A5104270450- Recommender Systems and Techniques
- Advanced Graph Neural Networks
- Advanced Bandit Algorithms Research
- Venous Thromboembolism Diagnosis and Management
- Pediatric health and respiratory diseases
- Voice and Speech Disorders
- Domain Adaptation and Few-Shot Learning
- Vascular anomalies and interventions
- Gastroesophageal reflux and treatments
- Liver Disease and Transplantation
- Machine Learning and Data Classification
Peking University
2025
Kuaishou (China)
2024
China Medical University
2004
Rich user behavior data has been proven to be of great value for recommendation systems. Modeling lifelong in the retrieval stage explore long-term preference and obtain comprehensive results is crucial. Existing modeling methods cannot applied because they extract target-relevant items through coupling between target item. Moreover, current fail precisely capture interests when length sequence increases further. That leads a gap ability models model data. In this paper, we propose concept...
With the rise of e-commerce and short videos, online recommender systems that can capture users' interests update new items in real-time play an increasingly important role. In both offline recommendation, cold-start problem due to interaction sparsity has been affecting recommendation effect items, which is also known as long-tail item distribution. Many scheme based on fine-tuning or knowledge transferring shows excellent performance recommendation. Yet, these schemes are infeasible for...