Publications

2019

  • Modeling Adversarial Behavior Against Mobility Data Privacy
    R. Pellungrini, A. Monreale, L. Pappalardo, F. Simini
    submitted, 2019.


  • Explainable Injury Forecasting in Soccer via Multivariate Time Series and Convolutional Neural Networks
    L. Pappalardo, L. Guerrini, A. Rossi, P. Cintia
    BARÇA Sports Analytics Summit, 2019
    [PDF]

  • scikit-mobility: a Python library for the analysis, generation and risk assessment of mobility data
    L. Pappalardo, F. Simini, G. Barlacchi, R. Pellungrini
    submitted, 2019
    [arxiv] [PDF] [github]


  • Measuring objective and subjective well-being: dimensions and data sources
    V. Voukelatou, L. Gabrielli, I. Miliou, S. Cresci, R. Sharma, M. Tesconi, L. Pappalardo
    to appear on International Journal of Data Science and Analytics (JDSA), 2019

  • Human Migration: the Big Data perspective
    A. Sirbu, G. Andrienko, N. Andrienko, C. Boldrini, M. Conti, F. Giannotti, R. Guidotti, S. Bertoli, J. Kim, C. I. Muntean, L. Pappalardo, A. Passarella, D. Pedreschi, L. Pollacci, F. Pratesi, R. Sharma
    submitted to International Journal of Data Science and Analytics (JDSA), 2019


  • A public data set of spatio-temporal match events in soccer competitions
    L. Pappalardo, P. Cintia, A. Rossi, P. Ferragina, E. Massucco, D. Pedreschi, F. Giannotti
    Nature Scientific Data 6:236, 2019
    [PDF] [Nature] [figshare] [blog post]
    SCImago Journal & Country Rank


  • 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, F. Giannotti
    ACM Transactions on Intelligent Systems and Technology (TIST) 10:5, 2019, DOI: 10.1145/3343172
    [PDF] [ACM] [github]
    Press Coverage: [IlSole24Ore]
    SCImago Journal & Country Rank


  • Understanding Societal Well-Being Through the Eyes of the News World Media
    V. Voukelatou, L. Pappalardo, F. Giannotti
    HUSO 2019, The Fifth International Conference on Human and Social Analytics, 2019.
    [PDF]


    2018

  • Personalized Market Basket Prediction with Temporal Annotated Recurring Sequences
    R. Guidotti, G. Rossetti, L. Pappalardo, F. Giannotti, D. Pedreschi,
    IEEE Transactions on Knowledge and Data Engineering (TKDE), 10.1109/TKDE.2018.2872587, 2018.
    [PDF] [ieeexplore]
    SCImago Journal & Country Rank


  • Weak nodes detection in urban transport systems: Planning for resilience in Singapore
    M. Ferretti, G. Barlacchi, L. Lucchini, L. Pappalardo, B. Lepri
    In Proceedings of the 2018 IEEE International Conference on Data Science and Analytics, 2018.
    [PDF] [arxiv] [research gate]


  • Effective injury prediction in professional soccer with GPS training data and machine learning
    A. Rossi, L. Pappalardo, P. Cintia, M. Iaia, J. Fernandez, D. Medina
    PLoS One, 13(7), https://doi.org/10.1371/journal.pone.0201264, 2018
    [PDF] [PLoS One] [arxiv] [research gate]Press coverage: [El Pais] [Wired] [New Scientist] [Gazzetta dello Sport] [IlSole24Ore] [La Repubblica] [ANSA] [Le Scienze] [La Repubblica] [com.unica] [sport fair] [interview on Radio Capital (from 12:09)] [interview on NTN24]
    SCImago Journal & Country Rank


  • Gravity and Scaling laws of city to city migration
    R. Prieto Curiel, L. Pappalardo, L. Gabrielli, S. Bishop
    PLoS One 13(7), https://doi.org/10.1371/journal.pone.0199892, 2018
    [PDF] [PLoS One] [research gate]
    SCImago Journal & Country Rank


