42298

Автор(ы): 

Автор(ов): 

1

Параметры публикации

Тип публикации: 

Тезисы доклада

Название: 

Extremes in Random Graphs Models of Complex Networks

ISBN/ISSN: 

978-618-5180-22-5

Наименование конференции: 

  • 17th International Conference on the Applied Stochastic Models and Data Analysis (ASMDA 2017, London) and Workshop DEMOGRAPHICS2017

Наименование источника: 

  • Book of Abstracts of the 17th Applied Stochastic Models and Data Analysis International Conference with the 6th Demographics Workshop (London, 2017)

Город: 

  • London

Издательство: 

  • ISAST: International Society for the Advancement of Science and Technology

Год издания: 

2017

Страницы: 

129
Аннотация
Regarding the analysis of Web communication, social and complex networks the fast finding of most influential nodes in a network graph constitutes an important research problem. We use two indices of the influence of those nodes, namely, PageRank and a Max-linear model. We consider the PageRank as an autoregressive process with a random number of random coefficients that depend on ranks of incoming nodes and their out-degrees and assume that the coefficients are independent and distributed with regularly varying tail and with the same tail index. Then it is proved that the tail index and the extremal index are the same for both PageRank and the Max-linear model and the values of these indices are found. The achievements are based on the study of random sequences of a random length and the comparison of the distribution of their maxima and linear combinations. Keywords: Extremal index, PageRank, Max-Linear model, Branching process, Autoregressive process, Tail index, Complex Networks

Библиографическая ссылка: 

Маркович Н.М. Extremes in Random Graphs Models of Complex Networks / Book of Abstracts of the 17th Applied Stochastic Models and Data Analysis International Conference with the 6th Demographics Workshop (London, 2017). London: ISAST: International Society for the Advancement of Science and Technology, 2017. С. 129.