Fabrizio Marozzo

Fabrizio Marozzo
Università della Calabria | Università della Calabria · Department of Computer Engineering, Modelling, Electronics and Systems (DIMES)

Assistant Professor in Computer Engineering at the University of Calabria, Italy

About

95
Publications
31,605
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1,069
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Introduction
Fabrizio Marozzo is an Assistant Professor in Computer Engineering at University of Calabria. His current research focuses on parallel and distributed computing, cloud computing, intelligent systems, peer-to-peer networks, programming models, social network and big data analysis. He has been member of program committee of several scientific conferences and reviewer for different international journals. He has been serving as associate editor the IEEE Access journal and the IJISTA journal.
Additional affiliations
January 2019 - June 2022
Università della Calabria
Position
  • Professor (Assistant)

Publications

Publications (95)
Poster
Full-text available
Dear Colleagues, Big data analysis is enabling researchers and data scientists to extract useful information and knowledge to make new discoveries and support decision-making processes. To this end, the use of advanced and scalable algorithms, along with parallel programming frameworks and high-performance computers, is commonly used to solve big...
Article
Full-text available
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 provides a precise view of the 2020 US presidential election by jointly applying topic discovery, opinion m...
Conference Paper
High-level programming models can help application developers to access and use resources without the need to manage low-level architectural entities, as a parallel programming model defines a set of programming abstractions that simplify the way by which a programmer structures and expresses her/his algorithm. Early proposals of Exascale programmi...
Article
The evolution of High-Performance Computing (HPC) platforms enables the design and execution of progressively larger and more complex workflow applications in these systems. The complexity comes not only from the number of elements that compose the workflows but also from the type of computations they perform. While traditional HPC workflows target...
Conference Paper
In recent years machine learning (ML) has achieved great results in providing solutions for many tasks such as speech recognition, sentiment analysis, email spam filters, fraud prevention and so on. The rapid spread of the Internet of Things (IoT), with billions of connected devices, has generated huge amounts of data and asks for decentralized sol...
Preprint
Full-text available
The evolution of High-Performance Computing (HPC) platforms enables the design and execution of progressively larger and more complex workflow applications in these systems. The complexity comes not only from the number of elements that compose the workflows but also from the type of computations they perform. While traditional HPC workflows target...
Article
Full-text available
The evolution of High-Performance Computing (HPC) platforms enables the design and execution of progressively larger and more complex workflow applications in these systems. The complexity comes not only from the number of elements that compose the workflows but also from the type of computations they perform. While traditional HPC workflows target...
Article
Full-text available
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 extracting useful information concerning people’s behaviors and interactions. In particular, they can be exp...
Article
Full-text available
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 referred to as Big Data, is challenging current storage, processing, and analysis capabilities. New models, lan...
Article
Full-text available
Social media platforms are part of everyday life, allowing the interconnection of people around the world in large discussion groups relating to every topic, including important social or political issues. Therefore, social media have become a valuable source of information-rich data, commonly referred as Social Big Data, effectively exploitable to...
Poster
Full-text available
Dear Colleagues, The purpose of this Special Issue is to address, by using recent advances in artificial intelligence, machine learning and big data, the challenges of sustainable communities that generate large volumes of data from sensors, smart meters, IoT devices and smartphones. Sustainable communities imply a consistent use of technology for...
Presentation
Full-text available
The purpose of this Special Issue is to address, by using recent advances in artificial intelligence, machine learning and big data, the challenges of sustainable communities that generate large volumes of data from sensors, smart meters, IoT devices and smartphones. Sustainable communities imply a consistent use of technology for the benefit of ci...
Article
Full-text available
The execution of complex distributed applications in exascale systems faces many challenges, as it involves empirical evaluation of countless code variations and application run-time parameters over a heterogeneous set of resources. To mitigate these challenges, the research field of autotuning has gained momentum. The autotuning automates identify...
Article
Full-text available
Social media platforms are increasingly used to convey advertising campaigns for products or services. A key issue is to identify an appropriate set of influencers within a social network, investing resources to get them to adopt a product. Influence maximization is an optimization problem that aims at finding a small set of users that maximize the...
Conference Paper
Full-text available
