The MSLR-WEB10K dataset consists of 10,000 search queries over the documents from search results. The data also contains the values of 136 features and a corresponding user-labeled relevance factor on a scale of one to five with respect to each query-document pair. It is a subset of the MSLR-WEB30K dataset.
35 PAPERS • NO BENCHMARKS YET
The MQ2007 dataset consists of queries, corresponding retrieved documents and labels provided by human experts. The possible relevance labels for each document are “relevant”, “partially relevant”, and “not relevant”.
30 PAPERS • NO BENCHMARKS YET
The MQ2008 dataset is a dataset for Learning to Rank. It contains 800 queries with labelled documents.
27 PAPERS • NO BENCHMARKS YET