42808

Автор(ов): 

3

Параметры публикации
Тип публикации: 
Статья в журнале/сборнике
Название: 
Nonparametric Analysis of Extremes on Web Graphs: PageRank versus Max-Linear Model
ISBN/ISSN: 
978-3-339-66835-2
Наименование источника: 
Communications in Computer and Information Science (20th International Conference DCCN2017 Moscow)
Обозначение и номер тома: 
CCIS, Volume 700
Город: 
Moscow
Издательство: 
Springer
Год издания: 
2017
Страницы: 
13-26
Аннотация
We analyze the cluster structure in large networks by means of clusters of exceedances regarding the influence characteristics of nodes. As the latter characteristics we use PageRank and the Max-Linear model and compare their distributions and dependence structure. Due to the heaviness of tail and dependence of PageRank and Max-Linear model observations, the influence indices appear by clusters or conglomerates of nodes grouped around influential nodes. The mean size of such clusters is determined by a so called extremal index. It is related to the tail index that indicates the heaviness of the distribution tail. We consider graphs of Web pages and partition them into clusters of nodes by their influence.
Библиографическая ссылка: 
Маркович Н.М., Рыжов М.С., Krieger U. R. Nonparametric Analysis of Extremes on Web Graphs: PageRank versus Max-Linear Model // Communications in Computer and Information Science (20th International Conference DCCN2017 Moscow). 2017. CCIS, Volume 700. С. 13-26.