overlapping-community-detection
There are 6 repositories under overlapping-community-detection topic.
- Splitter
benedekrozemberczki / Splitter
A Pytorch implementation of "Splitter: Learning Node Representations that Capture Multiple Social Contexts" (WWW 2019).
Language:Python 211 shchur / overlapping-community-detection
Implementation of "Overlapping Community Detection with Graph Neural Networks"
Language:Jupyter Notebook 151- Language:MATLAB 21
rwth-acis / REST-OCD-Services
This repository contains the OCD service of WebOCD. In the repository, java based codes of overlapping community detection algorithms (OCDA) can be found.
Language:Java 14justin830827 / Overlapping-Community-Detection
This project is to implement the algorithm discussed in Efficient Identification of Overlapping Communities.
Language:Python 12DevilYangS / EMOFM
The source code of EMOFM-DK : An Evolutionary Multiobjective Optimization Based Fuzzy Method for Overlapping Community Detection
Language:MATLAB 11XueyingBai / An-overlapping-community-detection-algorithm-based-on-density-peaks
Source code of our paper: An overlapping community detection algorithm based on density peaks
Language:MATLAB 11- Language:MATLAB 7
- Language:Python 3
stephenyang / dynamic-Edge-Partition-Models
Dynamic Edge Partition Models for Overlapping Community Detection and Temporal Links Prediction
Language:MATLAB 2- Language:Python 1
senguptaneha / DynamicBenchmarkGenerator
Benchmark Generator for Dynamic Overlapping Communities
Language:C++ 1skaraoglu / Community-Detection-on-Graphs-with-Multiple-Layered-Community-Structure
This project focuses on the community structure analysis on graphs with multiple layers of community structures embedded in it. To conduct experiments on multiple layers of community structures in the graph, graphs that are based on the same nodes but wired with different edges are merged. Then the merged graph is analyzed by different techniques - such as community detection algorithms, overlapping community detection algorithms, nested community detection algorithms - to recover information about community structures set in the merged graph.
Language:Jupyter Notebook 1- Language:Python 0
- Language:TypeScript 0
Algorithms for “community” or cohesive subgraph detection are frequently used to analyze network representations of complex systems, and constitute an active area of methodological research. Algorithms for overlapping community detection are of particular interest, because it is often unrealistic to form strict partitions of natural systems, with at least some nodes participating in multiple clusters. However, the literature on overlapping communities does not distinguish different sources of potential overlap. This paper begins by discussing randomness, bridging nodes, and superimposed relational structures as three distinct sources of overlapping communities. It then focuses on the third source (neglected in the literature), by constructing test graphs that merge two distinct relational structures and comparing the communities identified by eight partition and overlapping community algorithms. Results show that most algorithms focus on the same source structure in each graph, ignoring the other, although a few algorithms find combined or nested communities from both structures.
0- Language:Python
