Prediction
inferred← citeshttps://doi.org/10.1145/3688571openalex-snapshot
CETN: Contrast-enhanced Through Network for Click-Through Rate Prediction
inferred← citeshttps://doi.org/10.1145/3829076openalex-snapshot
A Trust and User Preference Model for Marketing Information Dissemination
inferred← citeshttps://doi.org/10.18267/j.aip.280openalex-snapshot
ResNetMF: Improving Recommendation Accuracy and Speed with Matrix Factorization Enhanced by Residual Networks
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