Most of the existing approaches to learning to rank can be generally grouped into three major categories: (i) pointwise approaches, (ii) pairwise approaches, and (iii) listwise approaches.
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.