LETOR: Learning to Rank for Information Retrieval - Microsoft Research
learning-to-rankinformation-retrievalsvmbenchmarkmicrosoft-research
Abstraction: LETOR benchmark page describing RankSVM primal baseline for learning-to-rank
Key points:
- Page is the RankSVM-primal baseline entry within the LETOR 4.0 benchmark package from Microsoft Research
- LETOR 4.0 uses Gov2 web collection (~25M pages) with MQ2007 (~1700 queries) and MQ2008 (~800 queries)
- Provides standard features, relevance judgments, data splits, evaluation tools, and SVM baseline implementations
- LETOR 3.0 citation: Qin, Liu, Xu, Li, Information Retrieval Journal 2010
- LETOR 4.0 citation: Qin and Liu, arXiv:1306.2597
Connections: Microsoft Research · Letor · Learning To Rank · Svm · Information Retrieval
Source: http://research.microsoft.com/en-us/um/beijing/projects/letor/baselines/ranksvm-primal.html