【论文整理】社区/群体检测论文集合

Community Detection Research Papers

Similar collections about graph classification, classification/regression tree, fraud detection, and gradient boosting papers with implementations.

Table of Contents

1. Factorization
2. Deep Learning
3. Label Propagation, Percolation and Random Walks
4. Tensor Decomposition
5. Spectral Methods
6. Temporal Methods
7. Cyclic Patterns
8. Centrality and Cuts
9. Physics Inspired
10. Others

Factorization

• Gromov-Wasserstein Factorization Models for Graph Clustering (AAAI 2020)

  • Hongteng Xu
  • [Paper]
  • [Python Reference]

• Graph Embedding with Self-Clustering (ASONAM 2019)

  • Benedek Rozemberczki, Ryan Davies, Rik Sarkar, and Charles Sutton
  • [Paper]
  • [Python Reference]

• Consistency Meets Inconsistency: A Unified Graph Learning Framework for Multi-view Clustering (ICDM 2019)

  • Youwei Liang, Dong Huang, and Chang-Dong Wang
  • [Paper]
  • [Matlab Reference]

• GMC: Graph-based Multi-view Clustering (TKDE 2019)

  • Hao Wang, Yan Yang, Bing Liu
  • [Paper]
  • [Matlab Reference]

• Knowledge Graph Enhanced Community Detection and Characterization (WSDM 2019)

  • Shreyansh Bhatt, Swati Padhee, Amit Sheth, Keke Chen ,Valerie Shalin, Derek Doran, and Brandon Minnery
  • [Paper]
  • [Java Reference]

• Discrete Optimal Graph Clustering (IEEE Cybernetics 2019)

  • Yudong Han, Lei Zhu, Zhiyong Cheng, Jingjing Li, Xiaobai Liu
  • [Paper]
  • [Matlab Reference]

• Non-Linear Attributed Graph Clustering by Symmetric NMF with PU Learning (Arxiv 2018)

  • Seiji Maekawa, Koh Takeuch, Makoto Onizuka
  • [Paper]
  • [Python Reference]

• Deep Autoencoder-like Nonnegative Matrix Factorization for Community Detection (CIKM 2018)

  • Fanghua Ye, Chuan Chen, and Zibin Zheng
  • [Paper]
  • [Python Reference]
  • [Matlab Reference]

• Adaptive Community Detection Incorporating Topology and Content in Social Networks (Knowledge-Based Systems 2018)

  • Qin Meng, Jin Di, Lei Kai, Bogdan Gabrys, Katarzyna, Musial-Gabrys
  • [Paper]
  • [Matlab Reference]

• Learning Latent Factors for Community Identification and Summarization (IEEE Access 2018)

  • Tiantian He, Lun Hu, Keith C. C. Chan, and Pengwei Hu
  • [Paper]
  • [Executable Reference]

• Bayesian Robust Attributed Graph Clustering: Joint Learning of Partial Anomalies and Group Structure (AAAI 2018)

  • Aleksandar Bojchevski and Stephan Günnemann
  • [Paper]
  • [Python Reference]

• A Poisson Gamma Probabilistic Model for Latent Node-group Memberships in Dynamic Networks (AAAI 2018)

  • Sikun Yang and Heinz Koeppl
  • [Paper]
  • [C Reference]

• Sentiment-driven Community Profiling and Detection on Social Media (ACM HSM 2018)

  • Amin Salehi, Mert Ozer, and Hasan Davulcu
  • [Paper]
  • [Matlab Reference]

• TNE: A Latent Model for Representation Learning on Networks (Arxiv 2018)

  • Abdulkadir Çelikkanat and Fragkiskos D. Malliaros
  • [Paper]
  • [Python Reference]

• Non-Linear Attributed Graph Clustering by Symmetric NMF with PU Learning (Arxiv 2018)

  • Seiji Maekawa, Koh Takeuch, Makoto Onizuka
  • [Paper]
  • [Python Reference]

• A Nonnegative Matrix Factorization Approach for Multiple Local Community Detection (ASONAM 2018)

  • Dany Kamuhanda and Kun He
  • [Paper]
  • [Python Reference]

• Community Preserving Network Embedding (AAAI 17)

  • Xiao Wang, Peng Cui, Jing Wang, Jain Pei, WenWu Zhu, Shiqiang Yang
  • [Paper]
  • [Python Reference]
  • [Matlab Reference]

• Self-weighted Multiview Clustering with Multiple Graphs (IJCAI 17)

  • Feiping Nie, Jing Li, and Xuelong Li
  • [Paper]
  • [Matlab Reference]

• Semi-supervised Clustering in Attributed Heterogeneous Information Networks (WWW 17)

  • Xiang Li, Yao Wu, Martin Ester, Ben Kao, Xin Wang, and Yudian Zheng
  • [Paper]
  • [Python Reference]

• Learning Community Embedding with Community Detection and Node Embedding on Graph (CIKM 2017)

  • Sandro Cavallari, Vincent W. Zheng, Hongyun Cai, Kevin Chen-Chuan Chang, and Erik Cambria
  • [Paper]
  • [Python Reference]

• Cross-Validation Estimate of the Number of Clusters in a Network (Scientific Report 2017)

  • Matsuro Kawamoto and Yoshiyuki Kabashima
  • [Paper]
  • [Julia Reference]

• Comparative Analysis on the Selection of Number of Clusters in Community Detection (ArXiv 2017)

  • Matsuro Kawamoto and Yoshiyuki Kabashima
  • [Paper]
  • [Julia Reference]

• Subspace Based Network Community Detection Using Sparse Linear Coding (TKDE 2016)

  • Arif Mahmood and Michael Small
  • [Paper]
  • [Python Reference]

• Joint Community and Structural Hole Spanner Detection via Harmonic Modularity (KDD 2016)

  • Lifang He, Chun-Ta Lu, Jiaqi Mu, Jianping Cao, Linlin Shen, and Philip S Yu
  • [Paper]
  • [Python Reference]

• Community Detection via Fused Loadings Principal Component Analysis (2016)