  • Gastroesophageal reflux symptoms among Italian university students: epidemiology and dietary correlates using automatically recorded transactions
    I. Martinucci, M. Natilli, V. Lorenzoni, L. Pappalardo, A. Monreale, G. Turchetti, D. Pedreschi, S. Marchi, R. Barale, N. de Bortoli
    BMC Gastroenterology, 18(116), doi:10.1186/s12876-018-0832-9, 2018
    [PDF] [Springer] [research gate]
    SCImago Journal & Country Rank


  • Analyzing privacy risk in human mobility data
    R. Pellungrini, L. Pappalardo, F. Pratesi, A. Monreale
    7th International Symposium “From Data to Models and Back (DataMod)”, 2018

  • Prediction of next career moves from scientific profiles
    C. James, L. Pappalardo, A. Sirbu, F. Simini
    submitted, 2018
    [arxiv]


  • Human perception of performance
    L. Pappalardo, P. Cintia, D. Pedreschi, F. Giannotti, A.-L. Barabasi,
    [arxiv] submitted, 2018Press coverage: [IlSole24Ore] [MIT Technology Review]


    2017

  • Data-driven generation of spatio-temporal routines in human mobility
    L. Pappalardo, F. Simini
    Data Mining and Knowledge Discovery, doi:10.1007/s10618-017-0548-4, 2017.
    [PDF] [Springer] [arxiv] [research gate] [Python code]
    SCImago Journal & Country Rank


  • A data mining approach to estimate privacy risk in human mobility data
    R. Pellungrini, L. Pappalardo, F. Pratesi, A. Monreale
    ACM Transactions on Intelligent Systems and Technology (TIST), 9(3), pp. 31:1–31:27, doi:10.1145/3106774, 2018.
    [PDF] [ACM] [research gate] [special issue] [Python code]
    SCImago Journal & Country Rank


  • Quantifying the relation between performance and success in soccer
    L. Pappalardo, P. Cintia
    Advances in Complex Systems, doi:10.1142/S021952591750014X, 2017.
    [PDF] [bibtex] [ACS] [arxiv] [research gate]
    SCImago Journal & Country Rank


  • Market Basket prediction using user-centric temporal annotated recurring sequences
    Riccardo Guidotti, Giulio Rossetti, Luca Pappalardo, Fosca Giannotti, Dino Pedreschi
    In Proceedings of the IEEE 17th International Conference on Data Mining (ICDM), 10.1109/ICDM.2017.111, 2017.
    [PDF] [bibtex] [IEEE] [arxiv]


  • A visual data-driven and network-based tool for transportation planning and simulation
    Michele Ferretti, Luca Pappalardo, Gianni Barlacchi, Bruno Lepri
    In Proceedings of the 2017 International Conference on Information and Knowledge Management (CIKM), Analyticup in DataSpark Mobility, finalist report, Singapore, 2017.
    [PDF] [research gate] [slides] [interview]


  • Who is going to get hurt? Predicting injuries in professional soccer
    A. Rossi, L. Pappalardo, P. Cintia, J. Fernandez, M. F. Iaia, D. Medina
    In Proceedings of the Machine Learning and Data Mining for Sports Analytics workshop (MLSA’17), ECML/PKDD 2017, Skopje, Macedonia.
    [PDF] [research gate] [slides]


  • Assessing privacy risk in retail data
    R. Pellungrini, F. Pratesi, L. Pappalardo
    International Workshop on Personal Analytics and Privacy, doi: 10.1007/978-3-319-71970-2_3, 2017.
    [PDF] [research gate]


  • Fast estimation of privacy risk in human mobility data
    R. Pellungrini, L. Pappalardo, F. Pratesi, A. Monreale
    3rd IEEE/ACM International Workshop on TEchnical and LEgal aspects of data pRIvacy and SEcurity, TELERISE 2017, Trento, Italy, September 12, 2017.
    [PDF] [research gate]


