1 In this article, we report our efforts in mining the information encoded as clickthrough data in the server logs to evaluate and monitor the relevance ranking quality of a commer...
This paper presents a new way of thinking for IR metric optimization. It is argued that the optimal ranking problem should be factorized into two distinct yet interrelated stages:...
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 the problem of learning to rank for document retrieval from the perspective of learning with multiple objective functions. We present solutions to two open problems...
Krysta Marie Svore, Maksims Volkovs, Christopher J...
Ranking a set of retrieved documents according to their relevance to a query is a popular problem in information retrieval. Methods that learn ranking functions are difficult to o...