most citedSequential Recommender Systems: Challenges, Progress and Prospects

361 citations · 406 across the 6 of their papers we have counts for

collaborators

6 papers

cs.LG202011 cited

A Deep Framework for Cross-Domain and Cross-System Recommendations

Feng Zhu, Yan Wang, Chaochao Chen +3

Cross-Domain Recommendation (CDR) and Cross-System Recommendations (CSR) are two of the promising solutions to address the long-standing data sparsity problem in recommender system…

eess.IV20203 cited

Beyond CNNs: Exploiting Further Inherent Symmetries in Medical Images for Segmentation

Shuchao Pang, Anan Du, Mehmet A. Orgun +5

Automatic tumor segmentation is a crucial step in medical image analysis for computer-aided diagnosis. Although the existing methods based on convolutional neural networks (CNNs) h…

cs.IR202028 cited

Graph Learning Approaches to Recommender Systems: A Review

Shoujin Wang, Liang Hu, Yan Wang +7

Recent years have witnessed the fast development of the emerging topic of Graph Learning based Recommender Systems (GLRS). GLRS mainly employ the advanced graph learning approaches…

cs.IR20203 cited

Enabling the Analysis of Personality Aspects in Recommender Systems

Shahpar Yakhchi, Amin Beheshti, Seyed Mohssen Ghafari +1

Existing Recommender Systems mainly focus on exploiting users' feedback, e.g., ratings, and reviews on common items to detect similar users. Thus, they might fail when there are no…

cs.IR2019361 cited

Sequential Recommender Systems: Challenges, Progress and Prospects

Shoujin Wang, Liang Hu, Yan Wang +3

The emerging topic of sequential recommender systems has attracted increasing attention in recent years.Different from the conventional recommender systems including collaborative…

cs.AI2019

On Conforming and Conflicting Values

Kinzang Chhogyal, Abhaya Nayak, Aditya Ghose +2

Values are things that are important to us. Actions activate values - they either go against our values or they promote our values. Values themselves can either be conforming or co…