LETOR: A benchmark collection for research on learning to rank for information retrieval

@article{Qin2009LETORAB,
  title={LETOR: A benchmark collection for research on learning to rank for information retrieval},
  author={Tao Qin and Tie-Yan Liu and Jun Xu and Hang Li},
  journal={Information Retrieval},
  year={2009},
  volume={13},
  pages={346-374}
}
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 LETOR collection and show how it can be used in different kinds of researches. Specifically, we describe how the document corpora and query sets in LETOR are selected, how the documents are sampled, how the learning features and meta information are extracted, and how the datasets are partitioned for comprehensive… CONTINUE READING
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