    2016

  • Homophilic network decomposition: a community-centric analysis of online social services
    G. Rossetti, L. Pappalardo, Riivo Kikas, Dino Pedreschi, Fosca Giannotti, Marlon Dumas
    Social Network Analysis and Mining (SNAM), 6:103, doi:10.1007/s13278-016-0411-4, 2016.
    [PDF] [bibtex] [Springer] [research gate]
    SCImago Journal & Country Rank


  • Tiles: an online algorithm for community discovery in dynamic social networks
    G. Rossetti, L. Pappalardo, D. Pedreschi, F. Giannotti
    Machine Learning, doi:10.1007/s10994-016-5582-8, 2016.
    [PDF] [bibtex] [Springer] [research gate] [Python code]
    SCImago Journal & Country Rank


  • The Haka Network: Evaluating Rugby Team Performance with Dynamic Graph Analysis
    P. Cintia, M. Coscia, L. Pappalardo
    Dyno: The Second International Workshop on Dynamics in Networks, 2016
    [PDF] [bibtex] [ieeexplore] [research gate] [blog]


  • An analytical framework to nowcast well-being using mobile phone data
    L. Pappalardo, M. Vanhoof, L. Gabrielli, Z. Smoreda, D. Pedreschi, F. Giannotti
    International Journal of Data Science and Analytics (JDSA), doi:10.1007/s41060-016-0013-2, 2016.
    [PDF] [bibtex] [Springer] [arxiv] [research gate]


  • Human mobility modelling: exploration and preferential return meet the gravity model
    L. Pappalardo, S. Rinzivillo, F. Simini
    Proceedings of ABMTRANS 2016: the 5th International Workshop on Agent-based Mobility, Traffic and Transportation Models, Methodologies and Applications, Madrid, Spain, 2016
    [PDF] [bibtex] [ScienceDirect] [research gate] [best paper award]


  • The origin of heterogeneity in human mobility ranges
    L. Pappalardo
    Proceedings of the Workshops of the EDBT/ICDT 2016 Joint Conference, EDBT/ICDT Workshops 2016, Bordeaux, France, 2016.
    [PDF] [bibtex] [research gate]


  • A novel approach to evaluate community detection algorithms on ground truth
    G. Rossetti, L. Pappalardo, S. Rinzivillo
    Proceedings of the 7th Workshop on Complex Networks (Complenet2016), Dijon, France, 2016
    [PDF] [bibtex] [research gate] [Python code]


    2015

  • Returners and Explorers dichotomy in Human Mobility
    L. Pappalardo, F. Simini, S. Rinzivillo, D. Pedreschi, F. Giannotti, A.-L. Barabási
    Nature Communications, 6:8166 doi: 10.1038/ncomms9166, 2015.   OPEN ACCESS
    [PDF] [Supplementary Materials] [bibtex] [Nature] [research gate] [paper metrics]Press coverage: [bigdatatales] [news and press]
    SCImago Journal & Country Rank


  • Using Big Data to study the link between human mobility and socio-economic development
    L. Pappalardo, Z. Smoreda, D. Pedreschi, F. Giannotti
    Proceedings of the 2015 IEEE International conference on Big Data (IEEE BigData 2015), Santa Clara, CA, USA
    [PDF] [bibtex] [ieeexplore] [research gate]


  • The harsh rule of the goals: data-driven performance indicators for football teams
    P. Cintia, L. Pappalardo, D. Pedreschi, F. Giannotti, M. Malvaldi
    In Proceedings of the 2015 IEEE International Conference on Data Science and Advanced Analytics (DSAA’2015), Paris, France
    [PDF] [bibtex] [ieeexplore] [research gate]


