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M. Nanni and Trasarti, R., Querying and mining trajectories with gaps: a multi-path reconstruction approach (Extended Abstract), in SEBD, 2010, pp. 126-133.
M. Nanni, Raffaetà, A., Renso, C., and Turini, F., \newblock{A Declarative Framework for Reasoning on Spatio-temporal Data}, 2004.
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.
M. Nanni, Trasarti, R., Furletti, B., Gabrielli, L., Van Der Mede, P., De Bruijn, J., de Romph, E., and Bruil, G., Transportation Planning Based on {GSM} Traces: {A} Case Study on Ivory Coast, in Citizen in Sensor Networks - Second International Workshop, CitiSens 2013, Barcelona, Spain, September 19, 2013, Revised Selected Papers, 2013.
M. Nanni, Raffaetà, A., Renso, C., and Turini, F., Deductive and Inductive Reasoning on Trajectories, in SEBD, 2004, pp. 98-105.
M. Nanni, Raffaetà, A., Renso, C., and Turini, F., Deductive and Inductive Reasoning on Spatio-Temporal Data, in INAP/WLP, 2004, pp. 98-115.
M. Nanni and Trasarti, R., K-BestMatch Reconstruction and Comparison of Trajectory Data, in ICDM Workshops, 2009, pp. 610-615.
M. Nanni and Trasarti, R., K-BestMatch Reconstruction and Comparison of Trajectory Data, in ICDM Workshops, 2009, pp. 610-615.
M. Nanni, Trasarti, R., and Giannotti, F., Movement Behaviour Recognition for Water Activities, in Personal Analytics and Privacy. An Individual and Collective Perspective - First International Workshop, {PAP} 2017, Held in Conjunction with {ECML} {PKDD} 2017, Skopje, Macedonia, September 18, 2017, Revised Selected Papers, 2017.
M. Nanni, Trasarti, R., Furletti, B., Gabrielli, L., Van Der Mede, P., De Bruijn, J., de Romph, E., and Bruil, G., MP4-A Project: Mobility Planning For Africa, in In D4D Challenge @ 3rd Conf. on the Analysis of Mobile Phone datasets (NetMob 2013), Cambridge, USA, 2013.
M. Nanni, Trasarti, R., Monreale, A., Grossi, V., and Pedreschi, D., Driving Profiles Computation and Monitoring for Car Insurance CRM, Journal ACM Transactions on Intelligent Systems and Technology (TIST), vol. 8, pp. 14:1–14:26, 2016.
M. Nanni, Raffaetà, A., Renso, C., and Turini, F., Spatio-Temporal Data, Spatio-Temporal Databases: Flexible Querying and Reasoning, p. 75, 2013.
M. Nanni, Trasarti, R., Cintia, P., Furletti, B., Renso, C., Gabrielli, L., Rinzivillo, S., and Giannotti, F., Mobility Profiling, in Data Science and Simulation in Transportation Research, IGI Global, 2014, pp. 1-29.
M. Nanni, Kuijpers, B., Körner, C., May, M., and Pedreschi, D., Spatiotemporal Data Mining, in Mobility, Data Mining and Privacy, 2008, pp. 267-296.
M. Nanni and Pedreschi, D., Time-focused clustering of trajectories of moving objects, J. Intell. Inf. Syst., vol. 27, pp. 267-289, 2006.
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.
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.
F. Naretto, Pellungrini, R., Fadda, D., and Rinzivillo, S., EXPHLOT: EXplainable Privacy assessment for Human LOcation Trajectories, in Discovery Science , 2023.
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.
M. Natilli and Romano, M. Francesca, The impact of wine and food tourism in Italy: an analysis of official statistical data at province level, in First European Conference on Wine and Food Tourism, 2011.
M. Natilli, Rossi, A., Trecroci, A., Cavaggioni, L., Merati, G., and Formenti, D., The long-tail effect of the COVID-19 lockdown on Italians’ quality of life, sleep and physical activity, Scientific Data, vol. 9, pp. 1–10, 2022.
M. Natilli, Fadda, D., Rinzivillo, S., Pedreschi, D., and Licari, F., Analysis and Visualization of Performance Indicators in University Admission Tests, in Formal Methods. FM 2019 International Workshops, Cham, 2020.
M. Natilli, Monreale, A., Guidotti, R., and Pappalardo, L., Exploring Students Eating Habits Through Individual Profiling and Clustering Analysis, in ECML PKDD 2018 Workshops, 2018.
A. Rita Nogueira, Pugnana, A., Ruggieri, S., Pedreschi, D., and Gama, J., Methods and tools for causal discovery and causal inference, WIREs Data Mining Knowl. Discov., vol. 12, 2022.
E. Ntoutsi, Fafalios, P., Gadiraju, U., Iosifidis, V., Nejdl, W., Vidal, M. - E., Ruggieri, S., Turini, F., Papadopoulos, S., Krasanakis, E., and others, Bias in data-driven artificial intelligence systems—An introductory survey, Wiley Interdisciplinary Reviews: Data Mining and Knowledge Discovery, vol. 10, p. e1356, 2020.

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