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Eugenio Cesario
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2020 – today
- 2024
- [j26]Eugenio Cesario
, Salvatore Giampà, Enrico Baglione, Louise Cordrie, Jacopo Selva
Machine Learning for Tsunami Waves Forecasting Using Regression Trees. Big Data Res. 36: 100452 (2024) - [j25]Eugenio Cesario
A parallel machine learning-based approach for tsunami waves forecasting using regression trees. Comput. Commun. 225: 217-228 (2024) - [j24]Eugenio Cesario
Machine Learning for Enhancing Public Safety in Modern Cities. Computer 57(4): 104-107 (2024) - [j23]Eugenio Cesario
Big data analytics and smart cities: applications, challenges, and opportunities. Frontiers Big Data 6 (2024) - [j22]Eugenio Cesario
A scalable multi-density clustering approach to detect city hotspots in a smart city. Future Gener. Comput. Syst. 157: 226-236 (2024) - [j21]Eugenio Cesario
A survey of the recent trends in deep learning for literature based discovery in the biomedical domain. Neurocomputing 568: 127079 (2024) - [j20]Eugenio Cesario, Paolo Lindia, Andrea Vinci:
Multi-density crime predictor: an approach to forecast criminal activities in multi-density crime hotspots. J. Big Data 11(1): 75 (2024) - [c40]Eugenio Cesario, Paolo Lindia:
Towards a Hierarchical Exascale Framework for Iterative Parallel Data Analysis Algorithms. PDP 2024: 293-296 - 2023
- [j19]Eugenio Cesario
Detecting Multi-Density Urban Hotspots in a Smart City: Approaches, Challenges and Applications. Big Data Cogn. Comput. 7(1): 29 (2023) - [c39]Eugenio Cesario
Forecasting Tsunami Waves Using Regression Trees. ICT-DM 2023: 1-7 - 2022
- [j18]Eugenio Cesario
Multi-density urban hotspots detection in smart cities: A data-driven approach and experiments. Pervasive Mob. Comput. 86: 101687 (2022) - [j17]Maria Pia Canino, Eugenio Cesario
Epidemic forecasting based on mobility patterns: an approach and experimental evaluation on COVID-19 Data. Soc. Netw. Anal. Min. 12(1): 116 (2022) - [c38]Maria Pia Canino, Eugenio Cesario
Exploiting mobility data to forecast Covid-19 spread. DASC/PiCom/CBDCom/CyberSciTech 2022: 1-4 - 2021
- [c37]Eugenio Cesario
Towards Parallel Multi-density Clustering for Urban Hotspots Detection. PDP 2021: 245-248 - 2020
- [c36]Eugenio Cesario
Discovering Multi-density Urban Hotspots in a Smart City. SMARTCOMP 2020: 332-337
2010 – 2019
- 2019
- [j16]Albino Altomare, Eugenio Cesario
Data analytics for energy-efficient clouds: design, implementation and evaluation. Int. J. Parallel Emergent Distributed Syst. 34(6): 690-705 (2019) - [j15]Charlie Catlett
Spatio-temporal crime predictions in smart cities: A data-driven approach and experiments. Pervasive Mob. Comput. 53: 62-74 (2019) - [c35]Eugenio Cesario
A Comparative Analysis of Classification and Regression Models for Energy-Efficient Clouds. ICNSC 2019: 385-390 - [c34]Eugenio Cesario
Hierarchical Clustering of Spatial Urban Data. NUMTA(1) 2019: 223-231 - [r1]Eugenio Cesario:
Big Data Analysis for Smart City Applications. Encyclopedia of Big Data Technologies 2019 - 2018
- [j14]Carlo Mastroianni
Efficient and scalable execution of smart city parallel applications. Concurr. Comput. Pract. Exp. 30(20) (2018) - [c33]Eugenio Cesario
Distributed Computation of Mobility Patterns in a Smart City Environment. Euro-Par Workshops 2018: 559-572 - [c32]Charlie Catlett, Eugenio Cesario
