{"id":141,"date":"2020-09-19T14:09:17","date_gmt":"2020-09-19T14:09:17","guid":{"rendered":"http:\/\/scalab.dimes.unical.it\/cesario\/?page_id=141"},"modified":"2026-04-19T17:41:50","modified_gmt":"2026-04-19T17:41:50","slug":"publications","status":"publish","type":"page","link":"https:\/\/scalab.dimes.unical.it\/cesario\/publications\/","title":{"rendered":"Publications"},"content":{"rendered":"

Eugenio Cesario’s author entries on:<\/strong><\/p>\n

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Journals<\/h4>\n
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  1. V. Verrina, M. Talia, E. Cesario, S. Capalbo, D. Scordamaglia, R. Lappano, A. M. Miglietta, M. Maggiolini, S. Giordano, “Integrating Trajectory Inference and Self-Explainable Predictive Models to Explore Cell State Transitions in Breast Cancer at Single-Cell Resolution<\/a>“. Frontiers in Bioinformatics, section Single Cell Bioinformatics<\/i>, <\/i>vol. 6, pp. 1-17, Frontiers, 2026.\u00a0 \"\"<\/a> \u00a0\"\"<\/a><\/li>\n
  2. E. Cesario, P. Lindia, F. Lobello, A. Vinci, S. Capalbo, “Enhancing Energy Efficiency in Cloud Computing through Regression Models: A Data-Driven Approach with Experimental Validation<\/a>“. Future Generation Computer Systems, <\/i>vol. 177, article n. 108245, pp. 1-14, Elsevier, 2026.\u00a0 \"\"<\/a> \u00a0\"\"<\/a><\/li>\n
  3. E. Cesario, C. Comito, “Unveiling Epidemic Dynamics: Harnessing the Synergy of Social Media Data and Mobility Patterns during COVID-19<\/a>“. Neural Computing and Applications<\/i>, <\/i>vol. 37, pp. 25555-25578, Springer, 2025. \"\"<\/a> \u00a0\"\"<\/a><\/li>\n
  4. M. Talia, D. Scordamaglia, F. Cirillo, A. Zicarelli, M. De Francesco, R. Malaguarnera, E. Cesario, A. M. Miglietta, M. Maggiolini, R. Lappano, “A novel six-biomarker panel identified from male breast cancer-associated fibroblasts demonstrates prognostic power for prostate tumors<\/a>“. Journal of Translational Medicine<\/i>, <\/i>vol. 23, n. 1090, pp. 1-17, Springer Nature, 2025.\u00a0\"\"<\/a> \u00a0\"\"<\/a><\/li>\n
  5. E. Cesario, P. Lindia, A. Vinci, “Comparing machine learning-based crime hotspots vs police districts: what\u2019s the best approach for crime forecasting ?<\/a>“. IEEE Access<\/i>, <\/i>vol. 13, pp. 133053-133077, IEEE, 2025. \"\"<\/a> \u00a0\"\"<\/a><\/li>\n
  6. E. Cesario, S. Giamp\u00e0, E. Baglione, L. Cordrie, J. Selva, D. Talia, “A Parallel Machine Learning-based Approach for Tsunami Waves Forecasting using Regression Trees<\/a>“. Computer Communications<\/i>, <\/i>vol. 225, pp. 217-228, Elsevier, 2024. \"\"<\/a> \u00a0\"\"<\/a><\/li>\n
  7. M. Talia, E. Cesario, F. Cirillo, D. Scordamaglia, M. Di Dio, A. Zicarelli, A. A. Mondino, M. A. Occhiuzzi, E. M. De Francesco, A. Belfiore, A. M. Miglietta, M. Di Dio, C. Capalbo, M. Maggiolini, R. Lappano, “Harnessing sample preparation for RNA-sequencing toward a reliable bioinformatics analysis<\/a>“. Journal of Translational Medicine<\/i>, <\/i>vol. 22, n. 846, pp. 1-2, Springer Nature, 2024. \"\"<\/a> \u00a0\"\"<\/a><\/li>\n
  8. M. Talia, E. Cesario, F. Cirillo, D. Scordamaglia, M. Di Dio, A. Zicarelli, A. A. Mondino, M. A. Occhiuzzi, E. M. De Francesco, A. Belfiore, A. M. Miglietta, M. Di Dio, C. Capalbo, M. Maggiolini, R. Lappano, “Cancer-associated fibroblasts (CAFs) gene signatures predict outcomes in breast and prostate tumor patients<\/a>“. Journal of Translational Medicine<\/i>, <\/i>vol. 22, n. 597, pp. 1-19, Springer Nature, 2024. \"\"<\/a> \u00a0\"\"<\/a><\/li>\n
  9. E. Cesario, P. Lindia, A. Vinci, “Multi-Density Crime Predictor: an approach to forecast criminal activities in multi-density crime hotspots<\/a>“. Journal of Big Data, <\/i>vol. 11, n. 75, pp. 1-39, Springer, 2024. \"\"<\/a> \u00a0\"\"<\/a><\/li>\n
  10. E. Cesario, S. Giamp\u00e0, E. Baglione, L. Cordrie, J. Selva, D. Talia, “Machine Learning for Tsunami Waves Forecasting using Regression Trees<\/a>“. Big Data Research, <\/i>vol. 36, pp. 1-14, Springer, 2024. \"\"<\/a> \u00a0\"\"<\/a><\/li>\n
