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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.
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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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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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A. Raffaetà
,
Turini, F.
, and
Renso, C.
,
“
Enhancing GISs for spatio-temporal reasoning
”
, in
ACM-GIS
, 2002, pp. 42-48.
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S. Ruggieri
,
“
Enumerating Distinct Decision Trees
”
, in
International Conference on Machine Learning
, 2017.
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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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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.
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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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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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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.
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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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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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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.
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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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F. Turini
,
Baglioni, M.
,
Furletti, B.
, and
Rinzivillo, S.
,
“
Examples of Integration of Induction and Deduction in Knowledge Discovery
”
, in
Reasoning, Action and Interaction in AI Theories and Systems
, 2006, pp. 307-326.
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F. Turini
,
Baglioni, M.
,
Furletti, B.
, and
Rinzivillo, S.
,
“
Examples of Integration of Induction and Deduction in Knowledge Discovery
”
, in
Reasoning, Action and Interaction in AI Theories and Systems
, vol. 4155, 2006, pp. 307-326.
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F. Bonchi
,
Giannotti, F.
,
Mazzanti, A.
, and
Pedreschi, D.
,
“
Exante: A Preprocessing Method for Frequent-Pattern Mining
”
,
IEEE Intelligent Systems
, vol. 20, pp. 25-31, 2005.
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F. Bonchi
,
Giannotti, F.
,
Mazzanti, A.
, and
Pedreschi, D.
,
“
ExAnte: Anticipated Data Reduction in Constrained Pattern Mining
”
, in
PKDD
, 2003, pp. 59-70.
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G. Rossetti
,
“
Exorcising the Demon: Angel, Efficient Node-Centric Community Discovery
”
, in
International Conference on Complex Networks and Their Applications
, 2019.
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F. Giannotti
,
Manco, G.
,
Pedreschi, D.
, and
Turini, F.
,
“
Experiences with a Logic-based knowledge discovery Support Environment
”
, in
1999 ACM SIGMOD Workshop on Research Issues in Data Mining and Knowledge Discovery
, 1999.
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F. Giannotti
,
Manco, G.
,
Pedreschi, D.
, and
Turini, F.
,
“
Experiences with a Logic-Based Knowledge Discovery Support Environment
”
, in
AI*IA
, 1999, pp. 202-213.
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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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F. Bodria
,
Panisson, A.
,
Perotti, A.
, and
Piaggesi, S.
,
“
Explainability Methods for Natural Language Processing: Applications to Sentiment Analysis.
”
, in
SEBD
, 2020.
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F. Bodria
,
“
Explaining Black Box with visual exploration of Latent Space
”
, in
EuroVis
, 2022.
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C. Panigutti
,
Guidotti, R.
,
Monreale, A.
, and
Pedreschi, D.
,
“
Explaining multi-label black-box classifiers for health applications
”
, in
International Workshop on Health Intelligence
, 2019.
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