Overview

Istella-X (eXtended) LETOR is an extended Learning to Rank benchmark obtained by retrieving up to 5,000 documents per query using the BM25F ranking score.

• 10,000 queries; 220 features per query-document pair
• 26,791,447 query-document pairs
• Training/validation/test split: 60% / 20% / 20%

How to cite this dataset

If you use this dataset in your research, please acknowledge Istella SpA and cite the following publications:

Claudio Lucchese, Franco Maria Nardini, Raffaele Perego, Salvatore Orlando, Salvatore Trani. 2018. Selective Gradient Boosting for Effective Learning to Rank. The 41st International ACM SIGIR Conference on Research and Development in Information Retrieval. 10.1145/3209978.3210048.

@inproceedings{istellaX2018,
  author = {Claudio Lucchese and Franco Maria Nardini and Raffaele Perego and Salvatore Orlando and Salvatore Trani},
  title = {Selective Gradient Boosting for Effective Learning to Rank},
  booktitle = {The 41st International ACM SIGIR Conference on Research and Development in Information Retrieval},
  year = {2018},
  doi = {10.1145/3209978.3210048},
  url = {https://doi.org/10.1145/3209978.3210048},
  pages = {155--164},
}

Domenico Dato, Claudio Lucchese, Franco Maria Nardini, Salvatore Orlando, Raffaele Perego, Nicola Tonellotto, Rossano Venturini. 2016. Fast Ranking with Additive Ensembles of Oblivious and Non-Oblivious Regression Trees. ACM Transactions on Information Systems. 10.1145/2987380.

@article{istellaLetor2016,
  author = {Domenico Dato and Claudio Lucchese and Franco Maria Nardini and Salvatore Orlando and Raffaele Perego and Nicola Tonellotto and Rossano Venturini},
  title = {Fast Ranking with Additive Ensembles of Oblivious and Non-Oblivious Regression Trees},
  journal = {ACM Transactions on Information Systems},
  year = {2016},
  doi = {10.1145/2987380},
  url = {https://doi.org/10.1145/2987380},
  volume = {35},
  number = {2},
  articleno = {15},
  numpages = {31},
}

Download

The dataset is available solely for non-commercial use. Read and accept the license before downloading the files. Read the license.