  11. E. Cesario, P. Lindia, A. Vinci, “A Scalable Multi-density Clustering Approach to detect City Hotspots in a Smart City<\/a>“. Future Generation Computer Systems, <\/i>vol. 157, pp. 226-236, Elsevier, 2024.\u00a0\"\"<\/a> \u00a0\"\"<\/a><\/li>\n
  12. E. Cesario, C. Comito, E. Zumpano, “A Survey of the Recent Trends in Deep Learning for Literature Based Discovery in the Biomedical Domain<\/a>“. Neurocomputing, <\/i>vol. 568, pp. 1-23, Elsevier, 2024.\u00a0\"\" <\/a>\u00a0\"\"<\/a><\/li>\n
  13. E. Cesario, “Machine Learning for Enhancing Public Safety in Modern Cities<\/a>“. Computer, <\/i>vol. 57, pp. 104-107, IEEE, 2024.\u00a0\"\"<\/a> \u00a0\"\"<\/a><\/li>\n
  14. E. Cesario, “Big data analytics and smart cities: applications, challenges, and opportunities<\/a>“. Frontiers in Big Data – Data Mining and Management, <\/i>vol. 6, pp. 1-13, Frontiers, 2023. \"\"<\/a> \u00a0\"\"<\/a><\/li>\n
  15. E. Cesario, P. Lindia, A. Vinci, “Detecting Multi-Density Urban Hotspots in a Smart City: Approaches, Challenges and Applications<\/a>“. Big Data and Cognitive Computing<\/i>, <\/i>vol. 7, n. 1, pp. 1-18, MDPI, 2023. \"\" <\/a>\"\"<\/a><\/li>\n
  16. E. Cesario, P.I. Uchubilo, A. Vinci, X. Zhu, “Multi-density Urban Hotspots Detection in Smart Cities: A Data-driven Approach and Experiments<\/a>“. Pervasive and Mobile Computing<\/i>, <\/i>vol. 86, pp. 1-13, Elsevier, 2022. \"\" <\/a>\"\"<\/a><\/li>\n
  17. M.P. Canino, E. Cesario, A. Vinci, S. Zarin, “Epidemic forecasting based on mobility patterns: an approach and experimental evaluation on COVID\u201119 Data<\/a>“. Social Network Analysis and Mining, <\/i>vol. 12, n. 116, pp. 1-15, Springer, 2022. \"\"<\/a> \"\"<\/a><\/li>\n
  18. C. Catlett, E. Cesario, D. Talia, A. Vinci, “Spatio-temporal crime predictions in smart cities: A data-driven approach and experiments<\/a>“. Pervasive and Mobile Computing<\/i>, <\/i>vol. 53, pp. 62-74, Elsevier, 2019. \"\"<\/a> \"\"<\/a><\/li>\n
  19. A. Altomare, E. Cesario, A. Vinci, “Data analytics for energy-efficient clouds: design, implementation and evaluation<\/a>“. International Journal of Parallel, Emergent and Distributed Systems, <\/i><\/i>vol. 34, n. 6, pp. 690-705, Taylor & Francis, 2019. \"\"<\/a> \"\"<\/a><\/li>\n
  20. E. Cesario, F. Marozzo, D. Talia, P. Trunfio, “SMA4TD: A social media analysis methodology for trajectory discovery in large-scale events<\/a>“. Online Social Networks and Media<\/i>, <\/i>vol. 3-4, pp. 49-62, Elsevier, 2017. \"\"<\/a> \"\"<\/a><\/li>\n
  21. C. Mastroianni, E. Cesario, A. Giordano, “Efficient and scalable execution of smart city parallel applications<\/a>“. Concurrency and Computation: Practice and Experience<\/i>, <\/i>vol. 30, n. 20, Wiley, 2018. \"\"<\/a> \"\"<\/a><\/li>\n
  22. E. Cesario, C. Comito, D. Talia, “An Approach for the Discovery and Validation of Urban Mobility Patterns<\/a>“. Pervasive and Mobile Computing<\/i>, <\/i>vol. 42, pp. 77-92, Elsevier, 2017.\u00a0\"\"<\/a> \"\"<\/a><\/li>\n
  23. A. Altomare, E. Cesario, C. Comito, F. Marozzo, D. Talia, “Trajectory Pattern Mining for Urban Computing in the Cloud<\/a>“. IEEE Transactions on Parallel and Distributed Systems<\/i>, vol. 28, n. 2, pp. 586-599, IEEE, 2017. \"\"<\/a> \"\"<\/a><\/li>\n
  24. A. Altomare, E. Cesario, D. Talia, “Mining frequent items and itemsets from distributed data streams for emergency detection and management<\/a>“. Journal of Ambient Intelligence and Humanized Computing,<\/i> vol. 8, n. 1, pp. 47-55, Springer, 2017. \"\"<\/a> \"\"<\/a><\/li>\n
  25. E. Cesario, C. Mastroianni, D. Talia, “Distributed Volunteer Computing for Solving Ensemble Learning Problems<\/a>“. Future Generation Computer Systems<\/i>, vol. 54, pp. 68-78, Elsevier, 2016. \"\"<\/a> \"\"<\/a><\/li>\n
