To overcome the above limitations, this paper investigates SOLAR -a new framework of Scalable Online Learning Algorithms for Ranking, which aims to learn a ranking model from a sequence of training data in an online learning fashion.
by following the pairwise learning to rank framework, we formally formulate the learning problem, and then present two different SOLAR algorithms to solve the challenging task together with the analysis of their theoretical properties.