  • Richard Samworth, Yang Feng, and Yi Yu
  • [R Reference]

• Feature Extraction via Multi-view Non-negative Matrix Factorization with Local Graph Regularization (IEEE ICIP 2015)

  • Zhenfan Wang, Xiangwei Kong, Hiayan Fu, Ming Li, and Yujia Zhang
  • [Paper]
  • [Matlab Reference]

• A Unified Semi-Supervised Community Detection Framework Using Latent Space Graph Regularization (IEEE TOC 2015)

  • Liang Yang, Xiaochun Cao, Di Jin, Xiao Wang, and Dan Meng
  • [Paper]
  • [Matlab Reference]

• Community Detection via Measure Space Embedding (NIPS 2015)

  • Yulong Pei, Nilanjan Chakraborty, and Katia Sycara
  • [Paper]
  • [Python Reference]

• Nonnegative Matrix Tri-Factorization with Graph Regularization for Community Detection in Social Networks (IJCAI 2015)

  • Mark Kozdoba and Shie Mannor
  • [Paper]
  • [Python Reference]

• Community Detection for Clustered Attributed Graphs via a Variational EM Algorithm (Big Data 2014)

  • Xiangyong Cao, Xiangyu Chang, and Zongben Xu
  • [Paper]
  • [Matlab Reference]

• Improved Graph Clustering (Transactions on Information Network Theory 2014)

  • Yudong Chen, Sujay Sanghavi, Huan Xu
  • [Paper]
  • [Matlab Reference]

• Overlapping Community Detection at Scale: a Nonnegative Matrix Factorization Approach (WSDM 2013)

  • Jaewon Yang and Jure Leskovec
  • [Paper]
  • [C++ Reference]
  • [Java Spark Reference]
  • [Python Reference]
  • [Python Reference]

• On the Statistical Detection of Clusters in Undirected Networks (Computation Statistics and Data Analysis 2013)

  • Marcus B. Perry, Gregory V. Michaelson, M. Allan Ballard
  • [Paper]
  • [C++ Reference]

• Symmetric Nonnegative Matrix Factorization for Graph Clustering (SDM 2012)

  • Da Kuang, Chris Ding, and Haesun Park
  • [Paper]
  • [Matlab Reference]

• A Model-based Approach to Attributed Graph Clustering (SIGMOID 2012)

  • Zhiqiang Xu, Yiping Ke, Yi Wang, Hong Cheng, and James Cheng
  • [Paper]
  • [Matlab Reference]

• Overlapping Community Detection Using Bayesian Non-negative Matrix Factorization (Physical Review E 2011)

  • Ionnis Psorakis, Stephen Roberts, Mark Ebden, and Ben Sheldon
  • [Paper]
  • [Matlab Reference]

Deep Learning

• Deep Multi-Graph Clustering via Attentive Cross-Graph Association (WSDM 2020)

  • Jingchao Ni, Suhang Wang, Yuchen Bian, Xiong Yu and Xiang Zhang
  • [Paper]
  • [Python Reference]

• Overlapping Community Detection with Graph Neural Networks (MLGWorkShop 2019)

  • Oleksandr Shchur and Stephan Gunnemann
  • [Paper]
  • [Python Reference]

• Supervised Community Detection with Line Graph Neural Networks (ICLR 2019)

  • Zhengdao Chen, Xiang Li, and Joan Bruna
  • [Paper]
  • [LUA Reference]
  • [Python Reference]

• CommunityGAN: Community Detection with Generative Adversarial Nets (ArXiv 2019)

  • Yuting Jia, Qinqin Zhang, Weinan Zhang, Xinbing Wang
  • [Paper]
  • [Python Reference]

• An Adaptive Graph Learning Method Based on Dual Data Representations for Clustering (Pattern Recognition 2018)

  • Tianchi Liu, Chamara Kasun, Liyanaarachchi Lekamalage Guang-Bin Huang, and Zhiping Lin
  • [Paper]
  • [Matlab Reference]

• Improving the Efficiency and Effectiveness of Community Detection via Prior-Induced Equivalent Super-Network (Scientific Reports 2017)

  • Liang Yang, Di Jin, Dongxiao He, Huazhu Fu, Xiaochun Cao, and Francoise Fogelman-Soulie
  • [Paper]
  • [Python Reference]

• MGAE: Marginalized Graph Autoencoder for Graph Clustering (CIKM 2017)

  • Chun Wang, Shirui Pan, Guodong Long, Xingquabn Zhu, and Jing Jiang
  • [Paper]
  • [Matlab Reference]

• Graph Clustering with Dynamic Embedding (Arxiv 2017)

  • Carl Yang, Mengxiong Liu, Zongyi Wang, Liyuan Liu, Jiawei Han
  • [Paper]
  • [Python Reference]

• Modularity based Community Detection with Deep Learning (IJCAI 2016)

  • Liang Yang, Xiaochun Cao, Dongxiao He, Chuan Wang, Xiao Wang, and Weixiong Zhan
  • [Paper]
  • [Python Reference]

• Learning Deep Representations for Graph Clustering (AAAI 2014)

  • Fei Tian, Bin Gao, Qing Cui, Enhong Chen, and Tie-Yan Liu
  • [Paper]
  • [Python Reference]
  • [Python Alternative]

Label Propagation, Percolation and Random Walks

• Community Detection in Bipartite Networks by Multi Label Propagation Algorithm (JSAI 2019)

  • Hibiki Taguchi, Tsuyoshi Murata
  • [Paper]
  • [Python Reference]

• Constrained Local Graph Clustering by Colored Random Walk (WWW 2019)

  • Yaowei Yan, Yuchen Bian, Dongsheng Luo, Dongwon Lee and Xiang Zhang
  • [Paper]
  • [Matlab Reference]

• Dynamic Graph-Based Label Propagation for Density Peaks Clustering (Expert Systems 2019)

  • Seyed Amjad Seyedi, Abdulrahman Lotfi, Parham Moradi and Nooruldeen Nasih Qader
  • [Paper]
  • [Matlab Reference]

