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

In this paper we introduce a new method to locate highly connected clustersin a network. Our proposed approach adapts the HyperBall algorithm to localizeregions with a high density of small subgraph patterns in large graphs in amemory-efficient manner. We use this method to evaluate three measures ofsubgraph connectivity: conductance, the number of triangles, and transitivity.We demonstrate that our algorithm, applied to these measures, helps to identifyclustered regions in graphs, and provides good seed sets for communitydetection algorithms such as PageRank-Nibble. We analytically obtain theperformance guarantees of our new algorithms, and demonstrate theireffectiveness in a series of numerical experiments on synthetic and real-worldnetworks.

Locating highly connected clusters in large networks with HyperLogLog counters