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Anna Monreale
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A. Monreale
,
Trasarti, R.
,
Renso, C.
,
Pedreschi, D.
, and
Bogorny, V.
,
“
Preserving privacy in semantic-rich trajectories of human mobility
”
, in
SPRINGL
, 2010, pp. 47-54.
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F. Naretto
,
Pellungrini, R.
,
Nardini, F. Maria
, and
Giannotti, F.
,
“
Prediction and Explanation of Privacy Risk on Mobility Data with Neural Networks
”
, in
ECML PKDD 2020 Workshops
, Cham, 2020.
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F. Naretto
,
Pellungrini, R.
,
Monreale, A.
,
Nardini, F. Maria
, and
Musolesi, M.
,
“
Predicting and Explaining Privacy Risk Exposure in Mobility Data
”
, in
Discovery Science
, Cham, 2020.
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R. G. Pensa
,
Monreale, A.
,
Pinelli, F.
, and
Pedreschi, D.
,
“
Pattern-Preserving k-Anonymization of Sequences and its Application to Mobility Data Mining
”
, in
PiLBA
, 2008.
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V. Grossi
,
Guns, T.
,
Monreale, A.
,
Nanni, M.
, and
Nijssen, S.
,
“
Partition-Based Clustering Using Constraint Optimization
”
, in
Data Mining and Constraint Programming - Foundations of a Cross-Disciplinary Approach
, Springer International Publishing, 2016, pp. 282–299.
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O
D. Pedreschi
,
Giannotti, F.
,
Guidotti, R.
,
Monreale, A.
,
Pappalardo, L.
,
Ruggieri, S.
, and
Turini, F.
,
“
Open the Black Box Data-Driven Explanation of Black Box Decision Systems
”
, 2018.
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N
M. Fontana
,
Naretto, F.
, and
Monreale, A.
,
“
A new approach for cross-silo federated learning and its privacy risks
”
, in
18th International Conference on Privacy, Security and Trust, PST 2021, Auckland, New Zealand, December 13-15, 2021
, 2021.
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M
R. Trasarti
,
Guidotti, R.
,
Monreale, A.
, and
Giannotti, F.
,
“
MyWay: Location prediction via mobility profiling
”
,
Information Systems
, vol. 64, pp. 350–367, 2017.
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M. Berlingerio
,
Coscia, M.
,
Giannotti, F.
,
Monreale, A.
, and
Pedreschi, D.
,
“
Multidimensional networks: foundations of structural analysis
”
,
World Wide Web
, vol. Volume 15 / 2012, 2012.
DOI
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M. Magnani
,
Monreale, A.
,
Rossetti, G.
, and
Giannotti, F.
,
“
On multidimensional network measures
”
, in
SEDB 2013
, 2013.
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G. Andrienko
,
Andrienko, N.
,
Giannotti, F.
,
Monreale, A.
, and
Pedreschi, D.
,
“
Movement data anonymity through generalization
”
, in
Proceedings of the 2nd SIGSPATIAL ACM GIS 2009 International Workshop on Security and Privacy in GIS and LBS
, 2009.
DOI
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A. Monreale
,
Andrienko, G.
,
Andrienko, N.
,
Giannotti, F.
,
Pedreschi, D.
,
Rinzivillo, S.
, and
Wrobel, S.
,
“
Movement Data Anonymity through Generalization
”
,
Transactions on Data Privacy
, vol. 3, pp. 91–121, 2010.
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M. Fontana
,
Naretto, F.
,
Monreale, A.
, and
Giannotti, F.
,
“
Monitoring Fairness in HOLDA
”
, in
HHAI 2022: Augmenting Human Intellect - Proceedings of the First International Conference on Hybrid Human-Artificial Intelligence, Amsterdam, The Netherlands, 13-17 June 2022
, 2022.
DOI
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R. Pellungrini
,
Pappalardo, L.
,
Simini, F.
, and
Monreale, A.
,
“
Modeling Adversarial Behavior Against Mobility Data Privacy
”
,
IEEE Transactions on Intelligent Transportation SystemsIEEE Transactions on Intelligent Transportation Systems
, pp. 1 - 14, 2020.
DOI
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D. Pedreschi
,
Giannotti, F.
,
Guidotti, R.
,
Monreale, A.
,
Ruggieri, S.
, and
Turini, F.
,
“
Meaningful explanations of Black Box AI decision systems
”
, in
Proceedings of the AAAI Conference on Artificial Intelligence
, 2019.
