Community Discovery in Dynamic Networks
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[1] Morten Mørup,et al. Modeling Temporal Evolution and Multiscale Structure in Networks , 2013, ICML.
[2] Sanjukta Bhowmick,et al. Fast Community Detection for Dynamic Complex Networks , 2011, CompleNet.
[3] Andrea Lancichinetti,et al. Benchmarks for testing community detection algorithms on directed and weighted graphs with overlapping communities. , 2009, Physical review. E, Statistical, nonlinear, and soft matter physics.
[4] Jimeng Sun,et al. ContexTour: Contextual Contour Visual Analysis on Dynamic Multi- Relational Clustering , 2010 .
[5] Yizhou Sun,et al. Integrating community matching and outlier detection for mining evolutionary community outliers , 2012, KDD.
[6] Bart Selman,et al. Tracking evolving communities in large linked networks , 2004, Proceedings of the National Academy of Sciences of the United States of America.
[7] Dorothea Wagner,et al. Dynamic graph clustering combining modularity and smoothness , 2013, JEAL.
[8] Renaud Lambiotte,et al. Predicting links in ego-networks using temporal information , 2015, EPJ Data Science.
[9] S. Fortunato,et al. Resolution limit in community detection , 2006, Proceedings of the National Academy of Sciences.
[10] Hideaki Takeda,et al. Using multiple-criteria methods to evaluate community partitions , 2015, ArXiv.
[11] Dino Pedreschi,et al. Interaction prediction in dynamic networks exploiting community discovery , 2015, 2015 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining (ASONAM).
[12] Jure Leskovec,et al. Structure and Overlaps of Ground-Truth Communities in Networks , 2014, TIST.
[13] Weidong Xiao,et al. Analyzing Community Core Evolution in Mobile Social Networks , 2013, 2013 International Conference on Social Computing.
[14] Bin Wu,et al. CommTracker: A Core-Based Algorithm of Tracking Community Evolution , 2008, ADMA.
[15] Boleslaw K. Szymanski,et al. LabelRank: A stabilized label propagation algorithm for community detection in networks , 2013, 2013 IEEE 2nd Network Science Workshop (NSW).
[16] Pablo Jensen,et al. Temporal evolution of communities based on scientometrics data , 2015 .
[17] Vincent Miele,et al. Statistical clustering of temporal networks through a dynamic stochastic block model , 2015, 1506.07464.
[18] Myra Spiliopoulou,et al. Mining and Visualizing the Evolution of Subgroups in Social Networks , 2006, 2006 IEEE/WIC/ACM International Conference on Web Intelligence (WI 2006 Main Conference Proceedings)(WI'06).
[19] Nam P. Nguyen,et al. Overlapping communities in dynamic networks: their detection and mobile applications , 2011, MobiCom.
[20] Huan Liu,et al. Community evolution in dynamic multi-mode networks , 2008, KDD.
[21] Ruixuan Li,et al. Incremental K-clique clustering in dynamic social networks , 2012, Artificial Intelligence Review.
[22] Chonghui Guo,et al. Evolutionary community structure discovery in dynamic weighted networks , 2014 .
[23] Philip S. Yu,et al. GraphScope: parameter-free mining of large time-evolving graphs , 2007, KDD '07.
[24] Jalel Akaichi,et al. Tracking dynamic community evolution in social networks , 2014, 2014 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining (ASONAM 2014).
[25] C. Lee Giles,et al. Efficient identification of Web communities , 2000, KDD '00.
[26] Sameet Sreenivasan,et al. Sequential detection of temporal communities in evolving networks by estrangement confinement , 2013 .
[27] Rémy Cazabet,et al. Simulate to Detect: A Multi-agent System for Community Detection , 2011, 2011 IEEE/WIC/ACM International Conferences on Web Intelligence and Intelligent Agent Technology.
[28] Junming Shao,et al. Community Detection via Local Dynamic Interaction , 2014, ArXiv.