• Community Detection by Information Flow Simulation (ArXiv 2018)

  • Rajagopal Venkatesaramani and Yevgeniy Vorobeychik
  • [Paper]
  • [Python Reference]

• Multiple Local Community Detection (ACM SIGMETRICS 2017)

  • Alexandre Hollocou, Thomas Bonald, and Marc Lelarge
  • [Paper]
  • [Python Reference]

• Krylov Subspace Approximation for Local Community Detection in Large Networks (ArXiv 2017)

  • Kun He, Pan Shi, David Bindel, and John E. Hopcroft
  • [Paper]
  • [Matlab Reference]

• Many Heads are Better than One: Local Community Detection by the Multi-Walker Chain (ICDM 2017)

  • Yuchen Bian, Jingchao Ni, Wei Cheng, and Zhang Xiang
  • [Paper]
  • [C++ Reference]

• Improving PageRank for Local Community Detection (ArXiv 2016)

  • Alexandre Hollocou, Thomas Bonald, and Marc Lelarge
  • [Paper]
  • [C Reference]
  • [Python Reference]

• Limited Random Walk Algorithm for Big Graph Data Clustering (Journal of Big Data 2016)

  • Honglei Zhang, Jenni Raitoharju, Serkan Kiranyaz, and Moncef Gabbouj
  • [Paper]
  • [C++ Reference]

• Community Detection Based on Structure and Content: A Content Propagation Perspective (ICDM 2015)

  • Liyuan Liu, Linli Xu, Zhen Wang, and Enhong Chen
  • [Paper]
  • [Matlab Reference]

• Modeling Community Detection Using Slow Mixing Random Walks (IEEE Big Data 2015)

  • Ramezan Paravi, Torghabeh Narayana, and Prasad Santhanam
  • [Paper]
  • [Python Reference]

• GossipMap: A Distributed Community Detection Algorithm for Billion-Edge Directed Graphs (SC 2015)

  • Seung-Hee Bae and Bill Howe
  • [Paper]
  • [C++ Reference]

• Scalable Detection of Statistically Significant Communities and Hierarchies, Using Message Passing for Modularity (PNAS 2014)

  • Pan Zhang and Cristopher Moore
  • [Paper]
  • [Python]

• Efficient Monte Carlo and Greedy Heuristic for the Inference of Stochastic Block Models (Phys. Rev. E 2014)

  • Tiago P. Peixoto
  • [Paper]
  • [Python Reference]

• Overlapping Community Detection Using Seed Set Expansion (CIKM 2013)

  • Joyce Jiyoung Whang, David F. Gleich, and Inderjit S. Dhillon
  • [Paper]
  • [Python Reference]

• Influence-Based Network-Oblivious Community Detection (ICDM 2013)

  • Nicola Barbieri, Francesco Bonchi, and Giuseppe Manco
  • [Paper]
  • [Java Reference]

• SLPA: Uncovering Overlapping Communities in Social Networks via A Speaker-listener Interaction Dynamic Process (ICDMW 2011)

  • Jierui Xie, Boleslaw K Szymanski, and Xiaoming Liu
  • [Paper]
  • [Java Reference]
  • [Python Reference]
  • [C++ Reference]

• On the Generation of Stable Communities of Users for Dynamic Mobile Ad Hoc Social Networks (IEEE ICOIN 2011)

  • Guillaume-Jean Herbiet and Pascal Bouvry
  • [Paper]
  • [Java Reference]

• SHARC: Community-Based Partitioning for Mobile Ad Hoc Networks Using Neighborhood Similarity (IEEE WoWMoM 2010)

  • Guillaume-Jean Herbiet and Pascal Bouvry
  • [Paper]
  • [Java Reference]

• Graph Clustering Based on Structural/Attribute Similarities (WSDM 2009)

  • Yang Zhou, Hong Cheng, Jeffrey Xu Yu
  • [Paper]
  • [Python Reference]

• Bridge Bounding: A Local Approach for Efficient Community Discovery in Complex Networks (ArXiv 2009)

  • Symeon Papadopoulos, Andre Skusa, Athena Vakali, Yiannis Kompatsiaris, and Nadine Wagner
  • [Paper]
  • [Java Reference]

• The Map Equation (The European Physical Journal Special Topics 2009)

  • Martin Rossvall, Daniel Axelsson, and Carl T Bergstrom
  • [Paper]
  • [R Reference]
  • [C Reference]
  • [Python Reference]

• Biclique Communities (Physical Review E 2008)

  • Sune Lehmann, Martin Schwartz, and Lars Kai Hansen
  • [Paper]
  • [R Reference]

• Chinese Whispers: an Efficient Graph Clustering Algorithm and its Application to Natural Language Processing Problems (HLT NAACL 2006)

  • Chris Biemann
  • [Paper]
  • [Python Reference]
  • [Python Alternative]

• An Efficient Algorithm for Large-scale Detection of Protein Families (Nucleic Acids Research 2002)

  • Anton Enright, Stijn Van Dongen, and Christos Ouzounis
  • [Paper]
  • [Python Reference]
  • [Python Reference]

Tensor Decomposition

• Coupled Graphs and Tensor Factorization for Recommender Systems and Community Detection (TKDE 2018)

  • Vassilis N. Ioannidis, Ahmed S. Zamzam, Georgios B. Giannakis, Nicholas D. Sidiropoulos
  • [Paper]
  • [Matlab reference]

• Community Detection, Link Prediction, and Layer Interdependence in Multilayer Networks (Physical Review E 2017)

  • Caterina De Bacco, Eleanor A. Power, Daniel B. Larremore, and Cristopher Moore
  • [Paper]
  • [Python Reference]

• Overlapping Community Detection via Constrained PARAFAC: A Divide and Conquer Approach (ICDM 2017)

  • Fatemeh Sheikholeslami and Georgios B. Giannakis
  • [Paper]
  • [Python Reference]

• Fast Detection of Overlapping Communities via Online Tensor Methods on GPUs (ArXiV 2013)

  • Furong Huang and Animashree Anandkumar
  • [Paper]
  • [C++ Reference]

