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FAke News discovery and propagation from big Data ANalysis and artificial intelliGence Operations

CORDIS bietet Links zu öffentlichen Ergebnissen und Veröffentlichungen von HORIZONT-Projekten.

Links zu Ergebnissen und Veröffentlichungen von RP7-Projekten sowie Links zu einigen Typen spezifischer Ergebnisse wie Datensätzen und Software werden dynamisch von OpenAIRE abgerufen.

Leistungen

Application areas business requirements and preliminary exploitation plan

The document will analyse the business requirements of the application areas to improve the impact of the pilots.

Market Analysis and preliminary business requirement

This deliverable will report a preliminary market analysis and business requirement for the FANDANGO application areas. This report will also include the FANDANGO Innovation strategy.

Report replicability of the solution

This report will describe the aspects of scalability and replicability of the big data tool.

Technical requirements (platform and service requirements)

In collaboration and extension of D1.1, D1.2 and D1.3 this deliverable will define the technical work plan and system requirements necessary to fulfill the goals.

Pilots execution and evaluation plans

This deliverable contains the comprehensive pilot execution and evaluation plans (PEEPs) for each pilot use-case domain, detailing how the pilots will be executed and evaluated. The document will be revised accordingly as the project progresses.

Final Exploitation plan and technology uptake

This report will present a full exploitation plan and action/analysis of technology uptake from FANDANGO

FANDANGO platform setup defining process

The deliverable will provide the design and the specification of every single FANDANGO component as well as the description of their implementation, integration and validation process.

Data lake integration plan

This deliverable will describe how the FANDANGO project manages data throughout its life cycle, according to the regulatory framework.

Dissemination Plan

This deliverable will include a description of the dissemination strategies and activities to be followed by the FANDANGO partners, as well as KPIs and metrics to be monitored.

Data model and components

This deliverable will contain the organization of data elements and how are related with both internal and external modules.

First iteration piloting and validation report

This deliverable contains the updated PEEPs as well as an overview of the outcomes of the first pilot iteration for each use-case domain. It will also contain the results of the validation of the different piloting activities.

Impact Report

This deliverable present an assessment of the impact of the project, both qualitatively, through case studies that demonstrate its impact, and quantitatively, via the metrics developed in the Dissemination Plan (D.7.2).

FANDANGO Reference Architecture description

The deliverable will define FANDANGO reference architecture describing how the FANDANGO components will interact each other.

Data Interoperability and data model design

An initial list of available data will be collected very early. It contains the data which is available for starting the first pilots.

User Requirements

This deliverable will collect the user requirement and will be the basis od D2.4.

Second iteration piloting and validation report

This deliverable contains the updated PEEPs as well as an overview of the outcomes of the second pilot iteration for each use-case domain. It will also contain the results of the validation of the different piloting activities.

Copy-move detection on audio-visual content prototypes

The deliverable will provide both: a) a report providing a detailed state of the art of the topics of Task 4.3 as well as the algorithms that are selected to be integrated in FANDANGO prototypes, and b) a prototype deliverable of the work done in Task 4.3 and will deliver the appropriate software and a report acting as manual of the provided software.

Source credibility scoring, profiling and social graph analytics prototypes

The deliverable will provide both: a) a report providing a detailed state of the art of the topics of Task 4.4 as well as the algorithms that are selected to be integrated in FANDANGO prototypes, and b) a prototype deliverable of the work done in Task 4.4 and will deliver the appropriate software and a report acting as manual of the provided software.

Software updates of the modules and prototypes

This is a prototype deliverable that will provide updates in all modules of WP4 following the evaluation phase as well as a report with all the necessary details on the provided software.

Pre-processing set of tools

This deliverable will be formed by the software tools that normalize the incoming data.

Lightweight data shipping components development

This deliverable will be a software package containing the components for data lake with its corresponding relevancy label.

Development of project website

A platform for ongoing public engagement, including areas for news releases, project reports and technical documentation. Will include links to tools and source code created by the project, as well as datasets.

Multilingual text analytics for misleading messages detection prototypes

The deliverable will provide both: a) a report providing a detailed state of the art of the topics of Task 4.2 as well as the algorithms that are selected to be integrated in FANDANGO prototypes, and b) a prototype deliverable of the work done in Task 4.2 and will deliver the appropriate software and a report acting as manual of the provided software.

Ground truth development for FANDANGO system assessment

This deliverable will implement the data gathering tasks and data preparation for ML models.

Machine learnable scoring for fake news decision making prototypes

The deliverable will provide both: a) a report providing a detailed state of the art of the topics of Task 4.5 as well as the algorithms that are selected to be integrated in FANDANGO prototypes, and b) a prototype deliverable of the work done in Task 4.5 and will deliver the appropriate software and a report acting as manual of the provided software.

Spatio-temporal analytics and out of context fakeness markers prototypes

The deliverable will provide both: a) a report providing a detailed state of the art of the topics of Task 4.1 as well as the algorithms that are selected to be integrated in FANDANGO prototypes, and b) a prototype is a prototype of the work done in Task 4.1 and will deliver the appropriate software and a report acting as manual of the provided software.

Data Management Plan

This deliverable will describe how the FANDANGO project manages data throughout its life cycle, in order to be compliant to the regulatory framework.

Veröffentlichungen

Volume-of-Interest Aware Deep Neural Networks for Rapid Chest CT-Based COVID-19 Patient Risk Assessment

Autoren: Anargyros Chatzitofis, Pierandrea Cancian, Vasileios Gkitsas, Alessandro Carlucci, Panagiotis Stalidis, Georgios Albanis, Antonis Karakottas, Theodoros Semertzidis, Petros Daras, Caterina Giannitto, Elena Casiraghi, Federica Mrakic Sposta, Giulia Vatteroni, Angela Ammirabile, Ludovica Lofino, Pasquala Ragucci, Maria Elena Laino, Antonio Voza, Antonio Desai, Maurizio Cecconi, Luca Balzarini, Arturo
Veröffentlicht in: International Journal of Environmental Research and Public Health, Ausgabe 18/6, 2021, Seite(n) 2842, ISSN 1660-4601
Herausgeber: Int. J. Environ. Res. Public Health
DOI: 10.3390/ijerph18062842

Artificial Intelligence against disinformation: the FANDANGO practical case

Autoren: F. Nucci, S. Boi, M. Magaldi
Veröffentlicht in: IFDAD 2020, 2020
Herausgeber: IFDAD

Embedding Big Data in Graph Convolutional Networks

Autoren: G. Palaiopanos, P. Stalidis, T. Semertzidis, N. Vretos, P. Daras
Veröffentlicht in: 2019 IEEE International Conference on Engineering, Technology and Innovation, 2019
Herausgeber: IEEE

FANDANGO un approccio centrato sulla AI per contrastare la disinformazione

Autoren: Francesco Nucci, Massimo Magaldi, Luca Bevilacqua
Veröffentlicht in: Ital-IA, 2019
Herausgeber: Ital-IA

A Multi-Modal approach for FAke News discovery and propagation from big Data ANalysis and artificial inteliGence Operations

Autoren: D. Martín-Gutiérrez, G. Hernández-Peñaloza, J.M. Menéndez, F. Álvarez
Veröffentlicht in: NEM Summit, 2020
Herausgeber: Nem summit

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