| Returners and explorers dichotomy in human mobility L Pappalardo, F Simini, S Rinzivillo, D Pedreschi, F Giannotti, ... Nature communications 6 (1), 8166, 2015 | 548 | 2015 |
| Measuring objective and subjective well-being: dimensions and data sources V Voukelatou, L Gabrielli, I Miliou, S Cresci, R Sharma, M Tesconi, ... International Journal of Data Science and Analytics 11, 279-309, 2021 | 370 | 2021 |
| Effective injury forecasting in soccer with GPS training data and machine learning A Rossi, L Pappalardo, P Cintia, FM Iaia, J Fernández, D Medina PloS one 13 (7), e0201264, 2018 | 356 | 2018 |
| A survey on deep learning for human mobility M Luca, G Barlacchi, B Lepri, L Pappalardo ACM Computing Surveys (CSUR) 55 (1), 1-44, 2021 | 290* | 2021 |
| PlayeRank: data-driven performance evaluation and player ranking in soccer via a machine learning approach L Pappalardo, P Cintia, P Ferragina, E Massucco, D Pedreschi, ... ACM Transactions on Intelligent Systems and Technology (TIST) 10 (5), 1-27, 2019 | 235 | 2019 |
| A public data set of spatio-temporal match events in soccer competitions L Pappalardo, P Cintia, A Rossi, E Massucco, P Ferragina, D Pedreschi, ... Scientific data 6 (1), 236, 2019 | 229 | 2019 |
| A deep gravity model for mobility flows generation F Simini, G Barlacchi, M Luca, L Pappalardo Nature communications 12 (1), 6576, 2021 | 193 | 2021 |
| Using big data to study the link between human mobility and socio-economic development L Pappalardo, D Pedreschi, Z Smoreda, F Giannotti 2015 IEEE international conference on big data (big data), 871-878, 2015 | 178 | 2015 |
| scikit-mobility: A Python library for the analysis, generation and risk assessment of mobility data L Pappalardo, F Simini, G Barlacchi, R Pellungrini Journal of Statistical Software 103 (4), 1-38, 2022 | 165 | 2022 |
| Data-driven generation of spatio-temporal routines in human mobility L Pappalardo, F Simini Data Mining and Knowledge Discovery, 2017 | 159 | 2017 |
| Tiles: an online algorithm for community discovery in dynamic social networks G Rossetti, L Pappalardo, D Pedreschi, F Giannotti Machine Learning 106, 1213-1241, 2017 | 158 | 2017 |
| An analytical framework to nowcast well-being using mobile phone data L Pappalardo, M Vanhoof, L Gabrielli, Z Smoreda, D Pedreschi, ... International Journal of Data Science and Analytics, 2016 | 158 | 2016 |
| Understanding the patterns of car travel L Pappalardo, S Rinzivillo, Z Qu, D Pedreschi, F Giannotti The European Physical Journal Special Topics 215, 61-73, 2013 | 140 | 2013 |
| Small area model-based estimators using big data sources S Marchetti, C Giusti, M Pratesi, N Salvati, F Giannotti, D Pedreschi, ... Journal of Official Statistics 31 (2), 263-281, 2015 | 139 | 2015 |
| The harsh rule of the goals: Data-driven performance indicators for football teams P Cintia, F Giannotti, L Pappalardo, D Pedreschi, M Malvaldi 2015 IEEE International Conference on Data Science and Advanced Analytics …, 2015 | 137 | 2015 |
| Human migration: The big data perspective A Sîrbu, G Andrienko, N Andrienko, C Boldrini, M Conti, F Giannotti, ... International Journal of Data Science and Analytics 11, 341-360, 2021 | 129 | 2021 |
| Quantifying the relation between performance and success in soccer L Pappalardo, P Cintia Advances in Complex Systems, https://doi.org/10.1142/S021952591750014X, 2017 | 94 | 2017 |
| A network-based approach to evaluate the performance of football teams P Cintia, S Rinzivillo, L Pappalardo Machine learning and data mining for sports analytics workshop, Porto, Portugal, 2015 | 94 | 2015 |
| Living in a pandemic: changes in mobility routines, social activity and adherence to COVID-19 protective measures L Lucchini, S Centellegher, L Pappalardo, R Gallotti, F Privitera, B Lepri, ... Scientific reports 11 (1), 24452, 2021 | 81 | 2021 |
| Gravity and scaling laws of city to city migration R Prieto Curiel, L Pappalardo, L Gabrielli, SR Bishop PloS one 13 (7), e0199892, 2018 | 77 | 2018 |
Dino PedreschiProfessor of Computer Science, University of Pisadi.unipi.it의 이메일 확인됨