361 citations · 499 across the 14 of their papers we have counts for
14 papers
A Counterfactual Collaborative Session-based Recommender System
Wenzhuo Song, Shoujin Wang, Yan Wang +3
Most session-based recommender systems (SBRSs) focus on extracting information from the observed items in the current session of a user to predict a next item, ignoring the causes…
Beyond CNNs: Exploiting Further Inherent Symmetries in Medical Image Segmentation
Shuchao Pang, Anan Du, Mehmet A. Orgun +5
Automatic tumor or lesion segmentation is a crucial step in medical image analysis for computer-aided diagnosis. Although the existing methods based on Convolutional Neural Network…
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…