10 citations · 22 across the 5 of their papers we have counts for
5 papers
Proactive Recommendation in Social Networks: Steering User Interest with Causal Inference
Hang Pan, Shuxian Bi, Wenjie Wang +3
Recommending items that solely cater to users' historical interests narrows users' horizons. Recent works have considered steering target users beyond their historical interests by…
Leveraging LLMs for Influence Path Planning in Proactive Recommendation
Mingze Wang, Shuxian Bi, Wenjie Wang +3
Recommender systems are pivotal in Internet social platforms, yet they often cater to users' historical interests, leading to critical issues like echo chambers. To broaden user ho…
Proactive Recommendation with Iterative Preference Guidance
Shuxian Bi, Wenjie Wang, Hang Pan +2
Recommender systems mainly tailor personalized recommendations according to user interests learned from user feedback. However, such recommender systems passively cater to user int…
On the Equivalence of Decoupled Graph Convolution Network and Label Propagation
Hande Dong, Jiawei Chen, Fuli Feng +4
The original design of Graph Convolution Network (GCN) couples feature transformation and neighborhood aggregation for node representation learning. Recently, some work shows that…
Data Augmentation View on Graph Convolutional Network and the Proposal of Monte Carlo Graph Learning
Hande Dong, Zhaolin Ding, Xiangnan He +2
Today, there are two major understandings for graph convolutional networks, i.e., in the spectral and spatial domain. But both lack transparency. In this work, we introduce a new u…