Xiao Lin

How good your recommender system is? A survey on evaluations in recommendation

2017 · International Journal of Machine Learning and Cybernetics

Recommender Systems have become a very useful tool for a large variety of domains. Researchers have been attempting to improve their algorithms in order to issue better predictions to the users. However, one of the …

A pareto-efficient algorithm for multiple objective optimization in e-commerce recommendation

2019

Recommendation with multiple objectives is an important but difficult problem, where the coherent difficulty lies in the possible conflicts between objectives. In this case, multi-objective optimization is expected to be Pareto efficient, where no single …

Personalized re-ranking for recommendation

2019

Ranking is a core task in recommender systems, which aims at providing an ordered list of items to users. Typically, a ranking function is learned from the labeled dataset to optimize the global performance, which …

BERT4Rec

2019

Modeling users' dynamic preferences from their historical behaviors is challenging and crucial for recommendation systems. Previous methods employ sequential neural networks to encode users' historical interactions from left to right into hidden representations for making …