Spectral Methods

• Spectral Clustering in Heterogeneous Information Networks (AAAI 2019)

  • Xiang Li, Ben Kao, Zhaochun Ren, Dawei Yin
  • [Paper]
  • [Matlab Reference]
  • [Python Reference]

• Community Detection Over a Heterogeneous Population of Non-aligned Networks (Arxiv 2019)

  • Guilherme Gomes, Vinayak Rao, Jennifer Neville
  • [Paper]
  • [Python Reference]

• Spectral Rejection for Testing Hypotheses of Structure in Networks (Arxiv 2019)

  • Mark D. Humphries, Javier A. Caballero, Mat Evans, Silvia Maggi, Abhinav Singh
  • [Paper]
  • [Matlab Reference]
  • [Python Reference]

• Spectral Clustering of Signed Graphs via Matrix Power Means (ICML 2019)

  • Pedro Mercado, Francesco Tudisco, Matthias Hein
  • [Paper]
  • [Matlab Reference]

• A Unified Framework for Structured Graph Learning via Spectral Constraints (ArXiv 2019)

  • Sandeep Kumar, Jiaxi Ying, José Vinícius de Miranda Cardoso, and Daniel Palomar
  • [Paper]
  • [R Reference]

• An Ensemble Based on a Bi-objective Evolutionary Spectral Algorithm for Graph Clutering (ArXiv 2018)

  • Camila P.S. Tautenhain, Mariá C.V. Nascimento
  • [Paper]
  • [C++ Reference]

• Hierarchical Community Detection by Recursive Partitioning (ArXiv 2018)

  • Tianxi Li, Lihua Lei, Sharmodeep Bhattacharyya, Purnamrita Sarkar, Peter J. Bickel, Elizaveta Levina
  • [Paper]
  • [R Reference]

• Scalable Spectral Clustering Using Random Binning Features (KDD 2018)

  • Lingfei Wu, Pin-Yu Chen, Ian En-Hsu Yen, Fangli Xu, Yinglong Xia, and Charu Aggarwal
  • [Paper]
  • [Matlab Reference]

• Community Detection and Stochastic Block Models: Recent Developments (JMLR 2018)

  • Emmanuel Abbe
  • [Paper]
  • [Python Reference]

• Understanding Regularized Spectral Clustering via Graph Conductance (NIPS 2018)

  • Yilin Zhang and Karl Rohe
  • [Paper]
  • [Python Reference]

• Locally-Biased Spectral Approximation for Community Detection (Knowledge-Based Systems 2018)

  • Pan Shi, Kun He, David Bindel, and John Hopcroft
  • [Paper]
  • [Matlab Reference]

• Community Detection on Euclidean Random Graphs (Electronic Journal of Statistics 2018)

  • Abishek Sankararaman and Francois Baccelli
  • [Paper]
  • [Python Reference]

• Community Detection by L0-Penalized Graph Laplacian (Electronic Journal of Statistics 2018)

  • Chong Chen, Ruibin Xi, and Nan Lin
  • [Paper]
  • [Matlab Reference]

• Phase Transitions and a Model Order Selection Criterion for Spectral Graph Clustering (IEEE TSP 2018)

  • Pin-Yu Chen and Alfred O. Hero
  • [Paper]
  • [Python Reference]

• An Algorithm J-SC of Detecting Communities in Complex Networks (Physics Letters A 2017)

  • Fang Hu, Mingzhu Wang, Yanran Wang, Zhehao Hong, and Yanhui Zhu
  • [Paper]
  • [Matlab reference]

• Local Lanczos Spectral Approximation for Community Detection (ECML PKDD 2017)

  • Pan Shi, He Kun, David Bindel, and John Hopcroft
  • [Paper]
  • [Python Reference]

• AMOS: An Automated Model Order Selection Algorithm for Spectral Graph Clustering (ICASSP 2017)

  • Pin-Yu Chen, Thibaut Gensollen, and Alfred O. Hero III
  • [Paper]
  • [Python Reference]

• Enhanced Community Detection in Social Networks Using Active Spectral Clustering (SAC 2016)

  • Sarah Habashi, Nagia M. Ghanem, and Mohamed A. Ismail
  • [Paper]
  • [Matlab Reference]

• Clustering Signed Networks with the Geometric Mean of Laplacians (NIPS 2016)

  • Pedro Mercado, Francesco Tudisco, and Matthias Hein
  • [Paper]
  • [Matlab Reference]

• Spectral Clustering with Graph Filtering and Landmark Based Representation (ICASSP 2016)

  • Nicolas Tremblay, Gilles Puy, Pierre Borgnat, Rémi Gribonval, and Pierre Vandergheynst
  • [Paper]
  • [Python Reference]

• Uncovering the Small Community Structure in Large Networks: a Local Spectral Approach (WWW 2015)

  • Li Yixuan, He Kun, David Bindel, and John Hopcroft
  • [Paper]
  • [Python Reference]

• Large-Scale Multi-View Spectral Clustering via Bipartite Graph (AAAI 2015)

  • Yeqing Li, Feiping Nie, Heng Huang, and Junzhou Huang
  • [Paper]
  • [Matlab Reference]

• Constructing Robust Affinity Graphs for Spectral Clustering (CVPR 2014)

  • Xiatian Zhu1, Chen Change Loy, Shaogang Gong
  • [Paper]
  • [Matlab Reference]

• Accurate Community Detection in the Stochastic Block Model via Spectral Algorithms (Arxiv 2014)

  • Se-Young Yun, Alexandre Proutiere
  • [Paper]
  • [R Reference]

• Self-Taught Spectral Clustering via Constraint Augmentation (SDM 2014)

  • Xiang Wang, Jun Wang, Buyue Qian, Fei Wang and Ian Davidson
  • [Paper]
  • [Matlab Reference]

• Multi-Objective Multi-View Spectral Clustering via Pareto Optimization (SDM 2013)

  • Xiang Wang, Buyue Qian, Jieping Ye, and Ian Davidson
  • [Paper]
  • [Matlab Reference]

