Discovering communities of similar R&D projects

VÍTA, Martin. Discovering communities of similar R&D projects. In Proceedings of the 7th International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management (IC3K 2015) - Volume 3: KMIS. Lisbon; Portugal: SciTePress, 2015, p. 460-465. ISBN 978-989-758-158-8. Available from: https://dx.doi.org/10.5220/0005663004600465.

Basic information

• Original name: Discovering communities of similar R&D projects
• Authors: VÍTA, Martin (203 Czech Republic, guarantor, belonging to the institution).
• Edition: Lisbon; Portugal, Proceedings of the 7th International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management (IC3K 2015) - Volume 3: KMIS, p. 460-465, 6 pp. 2015.
• Publisher: SciTePress

Other information

• Original language: English
• Type of outcome: Proceedings paper
• Field of Study: 10201 Computer sciences, information science, bioinformatics
• Country of publisher: Portugal
• Confidentiality degree: is not subject to a state or trade secret
• Publication form: printed version "print"
• RIV identification code: RIV/00216224:14330/15:00087399
• Organization unit: Faculty of Informatics
• ISBN: 978-989-758-158-8
• Doi: http://dx.doi.org/10.5220/0005663004600465
• Keywords in English: Community discovery; Document similarity; Eigenvector centrality; Latent semantic analysis

Abstract

Datasets about research projects contain knowledge that is valuable for several types of subjects working in the R&D field - including innovative companies, research institutes and universities even individual researchers or research teams, as well as funding providers. The main goal of this paper is to introduce a software tool based on a reusable methodology that allows us to deal with similarity of projects in order to group them and provide a deeper insight into a structure of considered set of projects in a visual way. In our approach we use several concepts developed in social network analysis.