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

Clustering the nodes of a graph allows the analysis of the topology of anetwork.  The stochastic block model is a clustering method based on a probabilisticmodel. Initially developed for binary networks it has recently been extended tovalued networks possibly with covariates on the edges.  We present an implementation of a variational EM algorithm. It is writtenusing C++, parallelized, available under a GNU General Public License (version3), and can select the optimal number of clusters using the ICL criteria. Itallows us to analyze networks with ten thousand nodes in a reasonable amount oftime.

Wmixnet: Software for Clustering the Nodes of Binary and Valued Graphs using the Stochastic Block Model