• Co-Clustering for Directed Graphs: the Stochastic Co-Blockmodel and Spectral Algorithm Di-Sim (ArXiv 2012)

  • Karl Rohe, Tai Qin, and Bin Yu
  • [Paper]
  • [R Reference]

• Asymptotic Analysis of the Stochastic Block Model for Modular Networks and its Algorithmic Applications (Physical Review 2011)

  • Aurelien Decelle, Florent Krzakala, Cristopher Moore, and Lenka Zdeborova
  • [Paper]
  • [C++ Reference]

• Phase Transition in the Detection of Modules in Sparse Networks (Physical Review Letters 2011)

  • Aurelien Decelle, Florent Krzakala, Cristopher Moore, and Lenka Zdeborova
  • [Paper]
  • [C++ Reference]

• Active Spectral Clustering (ICDM 2010)

  • Xiang Wang and Ian Davidson
  • [Paper]
  • [Matlab Reference]

• Flexible Constrained Spectral Clustering (KDD 2010)

  • Xiang Wang and Ian Davidson
  • [Paper]
  • [Matlab Reference]

• Spectral Clustering Based on the Graph p-Laplacian (ICML 2009)

  • Thomas Buhler and Matthias Hein
  • [Paper]
  • [Matlab Reference]

Temporal Methods

• DynComm R Package - Dynamic Community Detection for Evolving Networks (Arxiv 2019)

  • Rui Portocarrero Sarmento, Luís Lemos, Mário Cordeiro, Giulio Rossetti, and Douglas Cardoso
  • [Paper]
  • [R Reference]

• Block-Structure Based Time-Series Models For Graph Sequences (Arxiv 2018)

  • Mehrnaz Amjadi and Theja Tulabandhula
  • [Paper]
  • [Python Reference]

• DyPerm: Maximizing Permanence for Dynamic Community Detection (PKDD 2018)

  • Prerna Agarwal, Richa Verma, Ayush Agarwal, Tanmoy Chakraborty
  • [Paper]
  • [Python Reference]

• Temporally Evolving Community Detection and Prediction in Content-Centric Networks (ECML 2018)

  • Ana Paula Appel, Renato L. F. Cunha, Charu C. Aggarwal, and Marcela Megumi Terakado
  • [Paper]
  • [Python Reference]

• A Streaming Algorithm for Graph Clustering (Arxiv 2017)

  • Alexandre Hollocou, Julien Maudet, Thomas Bonald and Marc Lelarge
  • [Paper]
  • [C++ Reference]

• DynaMo: Dynamic Community Detection by Incrementally Maximizing Modularity (Arxiv 2017)

  • Di Zhuang, J. Morris Chang, Mingchen Li
  • [Paper]
  • [Java Reference]

• Model-Based Clustering of Time-Evolving Networks through Temporal Exponential-Family Random Graph Models (Arxiv 2017)

  • Kevin H. Lee, Lingzhou Xue, and David R. Hunter
  • [Paper]
  • [R Reference]

• Dynamic Community Detection Based on Network Structural Perturbation and Topological Similarity (Journal of Statistical Mechanics 2017)

  • Peizhuo Wang, Lin Gao and Xiaoke Ma
  • [Paper]
  • [Matlab Reference]

• RDYN⁠: Graph Benchmark Handling Community Dynamics (Arxiv 2017)

  • Giulio Rossetti
  • [Paper]
  • [Python Reference]

• Sequential Detection of Temporal Communities by Estrangement Confinement (Scientific Reports 2012)

  • Vikas Kawadia and Sameet Sreenivasan
  • [Paper]
  • [Python Reference]

• GraphScope: Parameter-Free Mining of Large Time-Evolving Graphs (KDD 2007)

  • Jimeng Sun, Christos Faloutsos, Spiros Papadimitriou, and Philip S. Yu
  • [Paper]
  • [Java Reference]

Cyclic Patterns

• DAOC: Stable Clustering of Large Networks (Phys. Rev E 2019)

  • Artem Lutov, Mourad Khayati, Philippe Cudré-Mauroux
  • [Paper]
  • [C++ Reference]

• Fast Consensus Clustering in Complex Networks (Phys. Rev E 2019)

  • Aditya Tandon, Aiiad Albeshri, Vijey Thayananthan, Wadee Alhalabi, Santo Fortunato
  • [Paper]
  • [Python Reference]

• EdMot: An Edge Enhancement Approach for Motif-aware Community Detection (KDD 2019)

  • Pei-Zhen Li, Ling Huang, Chang-Dong Wang, and Jian-Huang Lai
  • [Paper]
  • [Python Reference]
  • [Matlab Reference]

• From Louvain to Leiden: Guaranteeing Well-connected Communities (Scientific Reports 2019)

  • Vincent Traag, Ludo Waltman, Nees Jan van Eck
  • [Paper]
  • [C++ Reference]
  • [Julia Reference]

• Anti-community Detection in Complex Networks (SSDBM 2018)

  • Sebastian Lackner, Andreas Spitz, Matthias Weidemüller and Michael Gertz
  • [Paper]
  • [C Reference]

• Adaptive Modularity Maximization via Edge Weighting Scheme (Information Sciences 2018)

  • Xiaoyan Lu, Konstantin Kuzmin, Mingming Chen, and Boleslaw K Szymanski
  • [Paper]
  • [Python Reference]

• Semi-Supervised Community Detection Using Structure and Size (ICDM 2018)

  • Arjun Bakshi, Srinivasan Parthasarathy, and Kannan Srinivasan
  • [Paper]
  • [Python Reference]

• Graph Sketching-based Space-efficient Data Clustering (SDM 2018)

  • Anne Morvan, Krzysztof Choromanski, Cédric Gouy-Pailler, Jamal Atif
  • [Paper]
  • [Python Reference]

• Hierarchical Graph Clustering using Node Pair Sampling (Arxiv 2018)

  • Thomas Bonald, Bertrand Charpentier, Alexis Galland and Alexandre Hollocou
  • [Paper]
  • [Python Reference]

• Priority Based Clustering in Weighted Graph Streams (JISE 2018)

