54824

Автор(ов): 

2

Параметры публикации
Тип публикации: 
Доклад
Название: 
Random Graph Node Classification by Extremal Index of PageRank
ISBN/ISSN: 
978-3-030-36624-7
DOI: 
10.1007/978-3-030-36625-4_34
Наименование конференции: 
22nd International Conference on Distributed Computer and Communication Networks: Control, Computation, Communications (DCCN-2019, Moscow)
Наименование источника: 
Proceedings of the 22nd International Conference on Distributed Computer and Communication Networks: Control, Computation, Communications (DCCN-2019, Moscow)
Обозначение и номер тома: 
vol 1141
Город: 
Cham
Издательство: 
Springer
Год издания: 
2019
Страницы: 
424-435
Аннотация
Taking account for the graph randomness, our purpose is a node classification by their extremal indexes (EI) as the local dependence measure of node influence characteristics. The EI was calculated by node PageRanks of the local tree related to the node, which is a kind of Thorny Branching Tree (TBT). The blocks estimator was used for the EI estimation by sliding and disjoint block definitions. The classification by the node EI value and the average block size for the local node TBT was introduced for simulated graphs by the Forest Fire and Erdős-Rényi Models and the Berkeley-Stanford dataset as a real example. The new classification methodology is proposed irrespective on the graph structure.
Библиографическая ссылка: 
Маркович Н.М., Рыжов М.С. Random Graph Node Classification by Extremal Index of PageRank / Proceedings of the 22nd International Conference on Distributed Computer and Communication Networks: Control, Computation, Communications (DCCN-2019, Moscow). Cham: Springer, 2019. vol 1141. С. 424-435.