Carmine Spagnuolo

University of Salerno | UNISA · Department of Computer Science DI

The metaverse is an immersive, multi-user, virtual world where humans, represented by avatars, can entertain, socialize, and collaborate. This demo proposes VRKG-CollaborativeExploration, a Virtual Reality application that enables users to join thematic and collaborative data-driven discussions in the social metaverse where data are retrieved from...

Hypergraphs have attracted increasing attention in recent years thanks to their flexibility in naturally modeling a broad range of systems where high-order relationships exist among their interacting parts. This survey reviews the newly born hypergraph representation learning problem, whose goal is to learn a function to project objects - most comm...

Agent-based models (ABMs) are one of the most effective and successful methods for analyzing real-world complex systems by investigating how modeling interactions on the individual level (i.e., micro-level) leads to the understanding of emergent phenomena on the system level (i.e., macro-level). ABMs represent an interdisciplinary approach to exami...

Last years witnessed a shift from the potential utility in digitisation to a crucial need to enjoy activities virtually. In fact, before 2019, data curators recognised the utility of performing data digitisation, while during the lockdown caused by the COVID-19, investing in virtual and remote activities to make culture survive became crucial as no...

The amount of accessible computational devices over the Internet offers an enormous but latent computational power. Nonetheless, the complexity of orchestrating and managing such devices requires dedicated architectures and tools and hinders the exploitation of this vast processing capacity. Over the last years, the paradigm of (Browser-based) Volu...

Knowledge Graphs are a critical source for Question Answering, but their potential may be threatened due to the complexity of their query languages, such as SPARQL. On the opposite side, Virtual Assistants have witnessed an extraordinary interest as they enable users to pose questions in natural language. Many companies and researchers have combine...

This work deals with a generalization of the minimum Target Set Selection (TSS) problem, a key algorithmic question in information diffusion research due to its potential commercial value. Firstly proposed by Kempe et al., the TSS problem is based on a linear threshold diffusion model defined on an input graph with node thresholds, quantifying the...

Agent-based simulations represent an effective scientific tool, with numerous applications from social sciences to biology, which aims to emulate or predict complex phenomena through a set of simple rules performed by multiple agents. To simulate a large number of agents with complex models, practitioners have developed high-performance parallel im...

Non-Pharmaceutical Interventions (NPIs) are essential measures that reduce and control a severe outbreak or a pandemic, especially in the absence of drug treatments. However, estimating and evaluating their impact on society remains challenging, considering the numerous and closely tied aspects to examine. This article proposes a fine-grain modelin...

This work introduces the problem of social influence diffusion in complex networks, where vertices are linked not only through simple pairwise relationships to other nodes but with groups of nodes of arbitrary size. A challenging problem that arises in this domain is to determine a small subset of nodes S (a target-set) able to spread their influen...

Cloud Computing is widely recognized as distributed computing paradigm for the next generation of dynamically scalable applications. Recently a novel service model, called Function-as-a-Service (FaaS), has been proposed, that enables users to exploit the computational power of cloud infrastructures, without the need to configure and manage complex...

The cloud computing paradigm has emerged as the backbone of modern price‐aware scalable computing systems. Many cloud service models are competing to become the leading doorway to access the computational power of cloud providers. Recently, a novel service model, called function‐as‐a‐service (FaaS), has been proposed, which enables users to exploit...

Real-world complex networks are usually being modeled as graphs. The concept of graphs assumes that the relations within the network are binary (for instance, between pairs of nodes); however, this is not always true for many real-life scenarios, such as peer-to-peer communication schemes, paper co-authorship, or social network interactions. For su...

The analysis of real systems and the development of predictive models to describe the evolution of real phenomena are challenging tasks that can improve the design of methodologies in many research fields. In this context, Agent-Based Model (ABM) can be seen as an innovative tool for modelling real-world complex simulations. This paper presents Rus...

Hypergraphs are natural generalization of graphs in which a single (hyper)edge can connect any number of vertices. As a result, hypergraphs are suitable and useful to model many important networks and processes. Typical applications are related to social data analysis and include situations such as exchanging emails with several recipients, reviewi...

Hypergraphs are natural generalization of graphs in which a single (hyper)edge can connect any number of vertices. As a result, hypergraphs are suitable and useful to model many important networks and processes. Typical applications are related to social data analysis and include situations such as exchanging emails with several recipients, reviewi...

MASON is a widely-used open-source agent-based simulation toolkit that has been in constant development since 2002. MASON’s architecture was cutting-edge for its time, but advances in computer technology now offer new opportunities for the ABM community to scale models and apply new modeling techniques. We are extending MASON to provide these oppor...

