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

One of the longstanding problems in spectral graph clustering (SGC) is theso-called model order selection problem: automated selection of the correctnumber of clusters. This is equivalent to the problem of finding the number ofconnected components or communities in an undirected graph. In this paper, wepropose AMOS, an automated model order selection algorithm for SGC. Based on arecent analysis of clustering reliability for SGC under the randominterconnection model, AMOS works by incrementally increasing the number ofclusters, estimating the quality of identified clusters, and providing a seriesof clustering reliability tests. Consequently, AMOS outputs clusters of minimalmodel order with statistical clustering reliability guarantees. Comparing tothree other automated graph clustering methods on real-world datasets, AMOSshows superior performance in terms of multiple external and internalclustering metrics.

AMOS: An Automated Model Order Selection Algorithm for Spectral Graph Clustering