[29] Duncan J. Watts,et al. Collective dynamics of ‘small-world’ networks , 1998, Nature.
[30] Harry Crane,et al. The cut-and-paste process , 2014, 1409.0976.
[31] Tanya Y. Berger-Wolf,et al. A framework for community identification in dynamic social networks , 2007, KDD '07.
[32] Claudio Castellano,et al. Defining and identifying communities in networks. , 2003, Proceedings of the National Academy of Sciences of the United States of America.
[33] Cheng Wu,et al. A Real-Time Detecting Algorithm for Tracking Community Structure of Dynamic Networks , 2014, ArXiv.
[34] Albert,et al. Emergence of scaling in random networks , 1999, Science.
[35] C. Matias,et al. A semiparametric extension of the stochastic block model for longitudinal networks , 2015, Biometrika.
[36] Hamidreza Alvari,et al. Community detection in dynamic social networks: A game-theoretic approach , 2014, 2014 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining (ASONAM 2014).
[37] David A. Bader,et al. A dynamic algorithm for local community detection in graphs , 2015, 2015 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining (ASONAM).
[38] Hideaki Takeda,et al. Using dynamic community detection to identify trends in user-generated content , 2012, Social Network Analysis and Mining.
[39] Leon Danon,et al. The effect of size heterogeneity on community identification in complex networks , 2006, physics/0601144.
[40] Nam P. Nguyen,et al. Adaptive algorithms for detecting community structure in dynamic social networks , 2011, 2011 Proceedings IEEE INFOCOM.
[41] Yun Chi,et al. Analyzing communities and their evolutions in dynamic social networks , 2009, TKDD.
[42] Céline Robardet,et al. Communities detection and analysis of their dynamics in collaborative networks , 2007, 2007 2nd International Conference on Digital Information Management.
[43] Dorothea Wagner,et al. Significance-Driven Graph Clustering , 2007, AAIM.
[44] Andrew E. Johnson,et al. Visualizing the Evolution of Community Structures in Dynamic Social Networks , 2011, Comput. Graph. Forum.
[45] Tanja Falkowski,et al. Mining the Dynamics of Music Preferences from a Social Networking Site , 2009, 2009 International Conference on Advances in Social Network Analysis and Mining.
[46] Myra Spiliopoulou,et al. Studying Community Dynamics with an Incremental Graph Mining Algorithm , 2008, AMCIS.
[47] Mark E. J. Newman,et al. The Structure and Function of Complex Networks , 2003, SIAM Rev..
[48] T. Vicsek,et al. Uncovering the overlapping community structure of complex networks in nature and society , 2005, Nature.
[49] Derek Greene,et al. Normalized Mutual Information to evaluate overlapping community finding algorithms , 2011, ArXiv.
[50] C. Matias,et al. Estimation and clustering in a semiparametric Poisson process stochastic block model for longitudinal networks , 2015 .
[51] Jean-Loup Guillaume,et al. Multi-Step Community Detection and Hierarchical Time Segmentation in Evolving Networks , 2011, KDD 2011.
[52] U. Alon. Network motifs: theory and experimental approaches , 2007, Nature Reviews Genetics.
[53] Ulrik Brandes,et al. Experiments on Graph Clustering Algorithms , 2003, ESA.
[54] Francesco Folino,et al. Multiobjective evolutionary community detection for dynamic networks , 2010, GECCO '10.
[55] Philip S. Yu,et al. ECODE: Event-Based Community Detection from Social Networks , 2011, DASFAA.
[56] Osmar R. Zaïane,et al. MODEC - Modeling and Detecting Evolutions of Communities , 2011, ICWSM.
[57] Jimeng Sun,et al. ContexTour: Contextual Contour Analysis on Dynamic Multi-relational Clustering , 2010, SDM.
[58] Matthieu Latapy,et al. Stream graphs and link streams for the modeling of interactions over time , 2017, Social Network Analysis and Mining.
[59] Jure Leskovec,et al. Defining and evaluating network communities based on ground-truth , 2012, Knowledge and Information Systems.
