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

Graph matching is a fruitful area in terms of both algorithms and theories.In this paper, we exploit the degree information, which was previously usedonly in noiseless graphs and perfectly-overlapping Erd\H{o}s--R\'enyi randomgraphs matching. We are concerned with graph matching of partially-overlappinggraphs and stochastic block models, which are more useful in tackling real-lifeproblems. We propose the edge exploited degree profile graph matching methodand two refined varations. We conduct a thorough analysis of our proposedmethods' performances in a range of challenging scenarios, including azebrafish neuron activity data set and a coauthorship data set. Our methods areproved to be numerically superior than the state-of-the-art methods.

Graph matching beyond perfectly-overlapping Erd\H{o}s--R\'enyi random graphs