| Learning relatedness measures for entity linking D Ceccarelli, C Lucchese, S Orlando, R Perego, S Trani Proceedings of the 22nd ACM international conference on Information …, 2013 | 103 | 2013 |
| Dexter: an open source framework for entity linking D Ceccarelli, C Lucchese, S Orlando, R Perego, S Trani Proceedings of the sixth international workshop on Exploiting semantic …, 2013 | 78 | 2013 |
| Post-learning optimization of tree ensembles for efficient ranking C Lucchese, FM Nardini, S Orlando, R Perego, F Silvestri, S Trani Proceedings of the 39th International ACM SIGIR conference on Research and …, 2016 | 28 | 2016 |
| Dexter 2.0: an open source tool for semantically enriching data S Trani, D Ceccarelli, C Lucchese, S Orlando, R Perego Proceedings of the 2014 International Conference on Posters & Demonstrations …, 2014 | 27 | 2014 |
| X-DART: Blending dropout and pruning for efficient learning to rank C Lucchese, FM Nardini, S Orlando, R Perego, S Trani Proceedings of the 40th International ACM SIGIR Conference on Research and …, 2017 | 13 | 2017 |
| SEL: A unified algorithm for entity linking and saliency detection S Trani, D Ceccarelli, C Lucchese, S Orlando, R Perego Proceedings of the 2016 ACM Symposium on Document Engineering, 85-94, 2016 | 10 | 2016 |
| Manual annotation of semi-structured documents for entity-linking S Trani, D Ceccarelli, C Lucchese, S Orlando, R Perego Proceedings of the 23rd ACM International Conference on Conference on …, 2014 | 8 | 2014 |
| X-CLEAVER: Learning Ranking Ensembles by Growing and Pruning Trees C Lucchese, FM Nardini, S Orlando, R Perego, F Silvestri, S Trani ACM Transactions on Intelligent Systems and Technology (TIST) 9 (6), 62, 2018 | 7 | 2018 |
| Selective gradient boosting for effective learning to rank C Lucchese, FM Nardini, R Perego, S Orlando, S Trani The 41st International ACM SIGIR Conference on Research & Development in …, 2018 | 6 | 2018 |
| SEL: A unified algorithm for salient entity linking S Trani, C Lucchese, R Perego, DE Losada, D Ceccarelli, S Orlando Computational Intelligence 34 (1), 2-29, 2018 | 6 | 2018 |
| Rankeval: An evaluation and analysis framework for learning-to-rank solutions C Lucchese, CI Muntean, FM Nardini, R Perego, S Trani Proceedings of the 40th International ACM SIGIR Conference on Research and …, 2017 | 3 | 2017 |
| The Impact of Negative Samples on Learning to Rank. C Lucchese, FM Nardini, R Perego, S Trani LEARNER@ ICTIR, 2017 | 3 | 2017 |
| Entity Linking on Philosophical Documents. D Ceccarelli, A De Francesco, R Perego, M Segala, N Tonellotto, S Trani IIR, 2015 | 1 | 2015 |
| Query-level Early Exit for Additive Learning-to-Rank Ensembles C Lucchese, FM Nardini, S Orlando, R Perego, S Trani arXiv preprint arXiv:2004.14641, 2020 | | 2020 |
| Improving the Efficiency and Effectiveness of Document Understanding in Web Search S Trani | | 2017 |
| Improving Document understanding through the Web of Data S Trani | | 2013 |
| Cite-as-you-Write K Jack, M Sambati, F Silvestri, S Trani, R Venturini Cybercrime, 52, 2012 | | 2012 |
| Improve Ranking Efficiency by Optimizing Tree Ensembles C Lucchese, FM Nardini, S Orlando, R Perego, F Silvestri, S Trani | | |
Raffaele PeregoISTI-CNRVerified email at isti.cnr.it
