Centrality measures in multi-layer knowledge graphs

• Autorzy: Dorpinghaus Jens , Weil Vera , Duing Carsten , Sommer Martin W.

Identyfikatory

DOI

10.15439/2022F43

• Konferencja: 17th Conference on Computer Science and Intelligence Systems
• Języki publikacji: EN

Abstrakty

EN

Knowledge graphs play a central role for linkingdifferent data which leads to multiple layers. Thus, they are widely used in big data integration, especially for connecting data from different domains. Few studies have investigated the questions how multiple layers within graphs impact methods and algorithms developed for single-purpose networks, for example social networks. This manuscript investigates the impact on the centrality measures of graphs with multiple layers compared to a those measures in single-purpose graphs. In particular, (a) we develop an experimental environment to (b) evaluate two different centrality measures --- degree and betweenness centrality --- on random graphs inspired by social network analysis: small-world and scale-free networks. The presented approach (c) shows that the graph structures and topology has a great impact on its robustness for additional data stored. Although the experimental analysis of random graphs allows us to make some basic observations we will (d) make suggestions for additional research on particular graph structures that have a great impact on the stability of networks.

• Wydawca: Polskie Towarzystwo Informatyczne
• Czasopismo: Annals of Computer Science and Information Systems
• Rocznik: 2022
• Tom: Vol. 32
• Strony: 163--170
• Opis fizyczny: Bibliogr. 28 poz., rys., tab., wykr.

Twórcy

autor

Dorpinghaus Jens

• Federal Institute for Vocational Education and Training (BIBB), Bonn, Germany
• University Koblenz-Landau, Koblenz, Germany

• https://orcid.org//0000-0003-0245-7752

autor

Weil Vera

• Department for Mathematics and Computer Science, University of Cologne, Germany

autor

Duing Carsten

• University Koblenz-Landau, Koblenz, Germany

autor

Sommer Martin W.

• Argelander-Institut fur Astronomie, Bonn, Germany

Bibliografia

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Uwagi

Opracowanie rekordu ze środków MEiN, umowa nr SONP/SP/546092/2022 w ramach programu "Społeczna odpowiedzialność nauki" - moduł: Popularyzacja nauki i promocja sportu (2022-2023).