A Unified Framework for Exploratory Learning-Aided Community Detection Under Topological Uncertainty

arXiv:2304.04497v3 Announce Type: replace-cross
Abstract: In social networks, the discovery of community structures has received considerable attention as a fundamental problem in various network analysis tasks. However, due to privacy concerns or access restrictions, the network structure is often uncertain, thereby rendering established community detection approaches ineffective without costly network topology acquisition. To tackle this challenge, we present META-CODE, a unified framework for detecting overlapping communities via exploratory learning aided by easy-to-collect node metadata when networks are topologically unknown (or …

abstract analysis arxiv attention community concerns cs.ir cs.lg cs.ne cs.ni cs.si detection discovery exploratory framework network networks privacy rendering restrictions social social networks tasks type uncertain uncertainty