Zobrazeno 1 - 10
of 41
pro vyhledávání: '"Loris Belcastro"'
Publikováno v:
IEEE Access, Vol 11, Pp 38864-38874 (2023)
In recent years, there has been an increase in the use of edge-cloud continuum solutions to efficiently collect and analyze data generated by IoT devices. In this paper, we investigate to what extent these solutions can manage tasks related to urban
Externí odkaz:
https://doaj.org/article/15639bd8a56d4413a78dc116065e50d1
Publikováno v:
Algorithms, Vol 16, Iss 12, p 542 (2023)
Since the advent of Bitcoin, the cryptocurrency landscape has seen the emergence of several virtual currencies that have quickly established their presence in the global market. The dynamics of this market, influenced by a multitude of factors that a
Externí odkaz:
https://doaj.org/article/3bca031ecde14e5fb65d088cdb4f5b41
Autor:
Loris Belcastro, Riccardo Cantini, Fabrizio Marozzo, Alessio Orsino, Domenico Talia, Paolo Trunfio
Publikováno v:
Journal of Big Data, Vol 9, Iss 1, Pp 1-50 (2022)
Abstract In the age of the Internet of Things and social media platforms, huge amounts of digital data are generated by and collected from many sources, including sensors, mobile devices, wearable trackers and security cameras. This data, commonly re
Externí odkaz:
https://doaj.org/article/047196eced554a8b93b24aea5a10a2d5
Autor:
Loris Belcastro, Fabrizio Marozzo, Domenico Talia, Paolo Trunfio, Francesco Branda, Themis Palpanas, Muhammad Imran
Publikováno v:
Journal of Big Data, Vol 8, Iss 1, Pp 1-22 (2021)
Abstract Social media platforms have become fundamental tools for sharing information during natural disasters or catastrophic events. This paper presents SEDOM-DD (Sub-Events Detection on sOcial Media During Disasters), a new method that analyzes us
Externí odkaz:
https://doaj.org/article/388557d5e833433cb3f55edf4f65faa1
Publikováno v:
IEEE Access, Vol 9, Pp 47354-47364 (2021)
Task scheduling is a crucial key component for the efficient execution of data-intensive applications on distributed environments, by which many machines must be coordinated to reduce execution times and bandwidth consumption. This paper presents ADA
Externí odkaz:
https://doaj.org/article/eea8a12aed8e47fea4716e9dbec66cd9
Publikováno v:
IEEE Access, Vol 8, Pp 47177-47187 (2020)
Social media analysis is a fast growing research area aimed at extracting useful information from social media platforms. This paper presents a methodology, called IOM-NN (Iterative Opinion Mining using Neural Networks), for discovering the polarizat
Externí odkaz:
https://doaj.org/article/23d3609d0fd44017a0bf3416b55604d0
Autor:
Fabrizio Marozzo, Loris Belcastro
Publikováno v:
Applied Sciences, Vol 12, Iss 20, p 10567 (2022)
With the spread of the Internet of Things, large amounts of digital data are generated and collected from different sources, such as sensors, cameras, in-vehicle infotainment, smart meters, mobile devices, applications, and web services [...]
Externí odkaz:
https://doaj.org/article/667df31fe78947c7a22e26e51c97bd08
Publikováno v:
Applied Sciences, Vol 12, Iss 3, p 1209 (2022)
In recent years, social media analysis is arousing great interest in various scientific fields, such as sociology, political science, linguistics, and computer science. Large amounts of data gathered from social media are widely analyzed for extracti
Externí odkaz:
https://doaj.org/article/1aab739b33ea495fabb0187c97b8c9ff
Autor:
Ludovica C Busi, Consuelo Ceccarelli, Melissa Casella, Maria Gabriele, Sabrina Maffi, Eugenia Scaricamazza, Simone Migliore, Maria Pia Abruzzese, Federica Perrone, Loris Belcastro, Tommaso Mazza, Barbara D’Alessio, Ferdinando Squitieri
Publikováno v:
H: Clinical care and clinical services.
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::ceda034e5c3aa1f8de5fc8ba7f7b5dce
https://doi.org/10.1136/jnnp-2022-ehdn.175
https://doi.org/10.1136/jnnp-2022-ehdn.175
Autor:
Loris Belcastro, Francesco Branda, Riccardo Cantini, Fabrizio Marozzo, Domenico Talia, Paolo Trunfio
Publikováno v:
Social Network Analysis and Mining. 12
Every day millions of people use social media platforms by generating a very large amount of opinion-rich data, which can be exploited to extract valuable information about human dynamics and behaviors. In this context, the present manuscript provide
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::8a0fd72999222a9f571dd858d90102a7
https://doi.org/10.1007/s13278-022-00913-9
https://doi.org/10.1007/s13278-022-00913-9