most citedTowards Feature Selection for Ranking and Classification Exploiting Quantum Annealers

46 citations · 106 across the 6 of their papers we have counts for

collaborators

6 papers

cs.IR2023★ 22 cited

How Discriminative Are Your Qrels? How To Study the Statistical Significance of Document Adjudication Methods

David Otero, Javier Parapar, Nicola Ferro

Creating test collections for offline retrieval evaluation requires human effort to judge documents' relevance. This expensive activity motivated much work in developing methods fo…

cs.IR2023★ 24 cited

Report from Dagstuhl Seminar 23031: Frontiers of Information Access Experimentation for Research and Education

Christine Bauer, Ben Carterette, Nicola Ferro +1

This report documents the program and the outcomes of Dagstuhl Seminar 23031 ``Frontiers of Information Access Experimentation for Research and Education'', which brought together…

cs.HC2022★ 1 cited

FullBrain: a Social E-learning Platform

Mirko Biasini, Vittorio Carmignani, Nicola Ferro +3

We present FullBrain, a social e-learning platform where students share and track their knowledge. FullBrain users can post notes, ask questions and share learning resources in ded…

cs.IR2022

Corrected Evaluation Results of the NTCIR WWW-2, WWW-3, and WWW-4 English Subtasks

Tetsuya Sakai, Sijie Tao, Maria Maistro +7

Unfortunately, the official English (sub)task results reported in the NTCIR-14 WWW-2, NTCIR-15 WWW-3, and NTCIR-16 WWW-4 overview papers are incorrect due to noise in the official…

cs.IR2022★ 46 cited

Towards Feature Selection for Ranking and Classification Exploiting Quantum Annealers

Maurizio Ferrari Dacrema, Fabio Moroni, Riccardo Nembrini +3

Feature selection is a common step in many ranking, classification, or prediction tasks and serves many purposes. By removing redundant or noisy features, the accuracy of ranking o…

cs.IR2022★ 13 cited

repro_eval: A Python Interface to Reproducibility Measures of System-oriented IR Experiments

Timo Breuer, Nicola Ferro, Maria Maistro +1

In this work we introduce repro_eval - a tool for reactive reproducibility studies of system-oriented information retrieval (IR) experiments. The corresponding Python package provi…