  • Mohsen Saadatpour, Sayyed Kamyar Izadi, Mohammad Nasirifar, and Hamed Kavoosi
  • [Paper]
  • [Java Reference]

• Graph Learning for Multiview Clustering (IEEE Transactions on Cybernetics 2017)

  • Anne Morvan, Krzysztof Choromanski, Cédric Gouy-Pailler, and Jamal Atif
  • [Paper]
  • [Matlab Reference]

• DCEIL: Distributed Community Detection with the CEIL Score (IEEE HPCC 2017)

  • Akash Jain, Rupesh Nasre, Balaraman Ravindran
  • [Paper]
  • [Java Reference]

• A Community Detection Algorithm Using Network Topologies and Rule-Based Hierarchical Arc-Merging Strategies (PLOS One 2017)

  • Yu-Hsiang Fu, Chung-Yuan Huang, and Chuen-Tsai Sun
  • [Paper]
  • [Python Reference]

• Local Higher-Order Graph Clustering (KDD 2017)

  • Hao Yin, Austin Benson, Jure Leskovec, and David Gleich
  • [Paper]
  • [Python Reference]
  • [C++ SNAP Reference]

• ComSim: A Bipartite Community Detection Algorithm Using Cycle and Node’s Similarity (Complex Networks 2017)

  • Raphael Tack, Fabien Tarissan, and Jean-Loup Guillaume
  • [Paper]
  • [C++ Reference]

• Evolutionary Graph Clustering for Protein Complex Identification (IEEE Transactions on Computational Biology and Bioinformatics 2016)

  • Tiantian He and Keith C.C. Chan
  • [Paper]
  • [Java Reference]

• pSCAN: Fast and Exact Structural Graph Clustering (ICDE 2016)

  • T Lijun Chang, Wei Li, Xuemin Lin, Lu Qin, and Wenjie Zhang
  • [Paper]
  • [C++ Reference]
  • [Scala]

• Node-Centric Detection of OverlappingCommunities in Social Networks (IWSCN 2016)

  • Yehonatan Cohen, Danny Hendler, Amir Rubin
  • [Paper]
  • [Java Reference]

• Graph Clustering with Density-Cut (Arxiv 2016)

  • Junming Shao, Qinli Yang, Jinhu Liu, Stefan Kramer
  • [Paper]
  • [Go Reference]

• Community Detection in Directed Acyclic Graphs (European Physical Journal B 2015)

  • Leo Speidel, Taro Takaguchi, Naoki Masuda
  • [Paper]
  • [Python Reference]

• Intra-Graph Clustering Using Collaborative Similarity Measure (DPCD 2015)

  • Waqas Nawaz, Kifayat-Ullah Khan, Young-Koo Lee, and Sungyoung Lee
  • [Paper]
  • [Java Reference]

• K-Clique Community Detection in Social NetworksBased on Formal Concept Analysis (IEEE Systems 2015)

  • Fei Hao, Geyong Min, Zheng Pei, Doo-Soon Park, Laurence T. Yang
  • [Paper]
  • [Python Reference]

• High Quality, Scalable and Parallel Community Detection for Large Real Graphs (WWW 2014)

  • Arnau Prat-Perez David Dominguez-Sal and Josep-Lluis Larriba-Pey
  • [Paper]
  • [C++ Reference]

• GMAC: A Seed-Insensitive Approach to Local Community Detection (DaWak 2013)

  • Lianhang Ma, Hao Huang, Qinming He, Kevin Chiew, Jianan Wu, and Yanzhe Che
  • [Paper]
  • [Python Reference]

• On the Maximum Quasi-Clique Problem (Discrete Applied Mathematics 2013)

  • Jeffrey Pattillo, Alexander Veremyev, Sergiy Butenko, and Vladimir Boginski
  • [Paper]
  • [Python Reference]

• Community Detection in Networks with Node Attributes (ICDM 2013)

  • Jaewon Yang, Julian McAuley, and Jure Leskovec
  • [Paper]
  • [C++ Reference]

• Detecting the Structure of Social Networks Using (α,β)-Communities (IWAMW 2011)

  • Jing He, John Hopcroft, Liang Hongyu, Supasorn Suwajanakorn, and Liaoruo Wang
  • [Paper]
  • [Python Reference]

• Multi-Netclust: An Efficient Tool for Finding Connected Clusters in Multi-Parametric Networks (IWAMW 2011)

  • Arnold Kuzniar, Somdutta Dhir, Harm Nijveen, Sándor Pongor, Jack A.M. Leunissen
  • [Paper]
  • [C Reference]

• Detecting Communities in Networks by Merging Cliques (IEEE ICICISYS 2009)

  • Bowen Yan and Steve Gregory
  • [Paper]
  • [Java Reference]

• Fast Unfolding of Communities in Large Networks (Journal of Statistical Mechanics 2008)

  • Vincent D Blondel, Jean-Loup Guillaume, Renaud Lambiotte, Renaud Lefebvre
  • [Paper]
  • [Python]
  • [Python]
  • [C++ Parallel]
  • [C++]
  • [Javascript]
  • [Javascript]
  • [Java]
  • [Matlab]
  • [Matlab]
  • [Scala]
  • [Rust]

• Modularity and Community Detection in Bipartite Networks (Phys. Rev. E 2007)

  • Michael J. Barber
  • [Paper]
  • [Python Reference]

Centrality and Cuts

• Hypergraph Clustering with Categorical Edge Labels (Arxiv 2019)

  • Ilya Amburg, Nate Veldt, Austin R. Benson
  • [Paper]
  • [Julia Reference]

• Learning Resolution Parameters for Graph Clustering (WWW 2019)

  • Nate Veldt, David F. Gleich, Anthony Wirth
  • [Paper]
  • [Julia Reference]

• Parallelizing Pruning-based Graph Structural Clustering (ICPP 2018)

  • Yulin Che, Shixuan Sun, and Qiong Luo
  • [Paper]
  • [C++ Reference]

• Real-Time Community Detection in Large Social Networks on a Laptop (PLOS 2018)