  26. E. Cesario, C. Mastroianni, D. Talia, “A Multi-Domain Architecture for Mining Frequent Items and Itemsets from Distributed Data Streams<\/a>“. Journal of Grid Computing<\/i>, vol. 12, n. 1, pp. 153-168, Springer, 2014. \"\"<\/a> \"\"<\/a><\/li>\n
  27. E. Cesario, M. Lackovic, D. Talia, P. Trunfio, “Programming Knowledge Discovery Workflows in Service-Oriented Distributed Systems<\/a>“. Concurrency and Computation: Practice and Experience<\/i>, vol. 25, n. 10, pp. 1482–1504, Wiley, 2013. \"\"<\/a> \"\"<\/a><\/li>\n
  28. E. Cesario, D. Talia, “Distributed Data Mining Patterns and Services: An Architecture and Experiments<\/a>“. Concurrency and Computation: Practice and Experience<\/i>, vol. 24, n. 15, pp. 1751-1774, Wiley, 2012. \"\"<\/a> \"\"<\/a><\/li>\n
  29. E. Cesario, D. Talia, “Using Grids for Exploiting the Abundance of Data in Science<\/a>“. Scalable Computing: Practice and Experience<\/i>, vol. 11, n. 3, pp. 251-262, 2010. \"\"<\/a> \"\"<\/a><\/li>\n
  30. E. Cesario, F. Folino, A. Locane, G. Manco, R. Ortale, “Boosting Text Segmentation via Progressive Classification<\/a>“. Knowledge and Information Systems<\/i>, vol. 15, n. 3, pp. 285 – 320, Springer, 2008. \"\"<\/a> \"\"<\/a><\/li>\n
  31. F. Hupfeld, T. Cortes, B. Kolbeck, E. Focht, M. Hess, J. Malo, J. Marti, J. Stender, E. Cesario, “The XtreemFS architecture – a case object-based file systems in Grids<\/a>“. Concurrency and Computation: Practice and Experience<\/i>, vol. 20, n. 8, pp. 2049-2060, Wiley, 2008. \"\"<\/a> \"\"<\/a><\/li>\n
  32. F. Angiulli, E. Cesario, C. Pizzuti, “Random Walk Biclustering for Microarray Data<\/a>“. Information Sciences<\/i>, vol. 178, n. 6, pp. 1479-1497, Elsevier, 2008. \"\"<\/a> \"\"<\/a><\/li>\n
  33. E. Cesario, G. Manco, R. Ortale, “Top-Down Parameter-Free Clustering of High-Dimensional Categorical Data<\/a>“. IEEE Transactions on Knowledge and Data Engineering<\/i>, vol. 19, n. 12, pp. 1607-1624, IEEE, 2007. \"\"<\/a> \"\"<\/a><\/li>\n<\/ol>\n
    \n

    Conferences and Workshops<\/h4>\n
      \n
    1. P. Lindia, E. Cesario, E. De Francesco, A. Aloia, D. Sacc\u00e0, “LSTM and ARIMA-based modeling of Cereal Crop Dynamics for Precision Agriculture”. Proc. of the <\/em>12th EAI International Conference on Smart Objects and Technologies for Social Good (GOODTECHS 2026<\/strong>)<\/i><\/em>, Dubrovnick, Croatia, pp. —, EAI, 2026. To appear.<\/em><\/li>\n
    2. S. Capalbo, E. Cesario, P. Lindia, F. Lobello, A. Vinci, “Performance analysis of a parallel implementation of the city hostpot detector algorithm”. Proc. of the <\/em>34th Euromicro International Conference on Parallel, Distributed and Network-Based Computing (PDP 2026<\/strong>)<\/i><\/em>, Cluj-Napoca, Croatia, pp. —, IEEE, 2026. To appear.<\/em><\/li>\n
    3. E. Cesario, P. Lindia, A. Vinci, “Evaluating Urban Partitioning Approaches to Improve Crime Forecasting Accuracy in Cities”. Proc. of the <\/em>23rd IEEE International Conference on Pervasive Intelligence and Computing (PICom 2025<\/strong>)<\/i><\/em>, Hakodate City, Hokkaido, Japan, pp. —, IEEE, 2025. To appear.<\/em><\/li>\n
    4. E. Cesario, P. Lindia, F. Lobello, A. Vinci, S. Capalbo, “Enhancing Cloud Energy Efficiency through Predictive Machine Learning for Inter- and Intra-Data Center VM Consolidation”. Proc. of the <\/em>28th European Conference on Artificial Intelligence (ECAI 2025<\/strong>)<\/i><\/em>, Bologna, Italy, pp. —, —, 2025. To appear.<\/em><\/li>\n
    5. E. Cesario, S. Giamp\u00e0, D. Talia, “Building Parallel Machine Learning Workflows in PyCOMPSs: The Case Study of Tsunami Forecasting”.\u00a0Proc. of 2nd Workshop on High-Performance eScience (HiPES 2025<\/strong>), in conjunction with EuroPar’25<\/i>, Dresden, Germany, pp. —, Springer, 2025. To appear.<\/em><\/li>\n
    6. E. Cesario, P. Lindia, F. Lobello, A. Vinci, S. Zarin, S. Capalbo, “Improving Cloud Energy Efficiency through Machine Learning Models”. Proc. of the <\/em>33rd Euromicro International Conference on Parallel, Distributed and Network-Based Computing (PDP 2025<\/strong>)<\/i><\/em>, Turin, Italy, pp. 247-251, IEEE, 2025.\u00a0<\/em><\/li>\n