A Data-Driven Approach for Spatio-Temporal Crime Predictions in Smart Cities. SMARTCOMP 2018: 17-24 - 2017
- [j13]Albino Altomare, Eugenio Cesario
Mining frequent items and itemsets from distributed data streams for emergency detection and management. J. Ambient Intell. Humaniz. Comput. 8(1): 47-55 (2017) - [j12]Eugenio Cesario
SMA4TD: A social media analysis methodology for trajectory discovery in large-scale events. Online Soc. Networks Media 3-4: 49-62 (2017) - [j11]Eugenio Cesario
An approach for the discovery and validation of urban mobility patterns. Pervasive Mob. Comput. 42: 77-92 (2017) - [j10]Albino Altomare, Eugenio Cesario
Trajectory Pattern Mining for Urban Computing in the Cloud. IEEE Trans. Parallel Distributed Syst. 28(2): 586-599 (2017) - [c31]Albino Altomare, Eugenio Cesario
A Data-driven Approach based on Auto-Regressive Models for Energy-Efficient Clouds. CCGrid 2017: 1062-1069 - [c30]Albino Altomare, Eugenio Cesario
A Comparative Analysis of Data-Driven Consolidation Policies for Energy-Efficient Clouds. PDP 2017: 535-538 - 2016
- [j9]Eugenio Cesario
Distributed volunteer computing for solving ensemble learning problems. Future Gener. Comput. Syst. 54: 68-78 (2016) - [c29]Eugenio Cesario
A Cloud-Based Prediction Framework for Analyzing Business Process Performances. CD-ARES 2016: 63-80 - [c28]Eugenio Cesario
Forecasting Crimes Using Autoregressive Models. DASC/PiCom/DataCom/CyberSciTech 2016: 795-802 - [c27]Eugenio Cesario
A Comprehensive Validation Methodology for Trajectory Pattern Mining of GPS Data. DASC/PiCom/DataCom/CyberSciTech 2016: 819-826 - [c26]Carlo Mastroianni, Eugenio Cesario
Balancing Speedup and Accuracy in Smart City Parallel Applications. Euro-Par Workshops 2016: 224-235 - [c25]Eugenio Cesario
Analyzing social media data to discover mobility patterns at EXPO 2015: Methodology and results. HPCS 2016: 230-237 - [c24]Eugenio Cesario
Nubytics: Scalable cloud services for data analysis and prediction. RTSI 2016: 1-6 - 2015
- [c23]Albino Altomare, Eugenio Cesario
Predictive Models for Energy-Efficient Clouds: An Analysis on Real-Life and Synthetic Data. CIT/IUCC/DASC/PICom 2015: 1538-1543 - [c22]Eugenio Cesario
Following soccer fans from geotagged tweets at FIFA World Cup 2014. ICSDM 2015: 33-38 - [c21]Albino Altomare, Eugenio Cesario
Energy-Aware Migration of Virtual Machines Driven by Predictive Data Mining Models. PDP 2015: 549-553 - 2014
- [j8]Eugenio Cesario
A Multi-Domain Architecture for Mining Frequent Items and Itemsets from Distributed Data Streams. J. Grid Comput. 12(1): 153-168 (2014) - [c20]Albino Altomare, Eugenio Cesario
Trajectory Pattern Mining over a Cloud-Based Framework for Urban Computing. HPCC/CSS/ICESS 2014: 367-374 - [p1]Eugenio Cesario
Trajectory Data Analysis Over a Cloud-Based Framework for Smart City Analytics. Internet of Things Based on Smart Objects, Technology, Middleware and Applications 2014: 143-162 - 2013
- [j7]Eugenio Cesario
Programming knowledge discovery workflows in service-oriented distributed systems. Concurr. Comput. Pract. Exp. 25(10): 1482-1504 (2013) - [c19]Eugenio Cesario
Towards a Cloud-Based Framework for Urban Computing, The Trajectory Analysis Case. CGC 2013: 16-23 - [c18]Albino Altomare, Eugenio Cesario
Using Clouds for Smart City Applications. CloudCom (2) 2013: 234-237 - 2012
- [j6]Eugenio Cesario
