Quantum social network analysis: Methodology, implementation, challenges, and future directions
Quantum social network analysis (QSNA) is a recent advancement in the interdisciplinary
field of quantum computing and social network analysis. This manuscript comprehensively …
field of quantum computing and social network analysis. This manuscript comprehensively …
TCD2: Tree-based community detection in dynamic social networks
Community detection in social networks is an important field of research in data mining and
has an abundant literature. Time varying social networks require algorithms that can comply …
has an abundant literature. Time varying social networks require algorithms that can comply …
Community detection in social networks using user frequent pattern mining
SA Moosavi, M Jalali, N Misaghian… - … and Information Systems, 2017 - Springer
Recently, social networking sites are offering a rich resource of heterogeneous data. The
analysis of such data can lead to the discovery of unknown information and relations in …
analysis of such data can lead to the discovery of unknown information and relations in …
Multi-objective based unbiased community identification in dynamic social networks
A network is a topological arrangement of its two basic elements, nodes and edges.
Networks in the real world are not static. They tend to evolve with time, causing the set of …
Networks in the real world are not static. They tend to evolve with time, causing the set of …
Investigating community structure in perspective of ego network
Complex relationships within the data are modeled as information network in various
application areas of data mining. Identification of connected groups of nodes associated with …
application areas of data mining. Identification of connected groups of nodes associated with …
LICOD: A Leader-driven algorithm for community detection in complex networks
Z Yakoubi, R Kanawati - Vietnam Journal of Computer Science, 2014 - Springer
Leader-driven community detection algorithms (LdCD hereafter) constitute a new trend in
devising algorithms for community detection in large-scale complex networks. The basic …
devising algorithms for community detection in large-scale complex networks. The basic …
Overlapping community detection algorithm based on coarsening and local overlapping modularity
Z Liu, B Xiang, W Guo, Y Chen, K Guo, J Zheng - IEEE access, 2019 - ieeexplore.ieee.org
Community detection is an important research direction in the field of complex network
analysis. It aims to discover community structures in complex networks. Algorithms based on …
analysis. It aims to discover community structures in complex networks. Algorithms based on …
Node-centric community discovery: From static to dynamic social network analysis
Nowadays, online social networks represent privileged playgrounds that enable researchers
to study, characterize and understand complex human behaviors. Social Network Analysis …
to study, characterize and understand complex human behaviors. Social Network Analysis …
Seed-centric approaches for community detection in complex networks
R Kanawati - Social Computing and Social Media: 6th International …, 2014 - Springer
Seed-centric algorithms constitue an emerging trend in the hot area of community detection
in complex networks. The basic idea underlaying these approaches consists on identifying …
in complex networks. The basic idea underlaying these approaches consists on identifying …
Defining quality metrics for graph clustering evaluation
Abstract Evaluation of clustering has significant importance in various applications of expert
and intelligent systems. Clusters are evaluated in terms of quality and accuracy. Measuring …
and intelligent systems. Clusters are evaluated in terms of quality and accuracy. Measuring …