Stacked autoencoder-based community detection method via an ensemble clustering framework
R Xu, Y Che, X Wang, J Hu, Y ** community detection using disjoint community structures
While there has been a plethora of approaches for detecting disjoint communities from real-
world complex networks, some methods for detecting overlap** community structures …
world complex networks, some methods for detecting overlap** community structures …
Anca: Attributed network clustering algorithm
Graph clustering techniques are very useful for detecting densely connected groups in large
graphs. Many existing graph clustering methods mainly focus on the topological structure …
graphs. Many existing graph clustering methods mainly focus on the topological structure …
Overlap** community detection using superior seed set selection in social networks
Community discovery in the social network is one of the tremendously expanding areas
which earn interest among researchers for past one decade. There are many already …
which earn interest among researchers for past one decade. There are many already …
Detecting community structure in dynamic social networks using the concept of leadership
SHS Javadi, P Gharani, S Khadivi - Sustainable Interdependent Networks …, 2018 - Springer
Detecting community structure in social networks is a fundamental problem empowering us
to identify groups of actors with similar interests. There have been extensive works focusing …
to identify groups of actors with similar interests. There have been extensive works focusing …
MinerLSD: efficient mining of local patterns on attributed networks
Local pattern mining on attributed networks is an important and interesting research area
combining ideas from network analysis and data mining. In particular, local patterns on …
combining ideas from network analysis and data mining. In particular, local patterns on …
Ensemble-based algorithms to detect disjoint and overlap** communities in networks
Given a set AL of community detection algorithms and a graph G as inputs, we propose two
ensemble methods EnDisCo and MeDOC that (respectively) identify disjoint and …
ensemble methods EnDisCo and MeDOC that (respectively) identify disjoint and …
Enriching networks with edge insertion to improve community detection
ÉTC de Oliveira, FO de França - Social Network Analysis and Mining, 2021 - Springer
Community detection is a broad area of study in network science, in which its correct
detection helps to get information about the groups and the relationships between their …
detection helps to get information about the groups and the relationships between their …
Ensemble detection and analysis of communities in complex networks
Though much work has been done on ensemble clustering in data mining, the application of
ensemble methods to community detection in networks is in its infancy. In this article, we …
ensemble methods to community detection in networks is in its infancy. In this article, we …