  • A network-based approach to evaluate the performance of football teams
    P. Cintia, S. Rinzivillo and L. Pappalardo
    In Proceedings of the Machine Learning and Data Mining for Sports Analytics workshop (MLSA’15), ECML/PKDD 2015, Porto, Portugal
    [PDF] [research gate]
    [bigdatatales]


  • Community-centric analysis of user engagement in Skype social network
    G. Rossetti, L. Pappalardo, R. Kikas, D. Pedreschi, F. Giannotti, M. Dumas
    In Proceedings of the 2015 IEEE/ACM International Conference on Advances in Social Network Analysis and Mining (ASONAM’15), Paris. France
    [PDF] [bibtex] [acm digital library] [research gate]


  • Small Area Model-Based Estimators Using Big Data Sources
    S. Marchetti, C. Giusti, M. Pratesi, N. Salvati, F. Giannotti, D. Pedreschi, S. Rinzivillo, L. Pappalardo, L. Gabrielli
    Journal of Official Statistics (JOS), 31(2), pp. 263-281, June 2015.   OPEN ACCESS
    [PDF] [bibtex] [degruyter] [research gate] [academia]
    SCImago Journal & Country Rank


    2014

  • The Purpose of Motion: Learning Activities from Individual Mobility Networks
    S. Rinvizillo, L. Gabrielli, M. Nanni, L. Pappalardo, D. Pedreschi, F. Giannotti
    In Proceedings of the 2014 IEEE International Conference on Data Science and Advanced Analytics (DSAA’2014), Shanghai, China
    [PDF] [bibtex] [ieeexplore] [research gate] [academia]


  • Mining efficient training patterns of non-professional cyclists
    P. Cintia, L. Pappalardo, D. Pedreschi
    22th Italian Symposium on Advanced Database SysNature Scientific Datatems (SEBD 2014), 2014
    [PDF] [bibtex]


  • The patterns of musical influence on the Last.Fm social network
    D. Pennacchioli, G. Rossetti, L. Pappalardo, D. Pedreschi, F. Giannotti, M. Coscia
    22th Italian Symposium on Advanced Database Systems (SEBD 2014), 2014
    [PDF] [bibtex]


    2013

  • “Engine matters:”  a first large scale data driven study on cyclists’ performance
    P. Cintia, L. Pappalardo, D. Pedreschi
    Proceedings of the IEEE 13th International Conference on Data Mining (ICDM 2013) Workshops, 2013
    [PDF] [bibtex] [ieeexplore] [acm digital library] [research gate] [academia]Press coverage: [big data tales] [cycling science]


  • The Three Dimensions of Social Prominence
    D. Pennacchioli, G. Rossetti, L. Pappalardo, D. Pedreschi, F. Giannotti, M. Coscia
    Proceedings of the 5th International Conference on Social Informatics (SocInfo2013), 2013
    [PDF] [bibtex] [code] [Springer] [acm digital library] [research gate] [academia]


  • Comparing general mobility and mobility by car
    L. Pappalardo, F. Simini, S. Rinzivillo, D. Pedreschi, F. Giannotti
    BRICS Countries Congress (BRICS-CCI) and 11th Brazilian Congress (CBIC) on Computational Intelligence, 2013
    [PDF] [ieeexplore] [acm digital library] [research gate]


  • Measuring tie strength in multidimensional social networks
    L. Pappalardo, G. Rossetti, D. Pedreschi
    21th Italian Symposium on Advanced Database Systems (SEBD 2013), 2013
    [PDF]


  • Validating general human mobility patterns on GPS data
    L. Pappalardo, S. Rinzivillo, D. Pedreschi, F. Giannotti
    21th Italian Symposium on Advanced Database Systems (SEBD 2013), 2013
    [PDF]


  • Understanding the patterns of car travel
    L. Pappalardo, S. Rinzivillo, Z. Qu, D. Pedreschi, F. Giannotti
    The European Physical Journal (EPJ) – Special Topics, vol. 215 (1), pp. 61-73, Springer, 2013.
    [PDF] [bibtex] [springer website] [research gate] [academia]SCImago Journal & Country Rank