DOI
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L
F. Pinelli
,
Monreale, A.
,
Trasarti, R.
, and
Giannotti, F.
,
“
Location prediction within the mobility data analysis environment Daedalus
”
,
First International Workshop on Computational Transportation Science
. Dublin, Ireland, 2008.
DOI
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A. Monreale
,
Pinelli, F.
,
Trasarti, R.
, and
Giannotti, F.
,
“
Location Prediction through Trajectory Pattern Mining (Extended Abstract)
”
, in
SEBD
, 2010, pp. 134-141.
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R. Guidotti
,
Monreale, A.
,
Ruggieri, S.
,
Pedreschi, D.
,
Turini, F.
, and
Giannotti, F.
,
“
Local Rule-Based Explanations of Black Box Decision Systems
”
, 2018.
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R. Guidotti
,
Monreale, A.
, and
Rinzivillo, S.
,
“
Learning Data Mining
”
, in
2018 IEEE 5th International Conference on Data Science and Advanced Analytics (DSAA)2018 IEEE 5th International Conference on Data Science and Advanced Analytics (DSAA)
, 2018.
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I
R. Guidotti
,
Monreale, A.
, and
Cariaggi, L.
,
“
Investigating Neighborhood Generation Methods for Explanations of Obscure Image Classifiers
”
, in
Pacific-Asia Conference on Knowledge Discovery and Data Mining
, 2019.
DOI
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S. Hajian
,
Monreale, A.
,
Pedreschi, D.
,
Domingo-Ferrer, J.
, and
Giannotti, F.
,
“
Injecting Discrimination and Privacy Awareness Into Pattern Discovery
”
, in
12th {IEEE} International Conference on Data Mining Workshops, {ICDM} Workshops, Brussels, Belgium, December 10, 2012
, 2012, pp. 360–369.
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H
G. Amato
,
Candela, L.
,
Castelli, D.
,
Esuli, A.
,
Falchi, F.
,
Gennaro, C.
,
Giannotti, F.
,
Monreale, A.
,
Nanni, M.
,
Pagano, P.
,
Pappalardo, L.
,
Pedreschi, D.
,
Pratesi, F.
,
Rabitti, F.
,
Rinzivillo, S.
,
Rossetti, G.
,
Ruggieri, S.
,
Sebastiani, F.
, and
Tesconi, M.
,
“
How Data Mining and Machine Learning Evolved from Relational Data Base to Data Science
”
, in
A Comprehensive Guide Through the Italian Database Research Over the Last 25 Years
,
S. Flesca
,
Greco, S.
,
Masciari, E.
, and
Saccà, D.
, Eds.
Cham: Springer International Publishing, 2018, pp. 287 - 306.
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G
M. Setzu
,
Guidotti, R.
,
Monreale, A.
,
Turini, F.
,
Pedreschi, D.
, and
Giannotti, F.
,
“
GLocalX - From Local to Global Explanations of Black Box AI Models
”
, vol. 294, p. 103457, 2021.
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M. Setzu
,
Guidotti, R.
,
Monreale, A.
, and
Turini, F.
,
“
Global Explanations with Local Scoring
”
, in
Machine Learning and Knowledge Discovery in Databases
, Cham, 2020.
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M. Nanni
,
Andrienko, G.
,
Barabasi, A. - L.
,
Boldrini, C.
,
Bonchi, F.
,
Cattuto, C.
,
Chiaromonte, F.
,
Comandé, G.
,
Conti, M.
,
Coté, M.
,
Dignum, F.
,
Dignum, V.
,
Domingo-Ferrer, J.
,
Ferragina, P.
,
Giannotti, F.
,
Guidotti, R.
,
Helbing, D.
,
Kaski, K.
,
Kertész, J.
,
Lehmann, S.
,
Lepri, B.
,
Lukowicz, P.
,
Matwin, S.
,
Jiménez, D. Megías
,
Monreale, A.
,
Morik, K.
,
Oliver, N.
,
Passarella, A.
,
Passerini, A.
,
Pedreschi, D.
,
Pentland, A.
,
Pianesi, F.
,
Pratesi, F.
,
Rinzivillo, S.
,
Ruggieri, S.
,
Siebes, A.
,
Torra, V.
,
Trasarti, R.
,
van den Hoven, J.
, and
Vespignani, A.
,
“
Give more data, awareness and control to individual citizens, and they will help COVID-19 containment
”
, 2021.
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