2 papers
cs.IR2026
Behavioral Feature Boosting via Substitute Relationships for E-commerce Search
Chaosheng Dong, Michinari Momma, Yijia Wang +2
On E-commerce platforms, new products often suffer from the cold-start problem: limited interaction data reduces their search visibility and hurts relevance ranking. To address thi…
cs.LG2023
Bandit Learning to Rank with Position-Based Click Models: Personalized and Equal Treatments
Tianchen Zhou, Jia Liu, Yang Jiao +4
Online learning to rank (ONL2R) is a foundational problem for recommender systems and has received increasing attention in recent years. Among the existing approaches for ONL2R, a…