    7. A. Zicarelli, M. Talia, E. Cesario, F. Cirillo, D. Scordamaglia, A. A. Mondino, M. Di Dio, S. De Rosis, M. Di Dio, A. M. Miglietta, M. Maggiolini, R. Lappano, “Assessment of gene signature deriving from prostate cancer-associated fibroblasts (CAFs)<\/a>” (Poster). Proc. of\u00a0 the <\/em>3rd International Online Conference on Cells (CELLS 2025<\/strong>)<\/i><\/em>, MDPI, 2025.
      \n<\/em><\/li>\n
    8. E. Cesario, P. Lindia, “Towards a Hierarchical Exascale Framework for Iterative Parallel Data Analysis Algorithms<\/a>“. Proc. of the <\/em>32nd Euromicro International Conference on Parallel, Distributed and Network-Based Computing (PDP 2024<\/strong>)<\/i><\/em>, Dublin, Ireland, pp. 293-296, IEEE, 2024.
      \n<\/em><\/li>\n
    9. E. Cesario, P. Lindia, A. Vinci, “How to deal with different densities of urban spatial data? A comparison of clustering approaches to detect city hotspots”. Proc. of the 4th International Conference and Summer School on Numerical Computations: Theory and Algorithms (NUMTA 2023<\/strong>)<\/em>, Pizzo Calabro (VV), Italy, pp. —, Springer, 2023. To be published<\/em><\/li>\n
    10. E. Cesario, S. Giamp\u00e0, E. Baglione, L. Cordrie, J. Selva, D. Talia, “Forecasting Tsunami Waves using Regression Trees<\/a>“. Proc. of the 8th International Conference on Information and Communication Technologies for Disaster Management<\/em> (ICT-DM 2023<\/strong>)<\/i><\/em>, Italy, pp. 1-7, IEEE, 2023.
      \n<\/em><\/li>\n
    11. M.P. Canino, E. Cesario, A. Vinci, S. Zarin, “Exploiting mobility data to forecast Covid-19 spread<\/a>“. Proc. of the 20th IEEE International Conference on Pervasive Intelligence and Computing<\/em> (PICom 2022<\/strong>)<\/i><\/em>, Italy, pp. 1-4, IEEE, 2022.<\/em><\/li>\n
    12. A. Rovella, A. Murzaku, E. Cesario, M. Critelli, M. Bartucci, F.M.C. Messiniti, “Analysis, evaluation and comparison of knowledge extraction tools in the Environmental and Health domain. A holistic approach<\/a>“. Proc. of the 2021 International KOMEEO Conference on Knowledge Organization and Management in the Domain of Environment and Earth Observation (KOMEEO 2022<\/strong>)<\/em>, Italy, pp. 121-146, Nomos Verlagsgesellschaft mbH und Co. KG, 2022.<\/em><\/li>\n
    13. E. Cesario, A. Vinci, S. Zarin, “Towards Parallel Multi-density Clustering for Urban Hotspots Detection<\/a>“. Proc. of the <\/em>29th Euromicro International Conference on Parallel, Distributed and Network-Based Computing (PDP 2021<\/strong>)<\/i><\/em>, Villadolid, Spain, pp. 245-248, IEEE, 2021.<\/em><\/li>\n
    14. E. Cesario, P.I. Uchubilo, A. Vinci, X. Zhu, “Discovering Multi-density Urban Hotspots in a Smart City<\/a>“. Proc. of the 6th IEEE International Conference on Smart Computing (SMARTCOMP 2020<\/strong>)<\/em>, Bologna, Italy, pp. 332-337, IEEE, 2020. <\/em><\/li>\n
    15. E. Cesario, A. Vinci, X. Zhu, “Hierarchical Clustering of Spatial Urban Data<\/a>“. Proc. of the 3rd International Conference and Summer School on Numerical Computations: Theory and Algorithms (NUMTA 2019<\/strong>)<\/em>, Le Castella (KR), Italy, pp. 223-231, Springer, 2019.<\/li>\n
    16. E. Cesario, A. Vinci, “A Comparative Analysis of Classification and Regression Models for Energy-Efficient Clouds<\/a>“. Proc. of the 16th IEEE International Conference on Networking, Sensing and Control <\/em>(ICNSC 2019<\/strong>), Calgary, Canada, pp. 385-390, IEEE, 2019.<\/li>\n
    17. C. Catlett, E. Cesario, D. Talia, A. Vinci, “A Data-driven Approach for Spatio-Temporal Crime Predictions in Smart Cities<\/a>“. Proc. of the 4th IEEE International Conference on Smart Computing (SMARTCOMP 2018<\/strong>)<\/em>, Taormina (ME), Italy, pp. 17-24, IEEE, 2018 (Best Paper Award<\/span><\/span><\/strong><\/a>).
