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

Community detection in networks refers to the process of seeking stronglyinternally connected groups of nodes which are weakly externally connected. Inthis work, we introduce and study a community definition based on internal edgedensity. Beginning with the simple concept that edge density equals number ofedges divided by maximal number of edges, we apply this definition to a varietyof node and community arrangements to show that our definition yields sensibleresults. Our community definition is equivalent to that of the Absolute PottsModel community detection method (Phys. Rev. E 81, 046114 (2010)), and theperformance of that method validates the usefulness of our definition across awide variety of network types. We discuss how this definition can be extendedto weighted, and multigraphs, and how the definition is capable of handlingoverlapping communities and local algorithms. We further validate ourdefinition against the recently proposed Affiliation Graph Model(arXiv:1205.6228 [cs.SI]) and show that we can precisely solve thesebenchmarks. More than proposing an end-all community definition, we explain howstudying the detailed properties of community definitions is important in orderto validate that definitions do not have negative analytic properties. We urgethat community definitions be separated from community detection algorithms andpropose that community definitions be further evaluated by criteria such asthese.

An edge density definition of overlapping and weighted graph communities