32 citations · 124 across the 23 of their papers we have counts for
23 papers
GreyShot: Zeroshot and Privacy-preserving Recommender System by GM(1,1) Model
Hao Wang
Every recommendation engineer needs to face the cold start problem when building his system. During the past decades, most scientists adopted transfer learning and meta learning to…
TriMat: Context-aware Recommendation by Tri-Matrix Factorization
Hao Wang
Search engine is the symbolic technology of Web 2.0, and many people used to believe recommender systems is the new frontier of Web 3.0. In the past 10 years, with the advent of Ti…
Emotion-based Recommender System
Hao Wang
Recommender system is one of the most critical technologies for large internet companies such as Amazon and TikTok. Although millions of users use recommender systems globally ever…
A Click-Through Rate Prediction Method Based on Cross-Importance of Multi-Order Features
Hao Wang, Nao Li
Most current click-through rate prediction(CTR)models create explicit or implicit high-order feature crosses through Hadamard product or inner product, with little attention to the…
Mitigating Position Bias with Regularization for Recommender Systems
Hao Wang
Fairness is a popular research topic in recent years. A research topic closely related to fairness is bias and debiasing. Among different types of bias problems, position bias is o…
Enhancing Recommender System Performance by Histogram Equalization
Hao Wang
Recommender system has been researched for decades with millions of different versions of algorithms created in the industry. In spite of the huge amount of work spent on the field…