most citedSequential Recommender Systems: Challenges, Progress and Prospects

361 citations · 393 across the 6 of their papers we have counts for

collaborators

6 papers

cs.IR2020

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…

cs.IR20201 cited

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…

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.DB2020

Updates-Aware Graph Pattern based Node Matching

Guohao Sun, Guanfeng Liu, Yan Wang +1

Graph Pattern based Node Matching (GPNM) is to find all the matches of the nodes in a data graph GD based on a given pattern graph GP. GPNM has become increasingly important in man…

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.LG20193 cited

Adaptive Portfolio by Solving Multi-armed Bandit via Thompson Sampling

Mengying Zhu, Xiaolin Zheng, Yan Wang +2

As the cornerstone of modern portfolio theory, Markowitz's mean-variance optimization is considered a major model adopted in portfolio management. However, due to the difficulty of…