1 citations · 1 across the 2 of their papers we have counts for
4 papers
Representation Quantization for Collaborative Filtering Augmentation
Yunze Luo, Yinjie Jiang, Gaode Chen +9
As the core algorithm in recommendation systems, collaborative filtering (CF) algorithms inevitably face the problem of data sparsity. Since CF captures similar users and items for…
Prompt Tuning for Item Cold-start Recommendation
Yuezihan Jiang, Gaode Chen, Wenhan Zhang +6
The item cold-start problem is crucial for online recommender systems, as the success of the cold-start phase determines whether items can transition into popular ones. Prompt lear…
Online Item Cold-Start Recommendation with Popularity-Aware Meta-Learning
Yunze Luo, Yuezihan Jiang, Yinjie Jiang +5
With the rise of e-commerce and short videos, online recommender systems that can capture users' interests and update new items in real-time play an increasingly important role. In…
A Unified Framework for Cross-Domain Recommendation
Jiangxia Cao, Shen Wang, Gaode Chen +4
In addressing the persistent challenges of data-sparsity and cold-start issues in domain-expert recommender systems, Cross-Domain Recommendation (CDR) emerges as a promising method…