      \n<\/span><\/span><\/em><\/li>\n
    18. E. Cesario, F. Cicirelli, C. Mastroianni, “Distributed computation of mobility patterns in a smart city environment<\/a>“. Proc. of the 6th Workshop on Large Scale Distributed Virtual Environments on Clouds and P2P held in conjunction with Euro-Par 2018 (LSDVE 2018<\/strong>)<\/em>, Turin, Italy, pp. 559-572, Springer, 2018.<\/em><\/li>\n
    19. A. Altomare, E. Cesario “A Data-driven Approach based on Auto-Regressive Models for Energy-Efficient Clouds<\/a>“. Proc. of the17th IEEE\/ACM International Symposium on Cluster, Cloud and Grid Computing (CCGrid 2017<\/strong>)<\/i><\/em>, Madrid, Spain, pp. 1062-1069, IEEE, 2017.<\/li>\n
    20. A. Altomare, E. Cesario “A Comparative Analysis of Data-Driven Consolidation Policies for Energy-Efficient Clouds<\/a>“. Proc. of the 25th Euromicro International Conference on Parallel, Distributed and Network-Based Computing (PDP 2017<\/strong>)<\/i><\/em>, St. Petersburg, Russia, pp. 535-538, IEEE, 2017.<\/li>\n
    21. E. Cesario, A. Giordano, C. Mastroianni, “Balancing Speedup and Accuracy in Smart City Parallel Applications<\/a>“. Proc. of the 4th Workshop on Large Scale Distributed Virtual Environments on Clouds and P2P held in conjunction with Euro-Par 2016 (LSDVE 2016<\/strong>)<\/em>, Grenoble, France, pp. –, Springer, 2016 (Best Paper Award<\/span><\/span><\/strong><\/a>).<\/span><\/span><\/em><\/li>\n
    22. E. Cesario, F. Folino, M. Guarascio, L. Pontieri, “A Cloud-based Prediction Framework for Analyzing Business Process Performances<\/a>“. Proc. of the 11th International Conference on Availability, Reliability and Security (ARES 2016<\/strong>)<\/em>, Salzburg, Austria, pp. 63-80, CPS, 2016.<\/li>\n
    23. E. Cesario, C. Catlett, D. Talia, “Forecasting Crimes using Autoregressive Models<\/a>“. Proc. of the<\/i> 2nd International Conference on Big Data Intelligence and Computing (DataCom 2016<\/strong>)<\/i>, Auckland, New Zealand, pp. –, IEEE, 2016.<\/li>\n
    24. E. Cesario, C. Comito, D. Talia, “A Comprehensive Validation Methodology for Trajectory Pattern Mining of GPS Data<\/a>“. Proc. of the<\/i> 2nd International Conference on Big Data Intelligence and Computing (DataCom 2016<\/strong>)<\/i>, Auckland, New Zealand, pp. –, IEEE, 2016.<\/li>\n
    25. E. Cesario, A. Iannazzo, F. Marozzo, F. Morello, D. Talia, P. Trunfio, “Nubytics: Scalable Cloud Services for Data Analysis and Prediction<\/a>“. Proc. of the<\/i> 2nd International Forum on Research and Technologies for Society and Industry (RTSI 2016<\/strong>)<\/i>, Salerno, Italy, pp. –, 2016. <\/li>\n
    26. E. Cesario, A. Iannazzo, F. Marozzo, F. Morello, G. Riotta, A. Spada, D. Talia, P. Trunfio, “Analyzing Social Media Data to Discover Mobility Patterns at EXPO 2015: Methodology and Results<\/a>“. Proc. of the<\/i> 2016 International Conference on High Performance Computing & Simulation (HPCS 2016<\/strong>)<\/i>, Innsbruck, Austria, pp. –, IEEE, 2016.<\/li>\n
    27. A. Altomare, E. Cesario, C. Mastroianni, “Efficient workload management in geographically distributed data centers leveraging autoregressive models<\/a>“. Proc. of the 2nd International Conference and Summer School on Numerical Computations: Theory and Algorithms (NUMTA 2016<\/strong>)<\/i>, Pizzo, Italy, SIAM, pp. –, 2016.<\/li>\n
    28. A. Altomare, E. Cesario, “Predictive Models for Energy-Efficient Clouds: an Analysis on Real-Life and Synthetic Data<\/a>“. Proc. of the 14th IEEE International Conference on Ubiquitous Computing and Communications (IUCC 2015<\/strong>)<\/i>, Liverpool, UK, pp. 1538-1543, IEEE, 2015.<\/li>\n
