49460

Автор(ы): 

Автор(ов): 

2

Параметры публикации

Тип публикации: 

Статья в журнале/сборнике

Название: 

Stability and Similarity in Networks Based on Topology and Nodes Importance

ISBN/ISSN: 

978-3-030-05410-6

DOI: 

https://doi.org/10.1007/978-3-030-05411-3_8

Наименование источника: 

  • Studies in Computational Intelligence

Обозначение и номер тома: 

Vol. 812

Город: 

  • Cambridge

Издательство: 

  • Springer Link

Год издания: 

2019

Страницы: 

94-103 https://link.springer.com/chapter/10.1007/978-3-030-05411-3_8
Аннотация
We propose a model that evaluates how much a network has changed over time in terms of its structure and a set of central elements. The difference of structure is evaluated in terms of node-to-node influence using known nodes correspondence models. To analyze the changes in nodes centralities we adapt an idea of interval orders to the network theory. Our approach can be used to investigate dynamic changes in temporal networks and to identify suspicious or abnormal effects in terms of the topology and its critical members. We can also transform the stability measure to the similarity measure in order to cluster the network in some homogeneous periods. To test our model, we consider the international migration network from 1970 to 2015 and attempt to analyze main changes in migration patterns.

Библиографическая ссылка: 

Алескеров Ф.Т., Швыдун С.В. Stability and Similarity in Networks Based on Topology and Nodes Importance // Studies in Computational Intelligence. 2019. Vol. 812. С. 94-103 https://link.springer.com/chapter/10.1007/978-3-030-05411-3_8.