Python functions for identifying communities in multiplex networks
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Updated
Jul 9, 2017 - Python
Python functions for identifying communities in multiplex networks
Community detection in VK
MLPb: Matching via weight-constrained label propagation in bipartite networks
Data analysis on graph dataset built from twitter user data
Multi-source propagation aware network clustering (MSPANC) published in Neurocomputing 2021
A Python Library for Network Community Detection
This project utilizes various metrics to analyze a graph network based on data of ENZYMES_g295
Learning From Networks (LFN) project repository. "Learning From Networks" is a course of the master degree in "Computer Engineering" at the University of Padua, Italy.
Graph partitioning engine for the degree-corrected bipartite Stochastic Block Model, using the Kernighan-Lin algorithm.
This project utilizes the Spark Framework and GraphFrames library to implement the Girvan-Newman algorithm, detecting communities in social networks by analyzing user connections based on common business reviews and optimizing modularity through iterative edge removal.
Bayesian Overlapping Community Detector (DBOCD) in Dynamic Networks
Here I illustrate how GGM selection methods work better in network hub and cluster detection when the false discover rate (FDR) control is ignored.
Визуализация московского арт-сообщества
C++ code for multi-level regularised Markov clustering of a kinetic network (Markov chain community detection)
A framework for REcommending LInks in SOcial Networks
Matlab implementation of online and offline dynamic spectral clustering.
Community Detection research initiative
Iteratively Reweighted Modularity Maximization (IRMM) Algorithm for hypergraph clustering, kumar et al. 2020
Datasets used in my bachelor thesis: "Louvain-initialized Genetic Algorithms for Community Detection in Complex Networks"
An R package for consistent estimation of the number of communities via regularized network embedding.
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