Introducing LETOR 4.0 Datasets. LETOR is a package of benchmark data sets for research on LEarning TO Rank, which contains standard features, relevance judgments, data partitioning, evaluation tools, and several baselines. Version 1.0 was released in April 2007. Version 2.0 was released in Dec. 2007. Version 3.0 was released in Dec. 2008. This version, 4.0, was released in July 2009. Very different from previous versions (V3.0 is an update based on V2.0 and V2.0 is an update based on V1.0), LETOR4.0 is a totally new release. It uses the Gov2 web page collection ( 25M pages) and two query sets from Million Query track of TREC 2007 and TREC 2008. We call the two query sets MQ2007 and MQ2008 for short. There are about 1700 queries in MQ2007 with labeled documents and about 800 queries in MQ2008 with labeled documents. If you have any questions or suggestions about the datasets, please kindly email us (letor@microsoft.com). Our goal is to make the dataset reliable and useful for the community.

References in zbMATH (referenced in 10 articles )

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  1. Pfannschmidt, Karlson; Gupta, Pritha; Haddenhorst, Björn; Hüllermeier, Eyke: Learning context-dependent choice functions (2022)
  2. Connamacher, Harold; Pancha, Nikil; Liu, Rui; Ray, Soumya: \textscRankboost(+): an improvement to \textscRankboost (2020)
  3. Zehlike, Meike; Hacker, Philipp; Wiedemann, Emil: Matching code and law: achieving algorithmic fairness with optimal transport (2020)
  4. Jiang, Chunheng; Lin, Wenbin: DEARank: a data-envelopment-analysis-based ranking method (2015)
  5. Kim, Sungchul; Qin, Tao; Liu, Tie-Yan; Yu, Hwanjo: Advertiser-centric approach to understand user click behavior in sponsored search (2014) ioport
  6. Lee, Ching-Pei; Lin, Chih-Jen: Large-scale linear rankSVM (2014)
  7. Birlutiu, Adriana; Groot, Perry; Heskes, Tom: Efficiently learning the preferences of people (2013)
  8. Wang, Yang; Huang, Yalou; Pang, Xiaodong; Lu, Min; Xie, Maoqiang; Liu, Jie: Supervised rank aggregation based on query similarity for document retrieval (2013) ioport
  9. Bollegala, Danushka; Okazaki, Naoaki; Ishizuka, Mitsuru: A preference learning approach to sentence ordering for multi-document summarization (2012) ioport
  10. Yang, Yiming; Gopal, Siddharth: Multilabel classification with meta-level features in a learning-to-rank framework (2012)