Tutorial: Eﬃciency/Eﬀectiveness Trade-oﬀs in Learning to Rank
Accepted at ECML-PKDD ’18: The European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases .
Abstract. In the last years, learning to rank (LtR) had a signiﬁcant inﬂuence on several data mining tasks and in particular in the Information Retrieval ﬁeld,with large research eﬀorts coming both from the academia and the industry. Indeed, eﬃciency requirements must be fulﬁlled in order to make an eﬀective research product deployable within an industrial environment. The evaluation of a model can be too expensive due to its size, the features used and several other factors. This tutorial discusses the recent solutions that allow to build an eﬀective ranking model that satisﬁes temporal budget constrains at evaluation time.
Tutorial material available at: http://learningtorank.isti.cnr.it/.