Zobrazeno 1 - 10
of 481
pro vyhledávání: '"Monreale A."'
Coordination is a fundamental aspect of life. The advent of social media has made it integral also to online human interactions, such as those that characterize thriving online communities and social movements. At the same time, coordination is also
Externí odkaz:
http://arxiv.org/abs/2408.01257
Autor:
Corbucci, Luca, Heikkila, Mikko A, Noguero, David Solans, Monreale, Anna, Kourtellis, Nicolas
Training and deploying Machine Learning models that simultaneously adhere to principles of fairness and privacy while ensuring good utility poses a significant challenge. The interplay between these three factors of trustworthiness is frequently unde
Externí odkaz:
http://arxiv.org/abs/2407.15224
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 paid to endowing AId systems with the ability to explain the reasons beh
Externí odkaz:
http://arxiv.org/abs/2311.02237
Online social networks are actively involved in the removal of malicious social bots due to their role in the spread of low quality information. However, most of the existing bot detectors are supervised classifiers incapable of capturing the evolvin
Externí odkaz:
http://arxiv.org/abs/2209.10361
Artificial Intelligence (AI) is increasingly used to build Decision Support Systems (DSS) across many domains. This paper describes a series of experiments designed to observe human response to different characteristics of a DSS such as accuracy and
Externí odkaz:
http://arxiv.org/abs/2203.15514
Publikováno v:
IEEE Access, Vol 12, Pp 137893-137912 (2024)
The current trend in the literature on Time Series Classification is to develop increasingly accurate algorithms by combining multiple models in ensemble hybrids, representing time series in complex and expressive feature spaces, and extracting featu
Externí odkaz:
https://doaj.org/article/7605f7553e6448a4afe63fb72c806d07
Autor:
Fernanda Oliveira Gomes, Roberto Pellungrini, Anna Monreale, Chiara Renso, Jean Everson Martina
Publikováno v:
IEEE Access, Vol 12, Pp 136354-136378 (2024)
With the rise of the Internet of Things (IoT), social networks, and mobile devices, vast amounts of mobility data are continuously generated. These data encompass diverse location information from various sources, including smart vehicles, sensors, w
Externí odkaz:
https://doaj.org/article/fa735550146643e19833b1b0aa7bb9f0
Publikováno v:
Applied Sciences, Vol 14, Iss 17, p 8014 (2024)
With the exponential growth of mobility data generated by IoT, social networks, and mobile devices, there is a pressing need to address privacy concerns. Our work proposes methods to reduce the computation of privacy risk evaluation on mobility datas
Externí odkaz:
https://doaj.org/article/6a266324b1b441bd95998a4899fe3e54
Autor:
Peduzzi, Giulia, Felici, Alessio, Pellungrini, Roberto, Giorgolo, Francesca, Farinella, Riccardo, Gentiluomo, Manuel, Spinelli, Andrea, Capurso, Gabriele, Monreale, Anna, Canzian, Federico, Calderisi, Marco, Campa, Daniele
Publikováno v:
In Digestive and Liver Disease June 2024 56(6):1054-1063
Autor:
Rotelli, Daniela, Monreale, Anna
Research is constantly engaged in finding more productive and powerful ways to support quality learning and teaching. However, although researchers and data scientists try to analyse educational data most transparently and responsibly, the risk of tr
Externí odkaz:
http://arxiv.org/abs/2106.11071