Distributed data mining patterns and services: an architecture and experiments. Concurr. Comput. Pract. Exp. 24(15): 1751-1774 (2012) - [c17]Eugenio Cesario
A Consistency Checker for verifying the knowledge encoded into clinical DSSs. CBMS 2012: 1-6 - [c16]Eugenio Cesario
Fault-Tolerant Distributed Knowledge Discovery Services for Grids. CISIS 2012: 1036-1041 - [c15]Eugenio Cesario
Using Mining@Home for Distributed Ensemble Learning. Globe 2012: 100-111 - [c14]Eugenio Cesario
Verification of clinical guidelines encoded into knowledge-based DSSs. IEEE Conf. of Intelligent Systems 2012: 264-269 - [c13]Eugenio Cesario
A Knowledge-based Method for Verifying the Reliability of Clinical DSSs. SITIS 2012: 489-495 - 2011
- [c12]Eugenio Cesario
A Sketch-Based Architecture for Mining Frequent Items and Itemsets from Distributed Data Streams. CCGRID 2011: 245-253 - [c11]Eugenio Cesario
A Failure Handling Framework for Distributed Data Mining Services on the Grid. PDP 2011: 70-79 - 2010
- [j5]Eugenio Cesario, Domenico Talia:
Using Grids for Exploiting the Abundance of Data in Science. Scalable Comput. Pract. Exp. 11(3) (2010) - [c10]Eugenio Cesario
Service-Oriented Data Analysis in Distributed Computing Systems. High Performance Computing Workshop 2010: 225-245
2000 – 2009
- 2009
- [c9]Eugenio Cesario
Distributed Data Mining using a Public Resource Computing Framework. CoreGRID@Euro-Par 2009: 33-44 - 2008
- [j4]Felix Hupfeld, Toni Cortes
The XtreemFS architecture - a case for object-based file systems in Grids. Concurr. Comput. Pract. Exp. 20(17): 2049-2060 (2008) - [j3]Fabrizio Angiulli
Random walk biclustering for microarray data. Inf. Sci. 178(6): 1479-1497 (2008) - [j2]Eugenio Cesario
Boosting text segmentation via progressive classification. Knowl. Inf. Syst. 15(3): 285-320 (2008) - [c8]Eugenio Cesario
Distributed Data Mining Models as Services on the Grid. ICDM Workshops 2008: 486-495 - [c7]Jan Stender, Björn Kolbeck, Felix Hupfeld, Eugenio Cesario, Erich Focht, Matthias Hess, Jesus Malo, Jonathan Martí:
Striping without Sacrifices: Maintaining POSIX Semantics in a Parallel File System. LASCO 2008 - 2007
- [j1]Eugenio Cesario
Top-Down Parameter-Free Clustering of High-Dimensional Categorical Data. IEEE Trans. Knowl. Data Eng. 19(12): 1607-1624 (2007) - [c6]Eugenio Cesario
From Parallel Data Mining to Grid-Enabled Distributed Knowledge Discovery. RSFDGrC 2007: 25-36 - 2006
- [b1]Eugenio Cesario:
Advanced approaches to clustering high-dimensional categorical data. University of Calabria, Italy, 2006 - [c5]Fabrizio Angiulli
A Greedy Search Approach to Co-clustering Sparse Binary Matrices. ICTAI 2006: 363-370 - [c4]Eugenio Cesario, Giuseppe Manco, Riccardo Ortale:
Top-Down Parameter-Free Clustering of High-Dimensional Categorical Data. SEBD 2006: 80-92 - 2005
- [c3]Eugenio Cesario
An Incremental Clustering Scheme for Duplicate Detection in Large Databases. IDEAS 2005: 89-95 - [c2]Eugenio Cesario, Francesco Folino, Antonio Locane, Giuseppe Manco, Riccardo Ortale:
RecBoost: A Supervised Approach to Text Segmentation. SEBD 2005: 220-231 - 2004
- [c1]Eugenio Cesario
Putting Enhanced Hypermedia Personalization into Practice via Web Mining. DEXA 2004: 947-956
Coauthor Index
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last updated on 2024-12-10 20:46 CET by the dblp team
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