Detecting and analyzing dense groups or communities from social and information networks
has attracted immense attention over the last decade due to its enormous applicability in …

The detection of community structures is a crucial research area. The problem of community
detection has received considerable attention from a large portion of the scientific …

In urban areas, the spatial configuration of urban elements is vital to the sustainable
development of cities. Due to the inherent spatial and networked characteristics of UBNs …

Large-scale analysis of functional MRI data has revealed that brain regions can be grouped
into stable “networks” or communities. In many instances, the communities are characterized …

The detection of community structures is a very crucial research area. The problem of
community detection has received considerable attention from a large portion of the …

Community detection is an important issue due to its wide use in designing network
protocols such as data forwarding in Delay Tolerant Networks (DTN) and worm containment …

Community identification refers to the process of selecting dense clusters with sparse
connections to the rest of the graph. These communities naturally overlap in many social …

In the field of research, Social Network Analysis is prevalent domain which pulls the
attention of many data mining experts. Social network analysis is the specific field of …

In this paper, a unique algorithm is proposed to detect overlap** communities in the un-
weighted and weighted networks with considerable accuracy. The maximal cliques …