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

The degree distribution is an important characteristic of complex networks.In many applications, quantification of degree distribution in the form of afixed-length feature vector is a necessary step. On the other hand, we oftenneed to compare the degree distribution of two given networks and extract theamount of similarity between the two distributions. In this paper, we propose anovel method for quantification of the degree distributions in complexnetworks. Based on this quantification method,a new distance function is alsoproposed for degree distributions, which captures the differences in theoverall structure of the two given distributions. The proposed method is ableto effectively compare networks even with different scales, and outperforms thestate of the art methods considerably, with respect to the accuracy of thedistance function.

Quantification and Comparison of Degree Distributions in Complex Networks