    29. E. Cesario, C. Congedo, F. Marozzo, G. Riotta, A. Spada, D. Talia, P. Trunfio, C. Turri, “Following Soccer Fans from Geotagged Tweets at FIFA World Cup 2014<\/a>“. Proc. of the 2nd IEEE Conference on Spatial Data Mining and Geographical Knowledge Services (ICSDM 2015<\/strong>)<\/i>, Fuzhou, China, pp. 33-38, IEEE, 2015.<\/li>\n
    30. A. Altomare, E. Cesario, D. Talia, “Energy-Aware Migration of Virtual Machines Driven by Predictive Data Mining Models<\/a>“. Proc. of the 23rd Euromicro International Conference on Parallel, Distributed and Network-Based Computing (PDP 2015<\/strong>)<\/i>, Turku, Finland, pp. 549-553, IEEE, 2015.<\/li>\n
    31. A. Altomare, E. Cesario, C. Comito, F. Marozzo, D. Talia, “Trajectory Pattern Mining over a Cloud-based Framework for Urban Computing<\/a>“. Proc. of the 16th International Conference on High Performance Computing and Communications (HPCC 2014<\/strong>)<\/i>, Paris, France, pp. 367-374, IEEE, 2014.<\/li>\n
    32. E. Cesario, C. Comito, D. Talia, “Towards a Cloud-based framework for Urban Computing. The Trajectory Analysis Case<\/a>“. Proc. of the 3rd IEEE International Conference on Cloud and Green Computing (CGC 2013<\/strong>)<\/i>, pp. 16-23, IEEE, 2013 (Best Paper Candidate<\/span><\/span><\/strong>).<\/span><\/span><\/em><\/li>\n
    33. A. Altomare, E. Cesario, C. Comito, F. Marozzo, D. Talia, “Using Clouds for Smart City Applications<\/a>“. Proc. of the 5th IEEE International Conference on Cloud Computing Technology and Science (CloudCom 2013<\/strong>)<\/i>, Bristol, UK, pp. 234-237, IEEE, 2013.<\/li>\n
    34. E. Cesario, C. Mastroianni, D. Talia, “Using Mining@home for Distributed Ensemble Learning<\/a>“. Proc. of the 5th International Conference on Data Management in Cloud, Grid and P2P Systems (Globe 2012<\/strong>)<\/i>, Wien, Austria , September 2012.<\/li>\n
    35. E. Cesario, D. Talia, “Fault-Tolerant Distributed Knowledge Discovery Services for Grids<\/a>“. Proc. of the Sixth International Conference on Complex, Intelligent, and Software Intensive Systems (CISIS 2012<\/strong>)<\/i>, Palermo, Italy, pp. 1036-1041, IEEE, 2012.<\/li>\n
    36. E. Cesario, M. Esposito, G. De Pietro, D. Talia, “A Consistency Checker for Verifying the Knowledge Encoded into Clinical DSSs<\/a>“. In Proc. of the 25th IEEE International Symposium on Computer-Based Medical Systems (CBMS 2012<\/strong>)<\/i>, Rome, Italy, pp. 1-6, IEEE, 2012.<\/li>\n
    37. E. Cesario, M. Esposito, “A Knowledge-based Method for Verifying the Reliability of Clinical DSSs<\/a>“. In Proc. of the 8th International Conference on Signal Image Technology and Internet Based Systems (SITIS 2012<\/strong>)<\/i>, Sorrento (NA), Italy, pp. 489-495, IEEE, 2012.<\/li>\n
    38. E. Cesario, M. Esposito, G. De Pietro, D. Talia, “Verification of clinical guidelines encoded into knowledge-based DSSs<\/a>“. In Proc. of the 6th IEEE International Conference on Intelligent Systems (IS 2012<\/strong>)<\/i>, Sofia, Bulgaria, pp. 264-269, IEEE, 2012.<\/li>\n
    39. E. Cesario, A. Grillo, C. Mastroianni, D. Talia, “A Sketch-based Architecture for Mining Frequent Items and Itemsets from Distributed Data Streams<\/a>“. Proc. of the 11th IEEE\/ACM International Symposium on Cluster, Cloud and Grid Computing (CCGrid 2011<\/strong>)<\/i>, Newport Beach, CA, USA, pp. 245-253, May 2011.<\/li>\n
    40. E. Cesario, D. Talia, “A Failure Handling Framework for Distributed Data Mining Services on the Grid<\/a>“. Proceedings of the 19th Euromicro International Conference on Parallel, Distributed and Network-Based Computing (PDP 2011<\/strong>)<\/i>, Ayia Napa, Cyprus, pp. 70-79, IEEE Computer Society Press, February 2011.<\/li>\n