[60] Mason A. Porter,et al. Community Structure in the United Nations General Assembly , 2010, ArXiv.
[61] James P. Ferry,et al. Community detection and tracking on networks from a data fusion perspective , 2012, ArXiv.
[62] Paul Newbold,et al. ARIMA model building and the time series analysis approach to forecasting , 1983 .
[63] Mason A. Porter,et al. Robust Detection of Dynamic Community Structure in Networks , 2012, Chaos.
[64] Yifan Hu,et al. Embedding, clustering and coloring for dynamic maps , 2012, 2012 IEEE Pacific Visualization Symposium.
[65] Francesco Folino,et al. An Evolutionary Multiobjective Approach for Community Discovery in Dynamic Networks , 2014, IEEE Transactions on Knowledge and Data Engineering.
[66] Miklós Krész,et al. Dynamic Communities and their Detection , 2011, Acta Cybern..
[67] Siyuan Liu,et al. Online Community Transition Detection , 2014, WAIM.
[68] Malik Magdon-Ismail,et al. Tracking and Predicting Evolution of Social Communities , 2011, 2011 IEEE Third Int'l Conference on Privacy, Security, Risk and Trust and 2011 IEEE Third Int'l Conference on Social Computing.
[69] Yun Chi,et al. Facetnet: a framework for analyzing communities and their evolutions in dynamic networks , 2008, WWW.
[70] Matthieu Latapy,et al. Computing maximal cliques in link streams , 2015, Theor. Comput. Sci..
[71] Tina Eliassi-Rad,et al. Applying latent dirichlet allocation to group discovery in large graphs , 2009, SAC '09.
[72] D. Bassett,et al. Dynamic reconfiguration of frontal brain networks during executive cognition in humans , 2015, Proceedings of the National Academy of Sciences.
[73] Jukka-Pekka Onnela,et al. Community Structure in Time-Dependent, Multiscale, and Multiplex Networks , 2009, Science.
[74] Rémy Cazabet,et al. Detection of Overlapping Communities in Dynamical Social Networks , 2010, 2010 IEEE Second International Conference on Social Computing.
[75] Alfred O. Hero,et al. Dynamic Stochastic Blockmodels for Time-Evolving Social Networks , 2014, IEEE Journal of Selected Topics in Signal Processing.
[76] M E J Newman,et al. Community structure in social and biological networks , 2001, Proceedings of the National Academy of Sciences of the United States of America.
[77] Przemyslaw Kazienko,et al. GED: the method for group evolution discovery in social networks , 2012, Social Network Analysis and Mining.
[78] Luis E C Rocha,et al. Exploiting Temporal Network Structures of Human Interaction to Effectively Immunize Populations , 2010, PloS one.
[79] Yizhou Sun,et al. Co-Evolution of Multi-Typed Objects in Dynamic Star Networks , 2014, IEEE Transactions on Knowledge and Data Engineering.
[80] F. Radicchi,et al. Benchmark graphs for testing community detection algorithms. , 2008, Physical review. E, Statistical, nonlinear, and soft matter physics.
[81] Naonori Ueda,et al. Dynamic Infinite Relational Model for Time-varying Relational Data Analysis , 2010, NIPS.
[82] Faraz Zaidi,et al. Detecting Structural Changes and Command Hierarchies in Dynamic Social Networks , 2009, 2009 International Conference on Advances in Social Network Analysis and Mining.
[83] Niloy Ganguly,et al. Dynamics On and Of Complex Networks, Volume 2 , 2013 .
[84] Jen-Wei Huang,et al. CUT: community update and tracking in dynamic social networks , 2013, SNAKDD '13.
[85] Nagiza F. Samatova,et al. Detecting and Tracking Community Dynamics in Evolutionary Networks , 2010, 2010 IEEE International Conference on Data Mining Workshops.
[86] Ayellet Tal,et al. Dynamic Drawing of Clustered Graphs , 2004 .
