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Complex Networks and Artificial Intelligence

Group
Gruppo di ricerca attivo nel settore delle reti complesse e delle applicazioni dell’intelligenza artificiale alle reti complesse
Address:
Dipartimento MIFT (Sede temporanea: Dipartimento di Ingegneria, stanza 703)
date/time interval:
(January 1, 2010 - )
  • Overview
  • Research Fields
  • Affiliation
  • Outputs
  • Contact

Overview

Term type

Gruppo di ricerca coordinata

Linked Units (3)

Dipartimento di Civiltà antiche e moderne
Dipartimento di Scienze cognitive, psicologiche, pedagogiche e degli studi culturali
Dipartimento di Scienze matematiche e informatiche, scienze fisiche e scienze della terra

Research Fields

Concepts (9)


PE6_10 - Web and information systems, database systems, information retrieval and digital libraries, data fusion - (2020)

PE6_11 - Machine learning, statistical data processing and applications using signal processing (e.g. speech, image, video) - (2020)

PE6_12 - Scientific computing, simulation and modelling tools - (2020)

PE6_7 - Artificial intelligence, intelligent systems, multi agent systems - (2020)

Goal 11: Sustainable cities and communities

Goal 3: Good health and well-being

Goal 9: Industry, Innovation, and Infrastructure

Settore INF/01 - Informatica

Settore ING-INF/05 - Sistemi di Elaborazione delle Informazioni

Keywords (7)

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  • decrescent
Data Science
Data mining
Intelligenza Artificiale
Link prediction
Reti complesse
Reti complesse, Intelligenza Artificiale, Reti criminali, Link prediction, Data mining, Data Science
Reti criminali
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Overview

1. Mining and analysis of complex networks This is the oldest research area of the group, as it dates back to 2010. It mainly deals with the creation of networks (assemblies of entities and their pairwise relations), their analysis using the tools provided by the Social Network Analysis and the application of algorithms borrowed from Artificial Intelligence (link prediction). The group benefited from the collaboration with the 'Arma dei Carabinieri' in studying official documents related to judicial acts against criminal organizations, mining criminal networks and studying them. 2. Artificial Intelligence for Health This line of research, in collaboration with CNR, aims at applying most recent and insightful algorithms of Artificial Intelligence to the prediction of the insurgence of pathologies in patients under treatment for kidney diseases. 3. Neural Networks for Complex Networks This is a recent area of interest. It benefits from the collaboration with scientists from the Chongqing University of Technology who are experts in Neural Networks, which are the cutting edge of research in Computer Science. We are currently applying some architectures of Neural Networks to Complex Network aiming at empowering link prediction and community detection.
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Affiliation

Has member

FIUMARA Giacomo

List of all contributors

Prof. Xiaoyang Liu - Chongqing University of Technology School of Computer Science and Engineering China, Prof. Antonio Liotta - Libera Università di Bolzano Facoltà di Scienze e Tecnologie Informatiche, Dott. Lucia Cavallaro - Libera Università di Bolzano Facoltà di Scienze e Tecnologie Informatiche, Dott. Xiang Li - Chongqing University of Technology School of Computer Science and Engineering China

Members (4)

DE MEO Pasquale
FICARA Annamaria
LICARI CLAUDIA
PEDALA' CARLO

Outputs

Publications (29)

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  • Open
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  • Mixed
  • Embargoed
  • Reserved

Contact

Email address

giacomo.fiumara@unime.it
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