Edge-cloud continuum solutions for urban mobility prediction and planning
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 …
efficiently collect and analyze data generated by IoT devices. In this paper, we investigate to …
Knowledge discovery from large amounts of social media data
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 …
such as sociology, political science, linguistics, and computer science. Large amounts of …
Using social media for sub-event detection during disasters
Social media platforms have become fundamental tools for sharing information during
natural disasters or catastrophic events. This paper presents SEDOM-DD (Sub-Events …
natural disasters or catastrophic events. This paper presents SEDOM-DD (Sub-Events …
A graph-based big data optimization approach using hidden Markov model and constraint satisfaction problem
To address the challenges of big data analytics, several works have focused on big data
optimization using metaheuristics. The constraint satisfaction problem (CSP) is a …
optimization using metaheuristics. The constraint satisfaction problem (CSP) is a …
Parallel extraction of Regions‐of‐Interest from social media data
Geotagged data gathered from social media can be used to discover places‐of‐interest
(PoIs) that have attracted many visitors. Since a PoI is generally identified by geographical …
(PoIs) that have attracted many visitors. Since a PoI is generally identified by geographical …
Boosting HPC data analysis performance with the ParSoDA-Py library
Develo** and executing large-scale data analysis applications in parallel and distributed
environments can be a complex and time-consuming task. Developers often find themselves …
environments can be a complex and time-consuming task. Developers often find themselves …
Autotuning of exascale applications with anomalies detection
The execution of complex distributed applications in exascale systems faces many
challenges, as it involves empirical evaluation of countless code variations and application …
challenges, as it involves empirical evaluation of countless code variations and application …
A graph-based big data optimization approach using hidden Markov model and constraint satisfaction problem
S Imad, A Samir, B Abdelkrim - Journal of Big Data, 2021 - search.proquest.com
To address the challenges of big data analytics, several works have focused on big data
optimization using metaheuristics. The constraint satisfaction problem (CSP) is a …
optimization using metaheuristics. The constraint satisfaction problem (CSP) is a …
Monitoring of exascale data processing
Exascale systems are a hot topic of research in computer science. These systems in contrast
to current Cloud, Big Data and HPC systems will routinely contain hundreds of thousand of …
to current Cloud, Big Data and HPC systems will routinely contain hundreds of thousand of …
A Systematic Map** Study of Italian Research on Workflows
An entire ecosystem of methodologies and tools revolves around scientific workflow
management. They cover crucial non-functional requirements that standard workflow …
management. They cover crucial non-functional requirements that standard workflow …