Researchers and leading IT companies are increasingly proposing hybrid cloud/edge solutions, which allow to move part of the workload from the cloud to the edge nodes, by reducing the network traffic and energy consumption, but also getting low latency responses near to real time. This paper proposes a novel hybrid cloud/edge architecture for effic...
Conference Paper
Full-text available
Nowadays, the number of people who prefer to make online purchases on e-commerce platforms is constantly increasing. Online shopping turns out to be fast and cheap but it also involves some risks. In fact, it sometimes happens that a product, once received, is smaller or bigger than expected, or does not comply with what is described on the purchas...
Article
Full-text available
Social media represents a rich environment to collect huge amounts of data containing useful information about people’s behaviors and interactions. In particular, such information has been widely exploited for analyzing the mobility of people, as geotagged social media posts allow to extract accurate patterns on movements of people. This paper pres...
Article
Full-text available
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 user posts to discover sub-events that occurred after a disaster (e.g., collapsed buildings, broken gas pipes,...
Article
Full-text available
The growing use of microblogging platforms is generating a huge amount of posts that need effective methods to be classified and searched. In Twitter and other social media platforms, hashtags are exploited by users to facilitate the search, categorization and spread of posts. Choosing the appropriate hashtags for a post is not always easy for user...
Article
Full-text available
Workflows are largely used to orchestrate complex sets of operations required to handle and process huge amounts of data. Parallel processing is often vital to reduce execution time when complex data-intensive workflows must be run efficiently, and at the same time, in-memory processing can bring important benefits to accelerate execution. However,...
Chapter
Full-text available
Pharmacogenomics is an important research field that studies the impact of genetic variation of patients on drug responses, looking for correlations between Single Nucleotide Polymorphisms (SNPs) of patient genome and drug toxicity or efficacy. The large number of available samples and the high resolution of the instruments allow microarray platfor...
Chapter
Full-text available
Every day billions of people access web sites, blogs, and social media. Often they use their mobile devices and produce huge amount of data that can be effectively exploited for extracting valuable information concerning human dynamics and behaviors. Such data, commonly referred as Big Data, contains rich information about user activities, interest...
Article
Full-text available
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 ADAGE, a data-aware scheduler designed to efficiently execute data-intensive workflows in large-scale c...
Article
Full-text available
In recent years the demand for collective mobility services has registered a significant growth. In particular, the long-distance coach market has undergone an important change in Europe since FlixBus adopted a dynamic pricing strategy, providing low-cost transport services and an efficient and fast information system. This paper presents a methodo...
Chapter
Full-text available
Social media analysis is a fast growing research area aimed at extracting useful information from social media. Several opinion mining techniques have been developed for capturing the mood of social media users related to a specific topic of interest. This paper shows how to use a cloud-based algorithm aimed at discovering the polarization of socia...
Conference Paper
Full-text available
This paper presents the main features and the programming constructs of the DCEx programming model designed for the implementation of data-centric large-scale parallel applications on Exascale computing platforms. To support scalable parallelism, the DCEx programming model employs private data structures and limits the amount of shared data among p...
Article
Full-text available
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 polarization of social media users during election campaigns characterized by the competition of political fa...
Article
Full-text available
File sharing is one of the leading Internet applications of P2P technology. Given the high number of computer nodes involved in peer‐to‐peer networks, reducing their aggregate energy consumption is an important challenge to be faced. In this paper, we show how the sleep‐and‐wake energy saving approach can be exploited to reduce energy consumption i...
Conference Paper
Full-text available
The convergence between HPC and Big Data processing can be pur-sued also providing high-level parallel programming tools for developing Big data analysis. Software systems for social data mining provide algorithms and tools for extracting useful knowledge from user-generated social media data. ParSoDA (Parallel Social Data Analytics) is a high-leve...
Conference Paper
Full-text available
This paper presents the main features and the programming constructs of the DCEx programming model designed for the implementation of data-centric large-scale parallel applications on Exascale computing platforms. To support scalable parallelism, the DCEx programming model employs private data structures and limits the amount of shared data among p...
Conference Paper
Full-text available
Nowadays, massive amounts of data are acquired, transferred, and analyzed nearly in real-time by utilizing a large number of computing and storage elements interconnected through high-speed communication networks. However, one issue that still requires research effort is to enable efficient monitoring of applications and infrastructures of such com...
Article
Full-text available
