81 citations · 98 across the 5 of their papers we have counts for
5 papers
Balancing Accuracy and Fairness for Interactive Recommendation with Reinforcement Learning
Weiwen Liu, Feng Liu, Ruiming Tang +3
Fairness in recommendation has attracted increasing attention due to bias and discrimination possibly caused by traditional recommenders. In Interactive Recommender Systems (IRS),…
Inter-sequence Enhanced Framework for Personalized Sequential Recommendation
Feng Liu, Weiwen Liu, Xutao Li +1
Modeling the sequential correlation of users' historical interactions is essential in sequential recommendation. However, the majority of the approaches mainly focus on modeling th…
Deep Reinforcement Learning based Recommendation with Explicit User-Item Interactions Modeling
Feng Liu, Ruiming Tang, Xutao Li +5
Recommendation is crucial in both academia and industry, and various techniques are proposed such as content-based collaborative filtering, matrix factorization, logistic regressio…
An Adjustable Heat Conduction based KNN Approach for Session-based Recommendation
Huifeng Guo, Ruiming Tang, Yunming Ye +2
The KNN approach, which is widely used in recommender systems because of its efficiency, robustness and interpretability, is proposed for session-based recommendation recently and…
Novel Approaches to Accelerating the Convergence Rate of Markov Decision Process for Search Result Diversification
Feng Liu, Ruiming Tang, Xutao Li +3
Recently, some studies have utilized the Markov Decision Process for diversifying (MDP-DIV) the search results in information retrieval. Though promising performances can be delive…