361 citations · 410 across the 9 of their papers we have counts for
8 papers · 1 filter
A Unified Framework for Cross-Domain and Cross-System Recommendations
Feng Zhu, Yan Wang, Jun Zhou +3
Cross-Domain Recommendation (CDR) and Cross-System Recommendation (CSR) have been proposed to improve the recommendation accuracy in a target dataset (domain/system) with the help…
Next-item Recommendations in Short Sessions
Wenzhuo Song, Shoujin Wang, Yan Wang +1
The changing preferences of users towards items trigger the emergence of session-based recommender systems (SBRSs), which aim to model the dynamic preferences of users for next-ite…
Graph Learning based Recommender Systems: A Review
Shoujin Wang, Liang Hu, Yan Wang +6
Recent years have witnessed the fast development of the emerging topic of Graph Learning based Recommender Systems (GLRS). GLRS employ advanced graph learning approaches to model u…
Cross-Domain Recommendation: Challenges, Progress, and Prospects
Feng Zhu, Yan Wang, Chaochao Chen +3
To address the long-standing data sparsity problem in recommender systems (RSs), cross-domain recommendation (CDR) has been proposed to leverage the relatively richer information f…
Stratified and Time-aware Sampling based Adaptive Ensemble Learning for Streaming Recommendations
Yan Zhao, Shoujin Wang, Yan Wang +1
Recommender systems have played an increasingly important role in providing users with tailored suggestions based on their preferences. However, the conventional offline recommende…
Double-Wing Mixture of Experts for Streaming Recommendations
Yan Zhao, Shoujin Wang, Yan Wang +2
Streaming Recommender Systems (SRSs) commonly train recommendation models on newly received data only to address user preference drift, i.e., the changing user preferences towards…