Research Papers

If you use QuickRank, please acknowledge the following paper:

  • Capannini, G., Lucchese, C., Nardini, F. M., Orlando, S., Perego, R., and Tonellotto, N. Quality versus efficiency in document scoring with learning-to-rank models. Information Processing & Management 2016. LINK.

If you use the CLEAVER, please acknowledge the following paper:

  • C. Lucchese, F. M. Nardini, S. Orlando, R. Perego, F. Silvestri, S. Trani. Post-Learning Optimization of Tree Ensembles for Efficient Ranking. ACM SIGIR Conference on Research and Development in Information Retrieval, 2016. LINK.

If you use X-DART, please acknowledge the following paper:

  • C. Lucchese, F. M. Nardini, S. Orlando, R. Perego, and S. Trani. X-DART: Blending Dropout and Pruning for Efficient Learning to Rank. ACM SIGIR Conference on Research and Development in Information Retrieval, 2017. LINK.

Featured by QuickRank

QuickRank was used in the following papers:

  • Claudio Lucchese, Franco Maria Nardini, Salvatore Orlando, Raffaele Perego and Salvatore Trani. X-DART: Blending Dropouts and Pruning for Efficient Learning To Rank. In Proc. ACM SIGIR. 2017.
  • Claudio Lucchese, Cristina Ioana Muntean, Franco Maria Nardini, Raffaele Perego and Salvatore Trani. RankEval: An Evaluation and Analysis Framework for Learning-to-Rank Solutions. In Proc. ACM SIGIR. 2017.
  • Domenico Dato, Claudio Lucchese, Franco Maria Nardini, Salvatore Orlando, Raffaele Perego, Nicola Tonellotto, Rossano Venturini. Fast Ranking with Additive Ensembles of Oblivious and Non-Oblivious Regression Trees. ACM Transactions on Information Systems (TOIS), Volume 35, Issue 2, Dec. 2016.
  • Claudio Lucchese Andrea Gigli, Franco Maria Nardini, and Raffaele Perego. Fast Feature Selection for Learning to Rank. In Proc. ACM ICTIR. 2016.
  • Claudio Lucchese, Franco Maria Nardini, Salvatore Orlando, and Gabriele Tolomei. Learning to Rank User Queries to Detect Search T asks. In Proc. ACM ICTIR. 2016.
  • Claudio Lucchese, Franco Maria Nardini, Salvatore Orlando, Raffaele Perego, Nicola Tonellotto, and Rossano Venturini.Exploiting CPU SIMD Extensions to Speed-up Document Scoring with Tree Ensembles. In Proc. ACM SIGIR. 2016.
  • Claudio Lucchese, Franco Maria Nardini, Salvatore Orlando, Raffaele Perego, Fabrizio Silvestri, Salvatore Trani Post-Learning Optimization of Tree Ensembles for Efficient Ranking. In Proc. ACM SIGIR. 2016.
  • Claudio Lucchese, Franco¬†Maria Nardini, Salvatore Orlando, Raffaele Perego, Nicola Tonellotto, Gabriele Capannini. Quality versus Efficiency in Document Scoring with Learning-to-Rank Models.¬† Information Processing & Management (Elsevier). 2016.
  • Claudio Lucchese, Franco Maria Nardini, Salvatore Orlando, Raffaele Perego, Nicola Tonellotto, Rossano Venturini. QuickScorer: a Fast Algorithm to Rank Documents with Additive Ensembles of Regression Trees. In Proc. ACM SIGIR. 2015. BEST PAPER AWARD.
  • Gabriele Capannini, Domenico Dato, Claudio Lucchese, Monica Mori, Franco Maria Nardini, Salvatore Orlando, Raffaele Perego, Nicola Tonellotto. QuickRank: a C++ Suite of Learning to Rank Algorithms. In Proc. IIR. 2105.

We will be happy to know that you are using QuickRank and to acknowledge you!