LETOR is a benchmark collection for the research on learning to rank for information retrieval, released by Microsoft Research Asia. In this paper, we describe the details of the L...
Ranking is a key problem in many information retrieval (IR) applications, such as document retrieval and collaborative filtering. In this paper, we address the issue of learning ...
Some applications have to present their results in the form of ranked lists. This is the case of many information retrieval applications, in which documents must be sorted accordi...
Adriano Veloso, Humberto Mossri de Almeida, Marcos...
The LETOR website contains three information retrieval datasets used as a benchmark for testing machine learning ideas for ranking. Algorithms participating in the challenge are re...
We consider an interactive information retrieval task in which the user is interested in finding several to many relevant documents with minimal effort. Given an initial documen...