    2012

  • “How well do we know each other?”: Detecting tie strength in multidimensional social networks
    L. Pappalardo, G. Rossetti, D. Pedreschi
    IEEE/ACM International Conference on Advance in Social Network Analysis and Mining (ASONAM 2012) Workshops 2012, pp. 1040-1045, Proceedings, 2012.
    [PDF] [bibtex] [ieeexplore] [acm digital library] [research gate] [academia]


Book Chapters

  • How Data Mining and Machine Learning evolved from Relational Data Base to Data Science
    G. Amato, L. Candela, D. Castelli, A. Esuli, F. Falchi, C. Gennaro, F. Giannotti, A. MonrealeM. Nanni, P. Pagano, L. Pappalardo, D. Pedreschi, F. Pratesi, F. Rabitti, S. Rinzivillo, G. Rossetti, S. Ruggieri, F. Sebastiani, M. Tesconi
    in A Comprehensive Guide Through the Italian Database Research Over the Last 25 Years, Volume 31 of the series Studies in Big Data pp 287-306, 2017.
    [PDF] [Springer]


  • Capire la mobilità attraverso i Big Data
    L. Pappalardo and F. Giannotti
    in Tempo di Cambiare: rapporto 2015 sulle migrazioni interne in Italia, Donzelli editore, ISBN: 9788868434076, 2015.
    [PDF] [donzelli]


  • Evaluation of Spatio-temporal Microsimulation Systems
    C. Kopp, B. Kochan, M. May, L. Pappalardo, S. Rinzivillo, D. Schulz, F. Simini
    in Data Science and Simulation in Transportation Research, Chapter 8, pp. 141-166, Davy Janssens, Ansar-Ul-Haque Yasar, Luk Knapen (eds.), Hershey, USA: IGI global, 2014.
    [PDF] [bibtex] [IGIglobal]


  • A complexity science perspective on human mobility
    F. Giannotti, L. Pappalardo, D. Pedreschi, D. Wang
    in Mobility Data – Modeling, Management, and Understanding, pp. 297-313. Chiara Renso, Stefano Spaccapietra, Esteban Zimanyi (eds.), New York, USA: Cambridge University Press, 2013.
    [PDF] [Cambridge Press] [bibtex]


  • Mobility and geo-social networks
    L. Spinsanti, M. Berlingerio, L. Pappalardo,
    in Mobility Data – Modeling, Management, and Understanding, pp. 315-333. Chiara Renso, Stefano Spaccapietra, Esteban Zimanyi (eds.), New York, USA: Cambridge University Press, 2013.
    [PDF] [Cambridge Press] [bibtex]


Technical Reports
  • Semantically enriched socio-mobility patterns and social network models: preliminary results
    F. Giannotti, G. Andrienko, B. Furletti, C. Koerner, F. Liu, M. Nanni, L. Pappalardo, D. Pedreschi, N. Pelekis, C. Renso, S. Rinzivillo
    deliverable D2.1 of work package WP2, DATASIM European project FP7-ICT (FET Open) #270833
    [PDF]


  • Development of a Novel Evaluation and Benchmarking Standard
    D. Schulz, B. Kochan, C. Kopp, M. May, L. Pappalardo, N. Pelekis, S. Rinzivillo, F. Simini, M. Vodas
    deliverable D4.1 of work package WP4, DATASIM European project FP7-ICT (FET Open) #270833
    [PDF] [research gate]


  • Semantic-enriched data-driven theory of mobility demand and final framework for integration
    F. Giannotti, G. Andriennko, N. Andrienko, B. Furletti, J. Kertesz F. Liu, M. Nanni, L.Pappalardo, N. Pelekis, C. Renso, S. Rinzivillo
    deliverable D2.2 of work package WP2, DATASIM European project FP7-ICT (FET Open) #270833
    [PDF]

 

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