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 Plus annual

Presents the access of premium content as premium feature

Premium Content

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 Plus monthly

Global: Zendy Tools annual

Global: Zendy Tools monthly

Global: Zendy Free Plan

Social networks have become an inseparable part of human life and processingthem in an efficient manner is a top priority in the study of networks. Thesenetworks are highly dynamic and they are growing incessantly. Inspired by theconcept of triadic closure, we propose a probabilistic mechanism to model theevolution of these dynamic graphs. Although triadic closure is ubiquitous insocial networks and its presence helps forming communities, probabilisticmodels encapsulating it have not been studied adequately.  We theoretically analyze our model and show how to bound the growth rate ofsome characteristics of the graph, such as degree of vertices. Leveraging ourtheoretical results, we develop a scheduling subroutine to processmodifications of the graph in batches. Our scheduling subroutine is then usedto speed up the state-of-the-art algorithms with negligible loss in theirapproximation guarantees. We demonstrate the applicability of our method byapplying it to the densest subgraph and tri-densest subgraph discovery problem.

The Wedge Picking Model: A dynamic graph model based on triadic closure