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F. Bonchi
,
Giannotti, F.
,
Mazzanti, A.
, and
Pedreschi, D.
,
“
ExAMiner: Optimized Level-wise Frequent Pattern Mining with Monotone Constraint
”
, in
ICDM
, 2003, pp. 11-18.
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M. Berlingerio
,
Coscia, M.
,
Giannotti, F.
,
Monreale, A.
, and
Pedreschi, D.
,
“
Evolving networks: Eras and turning points
”
,
Intell. Data Anal.
, vol. 17, pp. 27–48, 2013.
DOI
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F. Naretto
,
Monreale, A.
, and
Giannotti, F.
,
“
Evaluating the Privacy Exposure of Interpretable Global and Local Explainers
”
, in
Submitted at Journal of Artificial Intelligence and Law
, 2023.
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R. Cazabet
,
Boudebza, S.
, and
Rossetti, G.
,
“
Evaluating community detection algorithms for progressively evolving graphs
”
,
arXiv preprint arXiv:2007.08635
, 2020.
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S. Citraro
and
Rossetti, G.
,
“
Eva: Attribute-Aware Network Segmentation
”
, in
International Conference on Complex Networks and Their Applications
, 2019.
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N. Forgó
,
Hänold, S.
,
van den Hoven, J.
,
Krügel, T.
,
Lishchuk, I.
,
Mahieu, R.
,
Monreale, A.
,
Pedreschi, D.
,
Pratesi, F.
, and
van Putten, D.
,
“
An ethico-legal framework for social data science
”
, 2020.
DOI
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F. Lillo
and
Ruggieri, S.
,
“
Estimating the Total Volume of Queries to a Search Engine
”
,
IEEE Transactions on Knowledge and Data Engineering
, pp. 1-1, 2021.
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V. Voukelatou
,
Pappalardo, L.
,
Gabrielli, L.
, and
Giannotti, F.
,
“
Estimating countries’ peace index through the lens of the world news as monitored by GDELT
”
, in
2020 IEEE 7th International Conference on Data Science and Advanced Analytics (DSAA)2020 IEEE 7th International Conference on Data Science and Advanced Analytics (DSAA)
, 2020.
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A. Rossi
,
Pedreschi, D.
,
Clifton, D. A.
, and
Morelli, D.
,
“
Error Estimation of Ultra-Short Heart Rate Variability Parameters: Effect of Missing Data Caused by Motion Artifacts
”
,
Sensors
, vol. 20, p. 7122, 2020.
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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S. Ruggieri
,
“
Enumerating Distinct Decision Trees
”
, in
International Conference on Machine Learning
, 2017.
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A. Raffaetà
,
Turini, F.
, and
Renso, C.
,
“
Enhancing GISs for spatio-temporal reasoning
”
, in
ACM-GIS
, 2002, pp. 42-48.
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P. Cintia
,
Pappalardo, L.
, and
Pedreschi, D.
,
“
"Engine Matters": {A} First Large Scale Data Driven Study on Cyclists' Performance
”
, in
13th {IEEE} International Conference on Data Mining Workshops, {ICDM} Workshops, TX, USA, December 7-10, 2013
, 2013.
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P. Mukala
,
Cerone, A.
, and
Turini, F.
,
“
An empirical verification of a-priori learning models on mailing archives in the context of online learning activities of participants in free\libre open source software (FLOSS) communities
”
,
Education and Information Technologies
, vol. 22, pp. 3207–3229, 2017.
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A. Sirbu
,
Crane, M.
, and
Ruskin, H. J.
,
“
EGIA–Evolutionary Optimisation of Gene Regulatory Networks, an Integrative Approach
”
, in
Complex Networks V
, Springer International Publishing, 2014, pp. 217–229.
DOI
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P. Contucci
,
Panizzi, E.
,
Ricci-Tersenghi, F.
, and
Sirbu, A.
,
“
Egalitarianism in the rank aggregation problem: a new dimension for democracy
”
,
Quality & Quantity
, pp. 1–16, 2015.
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A. Baroni
,
Conte, A.
,
Patrignani, M.
, and
Ruggieri, S.
,
“
Efficiently Clustering Very Large Attributed Graphs
”
,
arXiv preprint arXiv:1703.08590
, 2017.
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F. Giannotti
,
Nanni, M.
, and
Pedreschi, D.
,
“
Efficient Mining of Temporally Annotated Sequences
”
, in
SDM
, 2006.
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K. S. Boeg
,
Ira Assent,
, and
Magnani, M.
,
“
Efficient GPU-based skyline computation
”
, in
DAMON@SIGMOD 2013
, 2013.
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F. Bonchi
,
Giannotti, F.
,
Mazzanti, A.
, and
Pedreschi, D.
,
“
Efficient breadth-first mining of frequent pattern with monotone constraints
”
,
Knowl. Inf. Syst.
, vol. 8, pp. 131-153, 2005.
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F. Giannotti
,
Manco, G.
,
Nanni, M.
, and
Pedreschi, D.
,
“
On the Effective Semantics of Nondeterministic, Nonmonotonic, Temporal Logic Databases
”
, in
CSL
, 1998, pp. 58-72.
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A. Rossi
,
Pappalardo, L.
,
Cintia, P.
,
F Iaia, M.
,
Fernàndez, J.
, and
Medina, D.
,
“
Effective injury forecasting in soccer with GPS training data and machine learning
”
,
PloS one
, vol. 13, p. e0201264, 2018.
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