The goal of this work is to integrate query similarity metrics as features into a dense model that can be trained on large amounts of query log data, in order to rank query rewrit...
Fabio De Bona, Stefan Riezler, Keith Hall, Massimi...
We investigate using gradient descent methods for learning ranking functions; we propose a simple probabilistic cost function, and we introduce RankNet, an implementation of these...
Christopher J. C. Burges, Tal Shaked, Erin Renshaw...
We propose a new boosting algorithm for bipartite ranking problems. Our boosting algorithm, called SoftRankBoost, is a modification of RankBoost which maintains only smooth distri...
The process of rank aggregation is intimately intertwined with the structure of skew-symmetric matrices. We apply recent advances in the theory and algorithms of matrix completion...
This paper introduces RankSQL, a system that provides a systematic and principled framework to support efficient evaluations of ranking (top-k) queries in relational database syst...
Chengkai Li, Kevin Chen-Chuan Chang, Ihab F. Ilyas...