55805

Автор(ы): 
Алескеров Ф. Т. (ИПУ РАН, Лаборатория 25)
Автор(ов): 

3

Параметры публикации
Тип публикации: 
Статья в журнале/сборнике
Название: 
Indirect Influence Assessment in the Context of Retail Food Network
ISBN/ISSN: 
978-3-030-37156-2
DOI: 
https://doi.org/10.1007/978-3-030-37157-9_10
Наименование источника: 
Springer Proceedings in Mathematics & Statistics: Network Algorithms, Data Mining, and Applications
Обозначение и номер тома: 
Vol. 315. Network Algorithms, Data Mining, and Applications. NET 2018.
Город: 
Cham
Издательство: 
Springer Link
Год издания: 
2020
Страницы: 
143-160, https://link.springer.com/chapter/10.1007/978-3-030-37157-9_10
Аннотация
We consider an application of long-range interaction centrality (LRIC) to the problem of the influence assessment in the global retail food network. Firstly, we reconstruct an initial graph into the graph of directed intensities based on individual node’s characteristics and possibility of the group influence. Secondly, we apply different models of the indirect influence estimation based on simple paths and random walks. This approach can help us to estimate node-to-node influence in networks. Finally, we aggregate node-to-node influence into the influence index. The model is applied to the food trade network based on the World International Trade Solution database. The results obtained for the global trade by different product commodities are compared with classical centrality measures.
Библиографическая ссылка: 
Алескеров Ф.Т., Мещерякова Н.Г., Швыдун С.В. Indirect Influence Assessment in the Context of Retail Food Network / Springer Proceedings in Mathematics & Statistics: Network Algorithms, Data Mining, and Applications. Cham: Springer Link, 2020. Vol. 315. Network Algorithms, Data Mining, and Applications. NET 2018. С. 143-160, https://link.springer.com/chapter/10.1007/978-3-030-37157-9_10.