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Community Detection

73 papers with code · Graphs

Community Detection is one of the fundamental problems in network analysis, where the goal is to find groups of nodes that are, in some sense, more similar to each other than to the other nodes.

Source: Randomized Spectral Clustering in Large-Scale Stochastic Block Models

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Latest papers with code

Extended Stochastic Block Models

16 Jul 2020danieledurante/ESBM

Stochastic block models (SBM) are widely used in network science due to their interpretable structure that allows inference on groups of nodes having common connectivity patterns.

COMMUNITY DETECTION

2
16 Jul 2020

Interferometric Graph Transform: a Deep Unsupervised Graph Representation

10 Jun 2020edouardoyallon/interferometric-graph-transform

We propose the Interferometric Graph Transform (IGT), which is a new class of deep unsupervised graph convolutional neural network for building graph representations.

ACTION RECOGNITION COMMUNITY DETECTION IMAGE CLASSIFICATION

4
10 Jun 2020

$p$-Norm Flow Diffusion for Local Graph Clustering

20 May 2020kfoynt/LocalGraphClustering

Local graph clustering and the closely related seed set expansion problem are primitives on graphs that are central to a wide range of analytic and learning tasks such as local clustering, community detection, nodes ranking and feature inference.

COMMUNITY DETECTION GRAPH CLUSTERING

60
20 May 2020

Sampling Community Structure

‏‏‎ ‎ 2020 benedekrozemberczki/littleballoffur

We propose a novel method, based on concepts from expander graphs, to sample communities in networks.

COMMUNITY DETECTION RELATIONAL REASONING

378
13 May 2020

Flow-based Algorithms for Improving Clusters: A Unifying Framework, Software, and Performance

20 Apr 2020kfoynt/LocalGraphClustering

Possible reasons for this are: the steep learning curve for these algorithms; the lack of efficient and easy to use software; and the lack of detailed numerical experiments on real-world data that demonstrate their usefulness.

COMMUNITY DETECTION GRAPH CLUSTERING

60
20 Apr 2020

Recommendation system using a deep learning and graph analysis approach

17 Apr 2020mahdikherad/RS_Deep_graph

The advances in machine learning methods, especially deep learning, have led to great achievements in recommender systems, although these systems still suffer from challenges such as cold-start and sparsity problems.

COMMUNITY DETECTION RECOMMENDATION SYSTEMS

1
17 Apr 2020

Inference in the Stochastic Block Model with a Markovian assignment of the communities

9 Apr 2020quentin-duchemin/inference-markovian-SBM

We tackle the community detection problem in the Stochastic Block Model (SBM) when the communities of the nodes of the graph are assigned with a Markovian dynamic.

COMMUNITY DETECTION

2
09 Apr 2020

Gossip and Attend: Context-Sensitive Graph Representation Learning

30 Mar 2020zekarias-tilahun/goat

In this study we show that in-order to extract high-quality context-sensitive node representations it is not needed to rely on supplementary node features, nor to employ computationally heavy and complex models.

COMMUNITY DETECTION GRAPH REPRESENTATION LEARNING LINK PREDICTION NODE CLUSTERING

1
30 Mar 2020

An API Oriented Open-source Python Framework for Unsupervised Learning on Graphs

arXiv 2020 benedekrozemberczki/karateclub

We present Karate Club a Python framework combining more than 30 state-of-the-art graph mining algorithms which can solve unsupervised machine learning tasks.

COMMUNITY DETECTION GRAPH EMBEDDING

877
16 Mar 2020

Analysis of ResearchGate, A Community Detection Approach

12 Mar 2020MohammadHeydari/ResearchGate

To reach a big picture of science production flow, analysis of the collaboration network is crucial.

COMMUNITY DETECTION

0
12 Mar 2020