1 citations · 4 across the 7 of their papers we have counts for
4 papers · 1 filter
Contrastive Learning for Cold Start Recommendation with Adaptive Feature Fusion
Jiacheng Hu, Tai An, Zidong Yu +2
This paper proposes a cold start recommendation model that integrates contrastive learning, aiming to solve the problem of performance degradation of recommendation systems in cold…
Enhancing Recommendation Systems with GNNs and Addressing Over-Smoothing
Wenyi Liu, Ziqi Zhang, Xinshi Li +3
This paper addresses key challenges in enhancing recommendation systems by leveraging Graph Neural Networks (GNNs) and addressing inherent limitations such as over-smoothing, which…
Metric Learning for Tag Recommendation: Tackling Data Sparsity and Cold Start Issues
Yuanshuai Luo, Rui Wang, Yaxin Liang +2
With the rapid growth of digital information, personalized recommendation systems have become an indispensable part of Internet services, especially in the fields of e-commerce, so…
A Recommendation Model Utilizing Separation Embedding and Self-Attention for Feature Mining
Wenyi Liu, Rui Wang, Yuanshuai Luo +3
With the explosive growth of Internet data, users are facing the problem of information overload, which makes it a challenge to efficiently obtain the required resources. Recommend…