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Roberto Confalonieri
Roberto Confalonieri
University of Padova, Department of Mathematics
Verified email at unipd.it - Homepage
Title
Cited by
Cited by
Year
Explainable Artificial Intelligence (XAI): What we know and what is left to attain Trustworthy Artificial Intelligence
S Ali, T Abuhmed, S El-Sappagh, K Muhammad, JM Alonso-Moral, ...
Information fusion 99, 101805, 2023
6272023
A historical perspective of explainable Artificial Intelligence
R Confalonieri, L Coba, B Wagner, TR Besold
Wiley Interdisciplinary Reviews: Data Mining and Knowledge Discovery 11 (1 …, 2021
3872021
Explainable Artificial Intelligence (XAI) 2.0: A manifesto of open challenges and interdisciplinary research directions
L Longo, M Brcic, F Cabitza, J Choi, R Confalonieri, J Del Ser, R Guidotti, ...
Information Fusion 106, 102301, 2024
1492024
Using ontologies to enhance human understandability of global post-hoc explanations of black-box models
R Confalonieri, T Weyde, TR Besold, FM del Prado Martín
Artificial Intelligence 296, 103471, 2021
1192021
A computational framework for conceptual blending
M Eppe, E Maclean, R Confalonieri, O Kutz, M Schorlemmer, E Plaza, ...
Artificial Intelligence 256, 105-129, 2018
1102018
Trepan reloaded: A knowledge-driven approach to explaining black-box models
R Confalonieri, T Weyde, TR Besold, F Moscoso del Prado Martín
ECAI 2020, 2457-2464, 2020
80*2020
Repairing ontologies via axiom weakening
N Troquard, R Confalonieri, P Galliani, R Penaloza, D Porello, O Kutz
Proceedings of the AAAI Conference on Artificial Intelligence 32 (1), 2018
712018
Computational invention of cadences and chord progressions by conceptual chord-blending
M Eppe, R Confalonieri, E Maclean, M Kaliakatsos, E Cambouropoulos, ...
Proceedings of the Twenty-Fourth International Joint Conference on …, 2015
572015
Upward refinement operators for conceptual blending in the description logic
R Confalonieri, M Eppe, M Schorlemmer, O Kutz, R Penaloza, E Plaza
Annals of Mathematics and Artificial Intelligence 82, 69-99, 2018
49*2018
Using argumentation to evaluate concept blends in combinatorial creativity
R Confalonieri, J Corneli, A Pease, E Plaza, M Schorlemmer
Proceedings of the Sixth International Conference on Computational …, 2015
292015
Concept invention
R Confalonieri, A Pease, M Schorlemmer, TR Besold, O Kutz, E Maclean, ...
Springer, 2018
282018
What makes a good explanation? Cognitive dimensions of explaining intelligent machines.
R Confalonieri, TR Besold, T Weyde, K Creel, T Lombrozo, ST Mueller, ...
CogSci, 25-26, 2019
262019
Two approaches to ontology aggregation based on axiom weakening
D Porello, N Troquard, O Kutz, R Penaloza, R Confalonieri, P Galliani
252018
ASP, amalgamation, and the conceptual blending workflow
M Eppe, E Maclean, R Confalonieri, O Kutz, M Schorlemmer, E Plaza
Logic Programming and Nonmonotonic Reasoning: 13th International Conference …, 2015
242015
Engineering multiuser museum interactives for shared cultural experiences
R Confalonieri, M Yee-King, K Hazelden, D de Jonge, N Osman, C Sierra, ...
Engineering Applications of Artificial Intelligence 46, 180-195, 2015
21*2015
Possibilistic semantics for logic programs with ordered disjunction
R Confalonieri, JC Nieves, M Osorio, J Vázquez-Salceda
International Symposium on Foundations of Information and Knowledge Systems …, 2010
212010
Towards even more irresistible axiom weakening
R Confalonieri, P Galliani, O Kutz, D Porello, G Righetti, N Toquard
202020
The Yoneda path to the Buddhist monk blend
M Schorlemmer, R Confalonieri, E Plaza
202016
A possibilistic argumentation decision making framework with default reasoning
JC Nieves, R Confalonieri
Fundamenta Informaticae 113 (1), 41-61, 2011
202011
RecoXplainer: a library for development and offline evaluation of explainable recommender systems
L Coba, R Confalonieri, M Zanker
IEEE Computational Intelligence Magazine 17 (1), 46-58, 2022
192022
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Articles 1–20