Mile: A multi-level framework for scalable graph embedding
Recently there has been a surge of interest in designing graph embedding methods. Few, if
any, can scale to a large-sized graph with millions of nodes due to both computational …
any, can scale to a large-sized graph with millions of nodes due to both computational …
Community detection in social networks
Online social networks have become a fundamental part of the global online experience.
They facilitate different modes of communication and social interactions, enabling …
They facilitate different modes of communication and social interactions, enabling …
Community detection in large-scale social networks: state-of-the-art and future directions
Community detection is an important research area in social networks analysis where we
are concerned with discovering the structure of the social network. Detecting communities is …
are concerned with discovering the structure of the social network. Detecting communities is …
A distributed model for sampling large scale social networks
Social networks content analysis has become more challenging over the years due to the
rapidly increasing amount of data. Real social networks are omnipresent in everyday life …
rapidly increasing amount of data. Real social networks are omnipresent in everyday life …
Community detection in social networks by spectral embedding of typed graphs
Although there is considerable disagreement about the details, community detection in
social networks requires finding groups of nodes that are similar to one another, and …
social networks requires finding groups of nodes that are similar to one another, and …
DF Louvain: Fast Incrementally Expanding Approach for Community Detection on Dynamic Graphs
Community detection is the problem of recognizing natural divisions in networks. A relevant
challenge in this problem is to find communities on rapidly evolving graphs. In this report we …
challenge in this problem is to find communities on rapidly evolving graphs. In this report we …
An efficient multilevel scheme for coarsening large scale social networks
The explosive growth of data raised from social networks, hinders researchers from
analysing them in a good way. So, is it possible to rapidly “zoom-out” from this huge network …
analysing them in a good way. So, is it possible to rapidly “zoom-out” from this huge network …
CoVeC: Coarse-grained vertex clustering for efficient community detection in sparse complex networks
This paper tackles the problem of community detection in large-scale graphs. In the literature
devoted to this topic, an iterative algorithm, called Louvain Method (LM), stands out as an …
devoted to this topic, an iterative algorithm, called Louvain Method (LM), stands out as an …
Triangle-induced and degree-wise sampling over large graphs in social networks
Social networks are crucial channels for information dissemination because they facilitate
the effective exchange of ideas and information. The extensive utilization of these networks …
the effective exchange of ideas and information. The extensive utilization of these networks …
Selecting a suitable Parallel Label-propagation based algorithm for Disjoint Community Detection
Community detection is an essential task in network analysis as it helps identify groups and
patterns within a network. High-speed community detection algorithms are necessary to …
patterns within a network. High-speed community detection algorithms are necessary to …