推荐系统之冷启动

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LHRM: A LBS Based Heterogeneous Relations Model for User Cold Start Recommendation in Online Travel Platform
EndCold: An End-to-End Framework for Cold Question Routing in Community Question Answering Services
Internal and Contextual Attention Network for Cold-start Multi-channel Matching in Recommendation
Addressing the Item Cold-start Problem by Attribute-driven Active Learning
The Pure Cold-Start Problem: A deep study about how to conquer first-time users in recommendations domains
Preliminary Investigation of Alleviating User Cold-Start Problem in E-commerce with Deep Cross-Domain Recommender System
Solving Cold Start Problem in Recommendation with Attribute Graph Neural Networks
STAR-GCN: Stacked and Reconstructed Graph Convolutional Networks for Recommender Systems
Hybrid Item-Item Recommendation via Semi-Parametric Embedding
Warm Up Cold-start Advertisements: Improving CTR Predictions via Learning to Learn ID Embeddings
Deeply Fusing Reviews and Contents for Cold Start Users in Cross-Domain Recommendation Systems
HERS: Modeling Influential Contexts with Heterogeneous Relations for Sparse and Cold-Start Recommendation
From Zero-Shot Learning to Cold-Start Recommendation
MeLU:Meta-Learned User Preference Estimator for Cold-Start Recommendation
Dropoutnet addressing cold start in recommender systems
A survey on solving cold start problem in recommender systems

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