On merging and dividing social graphs

• Autorzy: Held P. , Dockhorn A. , Kruse R.

Identyfikatory

DOI

10.1515/jaiscr-2015-0017

• Języki publikacji: EN

Abstrakty

EN

Modeling social interaction can be based on graphs. However most models lack the flexibility of including larger changes over time. The Barabási-Albert-model is a generative model which already offers mechanisms for adding nodes. We will extent this by presenting four methods for merging and five for dividing graphs based on the Barabási- Albert-model. Our algorithms were motivated by different real world scenarios and focus on preserving graph properties derived from these scenarios. With little alterations in the parameter estimation those algorithms can be used for other graph models as well. All algorithms were tested in multiple experiments using graphs based on the Barabási- Albert-model, an extended version of the Barabási-Albert-model by Holme and Kim, the Watts-Strogatz-model and the Erd˝os-Rényi-model. Furthermore we concluded that our algorithms are able to preserve different properties of graphs independently from the used model. To support the choice of algorithm, we created a guideline which highlights advantages and disadvantages of discussed methods and their possible use-cases.

Słowa kluczowe

EN

social interaction; modeling; Barabási-Albert-model; Watts-Strogatz-model; Erd˝os-Rényi-model; graph; algorithm

PL

interakcja społeczna; modelowanie; model Barabasi-Albert-Model; model Watts-Strogatz; model Erdős-Renyi; wykres; algorytm

• Wydawca: University of Social Sciences
• Czasopismo: Journal of Artificial Intelligence and Soft Computing Research
• Rocznik: 2015
• Tom: Vol. 5, No. 1
• Strony: 23--49
• Opis fizyczny: Bibliogr. 17 poz., rys., tab.

Twórcy

autor

Held P.

• Department of Knowledge Processing and Language Engineering Faculty of Computer Science, Otto von Guericke University Magdeburg Universitaetsplatz 2, 39106 Magdeburg, Germany

autor

Dockhorn A.

• Department of Knowledge Processing and Language Engineering Faculty of Computer Science, Otto von Guericke University Magdeburg Universitaetsplatz 2, 39106 Magdeburg, Germany

autor

Kruse R.

• Department of Knowledge Processing and Language Engineering Faculty of Computer Science, Otto von Guericke University Magdeburg Universitaetsplatz 2, 39106 Magdeburg, Germany

Bibliografia

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