Comprehensive Analysis of H2020 Funding Participation based on LDA Topic Modeling and Robust Outlier Identification-Reference-Cited by-同舟云学术

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Comprehensive Analysis of H2020 Funding Participation based on LDA Topic Modeling and Robust Outlier Identification

Published:2023-09-21 Issue: Volume:51 Page:000327-000332
ISSN:
Container-title:2023 IEEE 21st Jubilee International Symposium on Intelligent Systems and Informatics (SISY)
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Author:

Tolner Ferenc¹,Barta Balázs²,Eigner György³

Affiliation:

1. Óbuda University Doctoral School of Applied Informatics and Applied Mathematics,Pannon Business Network Association,Szombathely,Hungary

2. Pannon Business Network Association,Szombathely,Hungary

3. University Research and Innovation Center, Physiological Controls Research Center, Óbuda University, Biomatics and Applied Artificial Intelligence Institution, John von Neumann Faculty of Informatics, Óbuda University,Budapest,Hungary

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/10417734/10417736/10417969.pdf?arnumber=10417969

Reference28 articles.

1. What does Horizon 2020 contribute to? Analysing and visualising the community practices of Europe's largest research and innovation programme

2. Social Network Analysis in Wood Industry Projects

3. The science of networks: From society to the web (in hungarian);Barabasi,2006

4. Network of European Union–funded collaborative research and development projects

5. Power relations in European RDI-collaboration networks. Disparities in policy-driven opportunities for knowledge generation in ICT

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