5 citations · 6 across the 5 of their papers we have counts for
5 papers
Motif-Based Prompt Learning for Universal Cross-Domain Recommendation
Bowen Hao, Chaoqun Yang, Lei Guo +2
Cross-Domain Recommendation (CDR) stands as a pivotal technology addressing issues of data sparsity and cold start by transferring general knowledge from the source to the target d…
A Multi-Strategy based Pre-Training Method for Cold-Start Recommendation
Bowen Hao, Hongzhi Yin, Jing Zhang +2
Cold-start problem is a fundamental challenge for recommendation tasks. The recent self-supervised learning (SSL) on Graph Neural Networks (GNNs) model, PT-GNN, pre-trains the GNN…
Self-supervised Graph Learning for Occasional Group Recommendation
Bowen Hao, Hongzhi Yin, Cuiping Li +1
As an important branch in Recommender System, occasional group recommendation has received more and more attention. In this scenario, each occasional group (cold-start group) has n…
Recommending Courses in MOOCs for Jobs: An Auto Weak Supervision Approach
Bowen Hao, Jing Zhang, Cuiping Li +2
The proliferation of massive open online courses (MOOCs) demands an effective way of course recommendation for jobs posted in recruitment websites, especially for the people who ta…
Pre-Training Graph Neural Networks for Cold-Start Users and Items Representation
Bowen Hao, Jing Zhang, Hongzhi Yin +2
Cold-start problem is a fundamental challenge for recommendation tasks. Despite the recent advances on Graph Neural Networks (GNNs) incorporate the high-order collaborative signal…