Scientific Computing (SC) is a multidisciplinary field that uses the computational approach to understand and study complex artificial and natural systems belonging many scientific sectors. Optimization via Simulation (OvS) is a fast developing area in SC field. OvS combines classical optimization algorithms and stochastic simulations to face probl...

Computational Social Science (CSS) involves interdisciplinary fields and exploits computational methods, such as social network analysis as well as computer simulation with the goal of better understanding social phenomena. Agent-Based Models (ABMs) represent an effective research tool for CSS and consist of a class of models, which, aim to emulate...

Agent-based simulations are becoming widespread among scientists from different areas, who use them to model increasingly complex problems. To cope with the growing computational complexity, parallel and distributed implementations have been developed for a wide range of platforms. However, it is difficult to have simulations that are portable to d...

Agent-based simulations are becoming widespread among scientists from different areas, who use them to model increasingly complex problems. To cope with the growing computational complexity, parallel and distributed implementations have been developed for a wide range of platforms. However, it is difficult to have simulations that are portable to d...

MASON is a widely-used open-source agent-based simulation toolkit that has been in constant development since 2002. MASON's architecture was cutting-edge for its time, but advances in computer technology now offer new opportunities for the ABM community to scale models and apply new modeling techniques. We are extending MASON to provide these oppor...

In order to increase transparency, Public Administrations (PAs) have their own portals to publish Open Data, resulting in more openness, reduced corruption and improved services. Open Data (OD) initiatives are achieving less citizens' engagement than expected. Hence, the need to find other ways and services to obtain more engagement and extract val...

Simulation models are becoming an increasingly popular tool for the analysis and optimization of complex real systems in different fields. Finding an optimal system design requires performing a large sweep over the parameter space in an organized way. Hence, the model optimization process is extremely demanding from a computational point of view, a...

Open Data are valuable initiatives in favour of transparency. Public administrations are increasing the availability of datasets for citizens, associations, innovators and other stakeholders, by releasing their data with open licenses. Open initiatives are achieving less success than expected, mainly due to the lack of engagement. There is a growin...

D-Mason framework is a parallel version of the Mason library for writing and running Agent-based simulations – a class of models that, by simulating the behavior of multiple agents, aims to emulate and/or predict complex phenomena. D-Mason has been conceived to harness the amount of unused computing power available in common installations like educ...

As high-performance computing resources have become increasingly available, new modes of computational processing and experimentation have become possible. This tutorial presents the Extreme-scale Model Exploration with Swift/T (EMEWS) framework for combining existing capabilities for model exploration approaches (e.g., model calibration, metaheuri...

This paper introduces the DatalEt-Ecosystem Provider (DEEP), an open source, extensible, modular and pluggable architecture providing datalets, which are web-component visualisations of datasets content. DEEP enables the shar-ing and collaboration around data visualisations, supporting for instance communities in public deliberation around Open Dat...

This paper focuses on innovative solutions to the problem of transparency in Public Administrations (PAs) by opening up public data and services so that citizens participation is facilitated and encouraged. We introduce the motivating principles and the architectural solutions to a Social Platform for Open Data, that is designed in order to provide...

Graph Partitioning is a key challenge problem with application in many scientific and technological fields. The problem is very well studied with a rich literature and is known to be NP-hard. Several heuristic solutions, which follow diverse approaches, have been proposed, they are based on different initial assumptions that make them difficult to...

In the last decade, the investigation of the social complexity has witnessed the rise of Computational Social Science, a research paradigm that heavily relies upon data and computation to foster our understanding of social phenomena. In this field, a key role is played by the explanatory and predictive power of agent-based social simulations that a...

Agent-based simulation models are a powerful experimental tool for research and management in many scientific and technological fields. D-Mason is a parallel version of Mason, a library for writing and running Agent-based simulations. In this paper, we present a novel development of D-Mason, a decentralized communication strategy which realizes a P...

Agent-Based simulation Models (ABMs) are a very powerful experimental tool of analysis, used in many scientific and technological communities of researchers, to assess and predict the dynamic unfolding of a series of events or processes, according to the imposition of certain conditions, given by the analyst. The computing power usually represents...

Agent-based simulation models are an increasingly popular tool for research and management in many fields. In executing such simulations "speed" is one of the most general and important issues because of the size and complexity of simulations. But another important issue is the effectiveness of the solution, which consists of how easily usable and...

Agent-Based Models (ABMs) are a class of models which, by simulating the behavior of multiple agents (i.e., ndependent actions, interactions and adaptation), aim to emulate and/or predict complex phenomena. One of the general features of ABM simulations is their experimental capacity, that requires a viable and reliable infrastructure to interact w...

Agent-based simulation models are an increasingly popular tool for research and management in many, different and diverse fields. In executing such simulations the "speed" is one of the most general and important issues. The traditional answer to this issue is to invest resources in deploying a dedicated installation of dedicated computers. In this...