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G
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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R. Guidotti
,
Monreale, A.
,
Nanni, M.
,
Giannotti, F.
, and
Pedreschi, D.
,
“
Clustering Individual Transactional Data for Masses of Users
”
, in
Proceedings of the 23rd ACM SIGKDD International Conference on Knowledge Discovery and Data Mining
, 2017.
DOI
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R. Guidotti
and
Coscia, M.
,
“
On the Equivalence Between Community Discovery and Clustering
”
, in
International Conference on Smart Objects and Technologies for Social Good
, 2017.
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R. Guidotti
,
Monreale, A.
,
Ruggieri, S.
,
Naretto, F.
,
Turini, F.
,
Pedreschi, D.
, and
Giannotti, F.
,
“
Stable and actionable explanations of black-box models through factual and counterfactual rules
”
,
Data Mining and Knowledge Discovery
, 2022.
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R. Guidotti
,
Gabrielli, L.
,
Monreale, A.
,
Pedreschi, D.
, and
Giannotti, F.
,
“
Discovering temporal regularities in retail customers’ shopping behavior
”
,
EPJ Data Science
, vol. 7, p. 6, 2018.
DOI
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R. Guidotti
,
Nanni, M.
,
Rinzivillo, S.
,
Pedreschi, D.
, and
Giannotti, F.
,
“
Never drive alone: Boosting carpooling with network analysis
”
,
Information Systems
, vol. 64, pp. 237–257, 2017.
DOI
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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
,
Rossetti, G.
,
Pappalardo, L.
,
Giannotti, F.
, and
Pedreschi, D.
,
“
Next Basket Prediction using Recurring Sequential Patterns
”
,
arXiv preprint arXiv:1702.07158
, 2017.
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R. Guidotti
,
Rossetti, G.
,
Pappalardo, L.
,
Giannotti, F.
, and
Pedreschi, D.
,
“
Personalized Market Basket Prediction with Temporal Annotated Recurring Sequences
”
,
IEEE Transactions on Knowledge and Data Engineering
, 2018.
DOI
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R. Guidotti
and
Rossetti, G.
,
“
“Know Thyself” How Personal Music Tastes Shape the Last. Fm Online Social Network
”
, in
International Symposium on Formal Methods
, 2019.
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R. Guidotti
and
Ruggieri, S.
,
“
Assessing the Stability of Interpretable Models
”
,
arXiv preprint arXiv:1810.09352
, 2018.
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R. Guidotti
,
Soldani, J.
,
Neri, D.
, and
Brogi, A.
,
“
Explaining successful docker images using pattern mining analysis
”
, in
Federation of International Conferences on Software Technologies: Applications and Foundations
, 2018.
DOI
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R. Guidotti
,
Monreale, A.
,
Giannotti, F.
,
Pedreschi, D.
,
Ruggieri, S.
, and
Turini, F.
,
“
Factual and Counterfactual Explanations for Black Box Decision Making
”
,
IEEE Intelligent Systems
, 2019.
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R. Guidotti
,
Coscia, M.
,
Pedreschi, D.
, and
Pennacchioli, D.
,
“
Going Beyond GDP to Nowcast Well-Being Using Retail Market Data
”
, in
Advances in Network Science
, Springer International Publishing, 2016, pp. 29–42.
DOI
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R. Guidotti
,
Soldani, J.
,
Neri, D.
,
Brogi, A.
, and
Pedreschi, D.
,
“
Helping your docker images to spread based on explainable models
”
, in
Joint European Conference on Machine Learning and Knowledge Discovery in Databases
, 2018.
DOI
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R. Guidotti
and
Berlingerio, M.
,
“
Where Is My Next Friend? Recommending Enjoyable Profiles in Location Based Services
”
, in
Complex Networks VII
, Springer International Publishing, 2016, pp. 65–78.
DOI
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R. Guidotti
,
Rossetti, G.
,
Pappalardo, L.
,
Giannotti, F.
, and
Pedreschi, D.
,
“
Market Basket Prediction using User-Centric Temporal Annotated Recurring Sequences
”
, in
2017 IEEE International Conference on Data Mining (ICDM)
, 2017.
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B. Guidi
,
Michienzi, A.
, and
Rossetti, G.
,
“
Towards the dynamic community discovery in decentralized online social networks
”
,
Journal of Grid Computing
, vol. 17, pp. 23–44, 2019.
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B. Guidi
,
Michienzi, A.
, and
Rossetti, G.
,
“
Dynamic community analysis in decentralized online social networks
”
, in
European Conference on Parallel Processing
, 2017.
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V. Grossi
,
Romei, A.
, and
Ruggieri, S.
,
“
A Case Study in Sequential Pattern Mining for IT-Operational Risk
”
, in
ECML/PKDD (1)
, 2008, pp. 424-439.
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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.
DOI
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V. Grossi
,
Monreale, A.
,
Nanni, M.
,
Pedreschi, D.
, and
Turini, F.
,
“
Clustering Formulation Using Constraint Optimization
”
, in
Software Engineering and Formal Methods - {SEFM} 2015 Collocated Workshops: ATSE, HOFM, MoKMaSD, and VERY*SCART, York, UK, September 7-8, 2015, Revised Selected Papers
, 2015.
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V. Grossi
,
Pedreschi, D.
, and
Turini, F.
,
“
Data Mining and Constraints: An Overview
”
, in
Data Mining and Constraint Programming
, Springer International Publishing, 2016, pp. 25–48.
DOI
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V. Grossi
,
Romei, A.
, and
Turini, F.
,
“
Survey on using constraints in data mining
”
,
Data Mining and Knowledge Discovery
, vol. 31, pp. 424–464, 2017.
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P. Gravino
,
Sirbu, A.
,
Becker, M.
,
Servedio, V. D. P.
, and
Loreto, V.
,
“
Experimental Assessment of the Emergence of Awareness and Its Influence on Behavioral Changes: The Everyaware Lesson
”
, in
Participatory Sensing, Opinions and Collective Awareness
, Springer, 2017, pp. 337–362.
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