activity
20212025
collaborators

7 papers

cs.IR2025

Quantifying Query Fairness Under Unawareness

Thomas Jaenich, Alejandro Moreo, Alessandro Fabris +4

Traditional ranking algorithms are designed to retrieve the most relevant items for a user's query, but they often inherit biases from data that can unfairly disadvantage vulnerabl…

cs.LG2023

Explainable Authorship Identification in Cultural Heritage Applications: Analysis of a New Perspective

Mattia Setzu, Silvia Corbara, Anna Monreale +2

While a substantial amount of work has recently been devoted to enhance the performance of computational Authorship Identification (AId) systems, little to no attention has been pa…

cs.LG2023

Regularization-Based Methods for Ordinal Quantification

Mirko Bunse, Alejandro Moreo, Fabrizio Sebastiani +1

Quantification, i.e., the task of training predictors of the class prevalence values in sets of unlabeled data items, has received increased attention in recent years. However, mos…

cs.LG2023

Binary Quantification and Dataset Shift: An Experimental Investigation

Pablo González, Alejandro Moreo, Fabrizio Sebastiani

Quantification is the supervised learning task that consists of training predictors of the class prevalence values of sets of unlabelled data, and is of special interest when the l…

cs.LG2023

Same or Different? Diff-Vectors for Authorship Analysis

Silvia Corbara, Alejandro Moreo, Fabrizio Sebastiani

We investigate the effects on authorship identification tasks of a fundamental shift in how to conceive the vectorial representations of documents that are given as input to a supe…

cs.CL2022

Unravelling Interlanguage Facts via Explainable Machine Learning

Barbara Berti, Andrea Esuli, Fabrizio Sebastiani

Native language identification (NLI) is the task of training (via supervised machine learning) a classifier that guesses the native language of the author of a text. This task has…