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Community Detection

21 papers with code · Graphs

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CayleyNets: Graph Convolutional Neural Networks with Complex Rational Spectral Filters

22 May 2017SeongokRyu/Graph-neural-networks

The rise of graph-structured data such as social networks, regulatory networks, citation graphs, and functional brain networks, in combination with resounding success of deep learning in various applications, has brought the interest in generalizing deep learning models to non-Euclidean domains.

COMMUNITY DETECTION IMAGE CLASSIFICATION MATRIX COMPLETION NODE CLASSIFICATION

Deep Autoencoder-like Nonnegative Matrix Factorization for Community Detection

CIKM 2018 benedekrozemberczki/DANMF

Considering the complicated and diversified topology structures of real-world networks, it is highly possible that the mapping between the original network and the community membership space contains rather complex hierarchical information, which cannot be interpreted by classic shallow NMF-based approaches.

LOCAL COMMUNITY DETECTION NETWORK COMMUNITY PARTITION NODE CLASSIFICATION REPRESENTATION LEARNING

Signed Graph Convolutional Network

ICDM 2018 benedekrozemberczki/SGCN

However, since previous GCN models have primarily focused on unsigned networks (or graphs consisting of only positive links), it is unclear how they could be applied to signed networks due to the challenges presented by negative links.

COMMUNITY DETECTION LINK PREDICTION NODE CLASSIFICATION REPRESENTATION LEARNING

Font Size: Community Preserving Network Embedding

AAAI 2017 benedekrozemberczki/M-NMF

While previous network embedding methods primarily preserve the microscopic structure, such as the first- and second-order proximities of nodes, the mesoscopic community structure, which is one of the most prominent feature of networks, is largely ignored.

COMMUNITY DETECTION NETWORK EMBEDDING

MPI-FAUN: An MPI-Based Framework for Alternating-Updating Nonnegative Matrix Factorization

28 Sep 2016ramkikannan/nmflibrary

NMF is a useful tool for many applications in different domains such as topic modeling in text mining, background separation in video analysis, and community detection in social networks.

COMMUNITY DETECTION

SINE: Scalable Incomplete Network Embedding

ICDM 2018 benedekrozemberczki/sine

Attributed network embedding aims to learn low-dimensional vector representations for nodes in a network, where each node contains rich attributes/features describing node content.

COMMUNITY DETECTION LINK PREDICTION NETWORK EMBEDDING NODE CLASSIFICATION

Evaluating Overfit and Underfit in Models of Network Community Structure

28 Feb 2018AGhasemian/CommunityFitNet

These results introduce both a theoretically principled approach to evaluate over and underfitting in models of network community structure and a realistic benchmark by which new methods may be evaluated and compared.

COMMUNITY DETECTION LINK PREDICTION

CommunityGAN: Community Detection with Generative Adversarial Nets

20 Jan 2019SamJia/CommunityGAN

In this paper, we propose CommunityGAN, a novel community detection framework that jointly solves overlapping community detection and graph representation learning.

COMMUNITY DETECTION GRAPH REPRESENTATION LEARNING

Time Series Clustering via Community Detection in Networks

19 Aug 2015lnferreira/time_series_clustering_via_community_detection

In this paper, we propose a technique for time series clustering using community detection in complex networks.

COMMUNITY DETECTION TIME SERIES TIME SERIES ANALYSIS