    41. E. Cesario, D. Talia, “Distributed Data Mining Models as Services on the Grid<\/a>“. Proc. of 10th International Workshop on High Performance Data Mining (HPDM 2008<\/strong>), in conjunction with ICDM’08<\/i>, Pisa, Italy, IEEE Computer Society Press, December 2008.<\/li>\n
    42. J. Stender, B. Kolbeck, F. Hupfeld, E. Cesario, E. Focht, M. Hess, J. Malo, J. Marti, “Striping without Sacrifices: Maintaining POSIX Semantics in a Parallel File System<\/a>“. Proc. of the 1st USENIX Workshop on Large-Scale Computing (LASCO 2008<\/strong>)<\/i>, Boston, June 2008.<\/li>\n
    43. F. Hupfeld, T. Cortes, B. Kolbeck, E. Focht, M. Hess, J. Malo, J. Marti, J. Stender, E. Cesario, “XtreemFS: a case for object-based storage in Grid data management”. Proc. of the 3rd VLDB Workshop on Data Management in Grids – co-located with the 33th International Conference on Very Large Data Bases (VLDB Workshop 2007<\/strong>)<\/i>, September 2007.<\/li>\n
    44. E. Cesario, T. Cortes, E. Focht, M. Hess, F. Hupfeld, B. Kolbeck, J. Malo, J. Marti, J. Stender, “XtreemFS – an object-based file system for large scale federated IT infrastructures”. Proc. of the Linux Tag 2007 (Linux Tag 2007<\/strong>) <\/i>, May 2007.<\/li>\n
    45. E. Cesario, D. Talia, “From Parallel Data Mining to Grid enabled Distributed Knowledge Discovery<\/a>“. Proc. of the 18th International Conference on Rough Sets, Fuzzy Sets, Data Mining and Granular Computing (RSFDGrC 2007<\/strong>)<\/i>, Toronto, Canada, LNAI, vol. 4482, pp. 25–36, Springer, May 2007.<\/li>\n
    46. F. Angiulli, E. Cesario, C. Pizzuti, “A Greedy Search Approach to Co-Clustering Sparse Binary Matrices<\/a>“. Proc. of the 18th IEEE International Conference on Tools with Artificial Intelligence (ICTAI 2006<\/strong>)<\/i>, Washington D.C., U.S.A., November 2006.<\/li>\n
    47. E. Cesario, G. Manco, R. Ortale, “Top-Down Parameter-Free Clustering of High-Dimensional Categorical Data”. Proc. of the 14th Italian Symposium on Advanced Database Systems (SEBD 2006<\/strong>)<\/i>, Portonovo (Ancona), Italy, June 2006. <\/i><\/li>\n
    48. E. Cesario, F. Folino, G. Manco, L. Pontieri, “An Incremental Clustering Scheme for Duplicate Detection in Large Databases<\/a>“. Proc. of 9th International Database Engineering and Application Symposium (IDEAS 2005<\/strong>)<\/i>, Montreal. Canada, pp. 89–95, IEEE Computer Society, July 2005.<\/li>\n
    49. E. Cesario, F. Folino, A. Locane, G. Manco, R. Ortale, “RecBoost: A Supervised Approach to Automatic Text Segmentation”. Proc. of 13th Italian Symposium on Advanced Database Systems (SEBD 2005<\/strong>)<\/i>, Bressanone (Bolzano), Italy, June 2005.<\/li>\n
    50. E. Cesario, F. Folino, R. Ortale, “Putting Enhanced Hypermedia Personalization into Practice via Web Mining<\/a>“. Proc. of 15th International Conference on Database and Expert Systems Applications (DEXA 2004<\/strong>)<\/i>, Zaragoza, Spain, LNCS, vol. 3180, pp. 947–956, Springer-Verlag, August 2004.<\/li>\n
    51. E. Cesario, F. Folino, G. Manco, D. Sacc\u00e0, R. Ortale, A. Tagarelli, “An Adaptative System for on-line Bank Services based on Web Mining”. Proc. of the Italian Conference AICA 2003 (AICA 2003<\/strong>)<\/i>,<\/i> Trento, Italy, September 2003.<\/li>\n<\/ol>\n
      \n

      Book Chapters<\/h4>\n
        \n
      1. R.M. Badia, C. Bhihe, E. Cesario, L. Cordrie, J. Ejarque, S. J. Gibbons, J. Mac\u00edas, M. Monterrubio, M. Pienkowska, C. S\u00e1nchez-Linares, J. Selva, D. Talia, J. de la Puente,\u00a0“Urgent computing for natural hazards: eFlows4HPC solution”. In: Urgent Computing across the Device-Edge-Cloud Continuum: Concepts, Applications, and Future Directions<\/i>, D. Balouek, M. Parashar (Editors), Springer, pp. –, 2026.<\/li>\n
