224 citations · 1.8k across the 59 of their papers we have counts for
Showing 2018Show all
2 papers · 1 filter
cs.IR2018★ 11 cited
Sampler Design for Bayesian Personalized Ranking by Leveraging View Data
Jingtao Ding, Guanghui Yu, Xiangnan He +2
Bayesian Personalized Ranking (BPR) is a representative pairwise learning method for optimizing recommendation models. It is widely known that the performance of BPR depends largel…
cs.IR2018★ 108 cited
Learning to Recommend with Multiple Cascading Behaviors
Chen Gao, Xiangnan He, Dahua Gan +7
Most existing recommender systems leverage user behavior data of one type only, such as the purchase behavior in E-commerce that is directly related to the business KPI (Key Perfor…