  • Benjamin Paul Chamberlain, Josh Levy-Kramer, Clive Humby, and Marc Peter Deisenroth
  • [Paper]
  • [Python Reference]

• A Polynomial Algorithm for Balanced Clustering via Graph Partitioning (EJOR 2018)

  • Luis-Evaristo Caraballo, José-Miguel Díaz-Báñez, Nadine Kroher
  • [Paper]
  • [Python Reference]

• A Community Detection Algorithm Using Network Topologies and Rule-based Hierarchical Arc-merging Strategies (PLOS 2018)

  • Yu-Hsiang Fu, Chung-Yuan Huang, and Chuen-Tsai Sun
  • [Paper]
  • [Python Reference]

• Hidden Community Detection in Social Networks (Information Sciences 2018)

  • Kun He, Yingru Li, Sucheta Soundarajan, John E. Hopcroft
  • [Paper]
  • [Python Reference]

• Ego-splitting Framework: from Non-Overlapping to Overlapping Clusters (KDD 2017)

  • Alessandro Epasto, Silvio Lattanzi, and Renato Paes Leme
  • [Paper]
  • [Python Reference]

• Query-oriented Graph Clustering (PAKDD 2017)

  • Li-Yen Kuo, Chung-Kuang Chou, and Ming-Syan Chen
  • [Paper]
  • [Python Reference]

• Fast Heuristic Algorithm for Multi-scale Hierarchical Community Detection (ASONAM 2017)

  • Eduar Castrillo, Elizabeth León, and Jonatan Gómez
  • [Paper]
  • [C++ Reference]

• Community Detection in Signed Networks: the Role of Negative Ties in Different Scales (Scientific Reports 2015)

  • Pouya Esmailian and Mahdi Jalili
  • [Paper]
  • [Java Reference]

• Detecting Community Structures in Social Networks by Graph Sparsification (CODS 2016)

  • Partha Basuchowdhuri, Satyaki Sikdar, Sonu Shreshtha, and Subhasis Majumder
  • [Paper]
  • [Python Reference]

• Community Detection in Complex Networks Using Density-Based Clustering Algorithm and Manifold Learning (Physica A 2016)

  • Tao Youa, Hui-Min Chenga, Yi-Zi Ninga, Ben-Chang Shiab, and Zhong-Yuan Zhang
  • [Paper]
  • [Matlab Reference]

• Smart Partitioning of Geo-Distributed Resources to Improve Cloud Network Performance (CloudNet 2015)

  • Hooman Peiro Sajjad, Fatemeh Rahimian, and Vladimir Vlassov
  • [Paper]
  • [Java Reference]

• Generalized Modularity for Community Detection (ECML 2015)

  • Mohadeseh Ganji, Abbas Seifi, Hosein Alizadeh, James Bailey, and Peter J. Stuckey
  • [Paper]
  • [Python Reference]

• General Optimization Technique for High-quality Community Detection in Complex Networks (Physical Review E 2014)

  • Stanislav Sobolevsky, Riccardo Campari, Alexander Belyi, and Carlo Ratti
  • [Paper]
  • [Python Reference]

• Online Community Detection for Large Complex Networks (IJCAI 2013)

  • Wangsheng Zhang, Gang Pan, Zhaohui Wu and Shijian Li
  • [Paper]
  • [C++ Reference]

• Agglomerative Clustering via Maximum Incremental Path Integral (Pattern Recognition 2013)

  • Wei Zhang, Deli Zhao, and Xiaogang Wang
  • [Paper]
  • [Matlab Reference]

• Graph Degree Linkage: Agglomerative Clustering on a Directed Graph (ECCV 2012)

  • Wei Zhang, Xiaogang Wang, Deli Zhao and Xiaoou Tang
  • [Paper]
  • [Matlab Reference]
  • [Python Reference]

• Weighted Graph Cuts without Eigenvectors a Multilevel Approach (IEEE TPAMI 2007)

  • Inderjit S Dhillon, Brian Kulis, and Yuqiang Guan
  • [Paper]
  • [C Reference]

Physics Inspired

• Community Detection Using Preference Networks (Physica A 2018)

  • Mursel Tasgin and Halu Bingol
  • [Paper]
  • [Java Reference]

• Thermodynamics of the Minimum Description Length on Community Detection (ArXiv 2018)

  • Juan Ignacio Perotti, Claudio Juan Tessone, Aaron Clauset and Guido Caldarelli
  • [Paper]
  • [Python Reference]

• Fluid Communities: A Community Detection Algorithm (Complenet 2017)

  • Ferran Parés, Dario Garcia-Gasulla, Armand Vilalta, Jonatan Moreno, Eduard Ayguadé, Jesús Labarta, Ulises Cortés and Toyotaro Suzumura
  • [Paper]
  • [Python Reference]

• A Local Perspective on Community Structure in Multilayer Networks (Network Science 2017)

  • Lucas GS Jeub, Michael Mahoney, Peter J Mucha and Mason A Porter
  • [Paper]
  • [Python Reference]

• Defining Least Community as a Homogeneous Group in Complex Networks (Physica A 2015)

  • Renaud Lambiotte, J-C Delvenne, and Mauricio Barahona
  • [Paper]
  • [Python Reference]

• Community Detection Based on Distance Dynamics (KDD 2015)

  • Shao Junming, Han Zhichao, Yang Qinli, and Zhou Tao
  • [Paper]
  • [Python Reference]

• Think Locally, Act Locally: Detection of Small, Medium-Sized, and Large Communities in Large Networks (Physica Review E 2015)

  • Lucas G. S. Jeub, Prakash Balachandran, Mason A. Porter, Peter J. Mucha, and Michael W. Mahoney
  • [Paper]
  • [Python Reference]

• Detecting Community Structure Using Label Propagation with Weighted Coherent Neighborhood Propinquity (Physica A 2013)

  • Hao Lou, Shenghong Li, and Yuxin Zhao
  • [Paper]
  • [Java Reference]

• Parallel Community Detection on Large Networks with Propinquity Dynamics (KDD 2009)