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 coordinates of a single point, it is hard to match it with people trajectories. Therefore, we define an area, called region‐of‐interest (RoI), represented by the boundarie...
Chapter
Full-text available
In recent years, the demand for collective mobility services is characterized by a significant growth. The long-distance coach market has undergone an important change in Europe since FlixBus adopted a dynamic pricing strategy, providing low-cost transport services and an efficient and fast information system. This paper presents a methodology, cal...
Conference Paper
Full-text available
— Social media analysis is a fast growing research area aimed at extracting useful information from social media. This paper presents a methodology aimed at discovering the behavior of social media users during election campaigns characterized by the competition of political parties. The methodology analyzes the posts published by social media user...
Conference Paper
Full-text available
Social media analysis is a fast growing research area aimed at extracting useful information from social media. Several opinion mining techniques have been developed for capturing the mood of social media users related to a specific topic of interest. This paper shows how to use a cloud-based algorithm aimed at discovering the polarization of socia...
Article
Full-text available
Software systems for social data mining provide algorithms and tools for extracting useful knowledge from user-generated social media data. ParSoDA (Parallel Social Data Analytics) is a high-level library for developing parallel data mining applications based on the extraction of useful knowledge from large dataset gathered from social media. The l...
Chapter
Full-text available
Software systems for social media analysis provide algorithms and tools for extracting useful knowledge from user-generated social media data. ParSoDA (Parallel Social Data Analytics) is a Java library for developing parallel data analysis applications based on the extraction of useful knowledge from social media data. This library aims at reducing...
Article
Full-text available
Big Data analysis refers to advanced and efficient data mining and machine learning techniques applied to large amount of data. Research work and results in the area of Big Data analysis are continuously rising, and more and more new and efficient architectures, programming models, systems, and data mining algorithms are proposed. Taking into accou...
Article
Full-text available
Social media analysis is a fast growing research area aimed at extracting useful information from social networks. Recent years have seen a great interest from academic and business world in using social media to measure public opinion. This paper presents a methodology aimed at discovering the behavior of social network users and how news sites ar...
Chapter
Full-text available
This article describes the main services provided by the most popular cloud infrastructures currently in use. The systems presented in this article are either public clouds - Amazon Web Services (AWS), Google Cloud Platform, Microsoft Azure and IBM Bluemix - or private clouds - OpenStack, OpenNebula and Eucalyptus. The formers provide a variety of...
Chapter
Full-text available
This article describes some of the most representative cloud computing development environments classified into four types. Integrated development environments are used to code, debug, deploy and monitor cloud applications that are executed on a cloud infrastructure. Parallel-processing development environments are used to define parallel applicati...
Article
Full-text available
Geotagged data gathered from social media can be used to discover interesting locations visited by users called Places-of-Interest (PoIs). Since a PoI is generally identified by the geographical coordinates of a single point, it is hard to match it with user trajectories. Therefore, it is useful to define an area, called Region-of-Interest (RoI), t...
Article
Full-text available
The widespread use of social media platforms allows scientists to collect huge amount of data posted by people interested in a given topic or event. This data can be analyzed to infer patterns and trends about people behaviors related to a topic or an event on a very large scale. Social media posts are often tagged with geographical coordinates or...
Article
Full-text available
As data intensive scientific computing systems become more widespread, there is a necessity of simplifying the development, deployment, and execution of complex data analysis applications for scientific discovery. The scientific workflow model is the leading approach for designing and executing data-intensive applications in high-performance comput...
Conference Paper
Full-text available
As scientific data analysis applications become more and more complex, there is a great need to simplify the definition and execution of such applications, particularly when dealing with large datasets. The Data Mining Cloud Framework (DMCF) is a system allowing domain experts to design and execute complex data analysis workflows on cloud platforms...
Chapter
Full-text available
MapReduce is one of the most popular programming models for parallel data processing in Cloud environments. Standard MapReduce implementations are based on centralized master-slave architectures that do not cope well with dynamic Cloud environments in which nodes may join and leave the network at high rates. In this chapter we describe P2P-MapReduc...
Chapter
Full-text available
The huge amount of data generated, the speed at which it is produced, and its heterogeneity in terms of format, represent a challenge to the current storage, process and analysis capabilities. Those data volumes, commonly referred as Big Data, can be exploited to extract useful information and to produce helpful knowledge for science, industry, pub...