87 citations · 166 across the 14 of their papers we have counts for
5 papers · 1 filter
Intent Disentanglement and Feature Self-supervision for Novel Recommendation
Tieyun Qian, Yile Liang, Qing Li +3
One key property in recommender systems is the long-tail distribution in user-item interactions where most items only have few user feedback. Improving the recommendation of tail i…
Recommending Accurate and Diverse Items Using Bilateral Branch Network
Yile Liang, Tieyun Qian
Recommender systems have played a vital role in online platforms due to the ability of incorporating users' personal tastes. Beyond accuracy, diversity has been recognized as a key…
Seq2seq Translation Model for Sequential Recommendation
Ke Sun, Tieyun Qian
The context information such as product category plays a critical role in sequential recommendation. Recent years have witnessed a growing interest in context-aware sequential reco…
Solving Cold Start Problem in Recommendation with Attribute Graph Neural Networks
Tieyun Qian, Yile Liang, Qing Li
Matrix completion is a classic problem underlying recommender systems. It is traditionally tackled with matrix factorization. Recently, deep learning based methods, especially grap…
Learning Spatiotemporal-Aware Representation for POI Recommendation
Bei Liu, Tieyun Qian, Bing Liu +3
The wide spread of location-based social networks brings about a huge volume of user check-in data, which facilitates the recommendation of points of interest (POIs). Recent advanc…