  • Yuzhou Zhang, Jianyong Wang, Yi Wang, and Lizhu Zhou
  • [Paper]
  • [Java Reference]

• Laplacian Dynamics and Multiscale Modular Structure in Networks (IEEE TNSE 2008)

  • Renaud Lambiotte, J-C Delvenne, and Mauricio Barahona
  • [Paper]
  • [R Reference]

• Statistical Mechanics of Community Detection (Phyics Review E 2006)

  • Jorh Reichardt and Stefan Bornholdt
  • [Paper]
  • [Ruby Reference]

Others

• Ensemble Clustering for Graphs: Comparisons and Applications (Applied Network Science 2019)

  • Valérie Poulin and François Théberge
  • [Paper]
  • [Python Reference]

• CutESC: Cutting Edge Spatial Clustering Technique based on Proximity Graphs (Knowledge-Based Systems 2019)

  • Alper Aksac, Tansel Özyer, Reda Alhajja
  • [Paper]
  • [Python Reference]

• A Study of Graph-based System for Multi-view Clustering (Knowledge-Based Systems 2019)

  • Hao Wang, Yan Yang, BingLiu, Hamido Fujita
  • [Paper]
  • [Python Reference]

• Learning Resolution Parameters for Graph Clustering (WWW 2019)

  • Nate Veldt, David Gleich, Anthony Wirth
  • [Paper]
  • [Julia Reference]

• Multiview Consensus Graph Clustering (IEEE TIP 2019)

  • Kun Zhan and Feiping Nie and Jing Wang and Yi Yang
  • [Paper]
  • [Matlab Reference]

• CutESC: Cutting Edge Spatial Clustering Technique based on Proximity Graphs (Knowledge-Based Systems 2019)

  • Alper Aksac, Tansel Özyer, Reda Alhajja
  • [Paper]
  • [Python Reference]

• Clubmark - Bench bencmarking Framework for the Clustering Algorithms Evaluation (ICDM 2018)

  • Artem Lutov, Mourad Khayati, Philippe Cudre-Mauroux
  • [Paper]
  • [Python Reference]

• The Difference Between Optimal and Germane Communities (Social Network Analysis and Mining 2018)

  • Jerry Scripps, Christian TrefftzZachary Kurmas
  • [Paper]
  • [Java Reference]

• Discovering Fuzzy Structural Patterns for Graph Analytics (IEEE TFS 2018)

  • Tiantian He and Keith C. C. Chan
  • [Paper]
  • [Executable Reference]

• Wiring Together Large Single-Cell RNA-Seq Sample Collections (biorxiv 2018)

  • Nikolas Barkas, Viktor Petukhov, Daria Nikolaeva, Yaroslav Lozinsky, Samuel Demharter, Konstantin Khodosevich, Peter V. Kharchenko
  • [Paper]
  • [C++]

• Watset: Automatic Induction of Synsets for a Graph of Synonyms (ACL 2017)

  • Dmitry Ustalov, Alexander Panchenko, and Chris Biemann
  • [Paper]
  • [Python Reference]
  • [Java Reference]

• An Overlapping Community Detection Algorithm Based on Density Peaks (NeuroComputing 2017)

  • Xueying Bai, Peilin Yang, and Xiaohu Shi
  • [Paper]
  • [Matlab Reference]

• Fast Heuristic Algorithm for Multi-scale Hierarchical Community Detection (ASONAM 2017)

  • Eduar Castrillo, Elizabeth León, and Jonatan Gómez
  • [Paper]
  • [C++ Reference]

• Time Series Clustering via Community Detection in Networks (Information Sciences 2016)

  • Leonardo N. Ferreira and Liang Zhao
  • [Paper]
  • [R Reference]

• Community Detection in Multi-Partite Multi-Relational Networks Based on Information Compression (New Generation Computing 2016)

  • Xin Liu, Weichu Liu, Tsuyoshi Murata, and Ken Wakita
  • [Paper]
  • [Scala Reference]

• Integration of Graph Clustering with Ant Colony Optimization for Feature Selection (Knowledge-Based Systems 2015)

  • Parham Moradi, Mehrdad Rostami
  • [Paper]
  • [Matlab Reference]

• Greedy Discrete Particle Swarm Optimization for Large-Scale Social Network Clustering (Information Sciences 2015)

  • Qing Cai, Maoguo Gong, Lijia Ma, Shasha Ruan, Fuyan Yuan, Licheng Jiao
  • [Paper]
  • [C++ Reference]

• Community Detection via Maximization of Modularity and Its Variants (IEEE TCSS 2014)

  • Mingming Chen, Konstantin Kuzmin, and Boleslaw K. Szymanski
  • [Paper]
  • [Python Reference]

• A Smart Local Moving Algorithm for Large-Scale Modularity-Based Community Detection (The European Physical Journal B 2013)

  • Ludo Waltman and Nees Jan Van Eck
  • [Paper]
  • [R Reference]
  • [Python Reference]

• Bayesian Hierarchical Community Discovery (NIPS 2013)

  • Charles Blundell and Yee Whye Teh
  • [Paper]
  • [Python Reference]
  • [C++ Reference]

• Efficient Discovery of Overlapping Communities in Massive Networks (PNAS 2013)

  • Prem K. Gopalan and David M. Blei
  • [Paper]
  • [C++ Reference]

• Complex Network Clustering by Multiobjective Discrete Particle Swarm Optimization Based on Decomposition (IEEE Trans. Evolutionary Computation 2013)

  • Maoguo Gong, Qing Cai, Xiaowei Chen, and Lijia Ma
  • [Paper]
  • [C++ Reference]

• An Efficient and Principled Method for Detecting Communities in Networks (Physical Review E 2011)

  • Brian Ball, Brian Karrer, M. E. J. Newman
  • [Paper]
  • [C++ Reference]
  • [Python Reference]

• A Game-Theoretic Approach to Hypergraph Clustering (NIPS 2009)

  • Samuel R. Bulò and Marcello Pelillo
  • [Paper]
  • [Matlab Reference]