LeToR
A linear regression based approach to page ranking
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. Each query-document pair contains 46 features which are used to train a linear regression model to predict ranks of new query-document pairs(relevance scores).