      2. E. Cesario, “Big Data Analysis for Smart City Applications<\/a>“. In: Encyclopedia of Big Data Technologies<\/i>, S. Sakr, A. Y. Zomaya (Editors), Springer, pp. –, 2019.<\/li>\n
      3. E. Cesario, C. Mastroianni, D. Talia, “Mining Distributed Data Streams on Content Delivery Networks<\/a>“. In: Advanced Content Delivery, Streaming, and Cloud Services<\/i>, M. Pathan, K. Sitaraman, D. Robinson (Editors), John Wiley & Sons, pp. 273–287, 2014.<\/li>\n
      4. E. Cesario, C. Comito, D. Talia, “Trajectory Data Analysis Over a Cloud-Based Framework for Smart City Analytics<\/a>“. In: Internet of Things Based on Smart Objects, Technology, Middleware and Applications<\/i>, G. Fortino, P. Trunfio (Editors), Springer, pp. 143–162, 2014.<\/li>\n
      5. E. Cesario, “Data Access<\/a>“. In: Encyclopedia of Systems Biology<\/i>, W. Dubitzky, O. Wolkenhauer, H. Yokota, K. Cho (Editors), Springer, 2013.<\/li>\n
      6. E. Cesario, M. Lackovic, D. Talia, P. Trunfio, “A Visual Environment for Designing and Running Data Mining Workflows in the Knowledge Grid<\/a>“. In: Data Mining: Foundations and Intelligent Paradigms<\/i>, D. Holmes, L. Jain (Editors), Springer, Intelligent Systems Reference Library, vol. 24, pp. 57–75, 2012.<\/li>\n
      7. E. Cesario, M. Lackovic, D. Talia, P. Trunfio, “Service-Oriented Data Analysis in Distributed Computing Systems<\/a>“. In: High Performance Computing: From Grids and Clouds to Exascale<\/i>, I. Foster, W. Gentzsch, L. Grandinetti, G. Joubert (Editors), IOS Press, Amsterdam, The Netherlands, Advances in Parallel Computing, vol. 20, pp. 225–245, 2011.<\/li>\n
      8. E. Cesario, N. De Caria, C. Mastroianni, D. Talia, “Distributed Data Mining Using a Public Resource Computing Framework<\/a>“. In: Grids, P2P and Service computing<\/i>, F. Desprez, V. Getov, T. Priol, R. Yahyapour (Editors), Springer, 2010.<\/li>\n
      9. E. Cesario, A. Congiusta, D. Talia, P. Trunfio, “Data Analysis Services in the Knowledge Grid<\/a>“. In: Data Mining Techniques in Grid Computing Environments<\/i>, W. Dubitzky (Editor), Wiley-Blackwell, pp. 17–36, 2008.
        \n<\/i><\/li>\n<\/ol>\n","protected":false},"excerpt":{"rendered":"

        Eugenio Cesario’s author entries on: \u00a0 \u00a0 \u00a0 \u00a0 \u00a0\u00a0 \u00a0 Journals V. Verrina, M. Talia, E. Cesario, S. Capalbo, D. Scordamaglia, R. Lappano, A. M. Miglietta, M. Maggiolini, S. Giordano, “Integrating Trajectory Inference and Self-Explainable Predictive Models to Explore Cell State Transitions in Breast Cancer at Single-Cell Resolution“. Frontiers in Bioinformatics, section Single Cell […]<\/p>\n","protected":false},"author":8,"featured_media":0,"parent":0,"menu_order":0,"comment_status":"closed","ping_status":"closed","template":"","meta":[],"aioseo_notices":[],"_links":{"self":[{"href":"https:\/\/scalab.dimes.unical.it\/cesario\/wp-json\/wp\/v2\/pages\/141"}],"collection":[{"href":"https:\/\/scalab.dimes.unical.it\/cesario\/wp-json\/wp\/v2\/pages"}],"about":[{"href":"https:\/\/scalab.dimes.unical.it\/cesario\/wp-json\/wp\/v2\/types\/page"}],"author":[{"embeddable":true,"href":"https:\/\/scalab.dimes.unical.it\/cesario\/wp-json\/wp\/v2\/users\/8"}],"replies":[{"embeddable":true,"href":"https:\/\/scalab.dimes.unical.it\/cesario\/wp-json\/wp\/v2\/comments?post=141"}],"version-history":[{"count":150,"href":"https:\/\/scalab.dimes.unical.it\/cesario\/wp-json\/wp\/v2\/pages\/141\/revisions"}],"predecessor-version":[{"id":473,"href":"https:\/\/scalab.dimes.unical.it\/cesario\/wp-json\/wp\/v2\/pages\/141\/revisions\/473"}],"wp:attachment":[{"href":"https:\/\/scalab.dimes.unical.it\/cesario\/wp-json\/wp\/v2\/media?parent=141"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}