English (United Kingdom)

https://curated-unify.zendy.io/wp-json/zendy-region/v1/featured_content/oa?rat=en

https://curated-unify.zendy.io/wp-json/zendy-region/v1/highlighted_journal/

Global: Zendy Tools annual

Presents the keyphrase highlighting as premium feature

Keyphrase Highlighting

Presents the summarisation as premium feature

Summarisation

Insights

Presents the pdf analysis as premium feature

PDF Analysis

Presents the zaia usage as premium feature

ZAIA

Global: Zendy Tools monthly

Global: Zendy Plus monthly

Presents the access of premium content as premium feature

Premium Content

Global: Zendy Plus annual

Global: Zendy Free Plan

Regarding the analysis of Web communication, social and complex networks thefast finding of most influential nodes in a network graph constitutes animportant research problem. We use two indices of the influence of those nodes,namely, PageRank and a Max-linear model. We consider the PageRank %both as%Galton-Watson branching process and as an autoregressive process with a randomnumber of random coefficients that depend on ranks of incoming nodes and theirout-degrees and assume that the coefficients are independent and distributedwith regularly varying tail and with the same tail index. Then it is provedthat the tail index and the extremal index are the same for both PageRank andthe Max-linear model and the values of these indices are found. Theachievements are based on the study of random sequences of a random length andthe comparison of the distribution of their maxima and linear combinations.

Extremes in Random Graphs Models of Complex Networks