[87] Giulio Rossetti,et al. $$\text{RD}\small{\text{YN}}$$ : graph benchmark handling community dynamics , 2017, J. Complex Networks.
[88] M. Newman,et al. Finding community structure in very large networks. , 2004, Physical review. E, Statistical, nonlinear, and soft matter physics.
[89] Boleslaw K. Szymanski,et al. LabelRankT: incremental community detection in dynamic networks via label propagation , 2013, DyNetMM '13.
[90] Dorothea Wagner,et al. Clustering Evolving Networks , 2014, Algorithm Engineering.
[91] Fabian Beck,et al. Visualizing the Evolution of Communities in Dynamic Graphs , 2015, Comput. Graph. Forum.
[92] Komal Kumar Bhatia,et al. Page Ranking Algorithms: A Survey , 2009, 2009 IEEE International Advance Computing Conference.
[93] Yihong Gong,et al. A Bayesian Approach Toward Finding Communities and Their Evolutions in Dynamic Social Networks , 2009, SDM.
[94] Myra Spiliopoulou,et al. Data Mining for Community Dynamics , 2007, Künstliche Intell..
[95] Kevin W. Boyack,et al. Mapping the structure and evolution of chemistry research , 2009, Scientometrics.
[96] Mason A. Porter,et al. Multilayer networks , 2013, J. Complex Networks.
[97] Zhengding Lu,et al. Community mining on dynamic weighted directed graphs , 2009, CIKM-CNIKM.
[98] Srinivasan Parthasarathy,et al. An event-based framework for characterizing the evolutionary behavior of interaction graphs , 2007, KDD '07.
[99] Jari Saramäki,et al. Temporal motifs in time-dependent networks , 2011, ArXiv.
[100] Rémy Cazabet,et al. Dynamic Community Detection , 2014, Encyclopedia of Social Network Analysis and Mining.
[101] Krithi Ramamritham,et al. Real Time Discovery of Dense Clusters in Highly Dynamic Graphs: Identifying Real World Events in Highly Dynamic Environments , 2012, Proc. VLDB Endow..
[102] Carl T. Bergstrom,et al. Mapping Change in Large Networks , 2008, PloS one.
[103] Naoki Masuda,et al. A Guide to Temporal Networks , 2016, Series on Complexity Science.
[104] L. Shapiro,et al. TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE , 2022 .
[105] Tina Eliassi-Rad,et al. Continuous Time Group Discovery in Dynamic Graphs , 2010, NIPS 2010.
[106] Michael Burch,et al. A Taxonomy and Survey of Dynamic Graph Visualization , 2017, Comput. Graph. Forum.
[107] Fabian Beck,et al. Visualizing Dynamic Hierarchies in Graph Sequences , 2016, IEEE Transactions on Visualization and Computer Graphics.
[108] Alan M. Frieze,et al. Random graphs , 2006, SODA '06.
[109] Walter Dempsey,et al. Community detection for interaction networks , 2015, ArXiv.
[110] Jari Saramäki,et al. Temporal Networks , 2011, Encyclopedia of Social Network Analysis and Mining.
[111] Leto Peel,et al. Detecting Change Points in the Large-Scale Structure of Evolving Networks , 2014, AAAI.
[112] Dino Pedreschi,et al. Tiles: an online algorithm for community discovery in dynamic social networks , 2017, Machine Learning.
[113] Jean-Loup Guillaume,et al. Fast unfolding of communities in large networks , 2008, 0803.0476.
[114] Michael Kirley,et al. Community evolution in a scientific collaboration network , 2012, 2012 IEEE Congress on Evolutionary Computation.
[115] Nagehan Ilhan,et al. Predicting community evolution based on time series modeling , 2015, 2015 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining (ASONAM).
[116] Richard M. Karp,et al. Algorithms for graph partitioning on the planted partition model , 2001, Random Struct. Algorithms.
[117] Ciro Cattuto,et al. Detecting the Community Structure and Activity Patterns of Temporal Networks: A Non-Negative Tensor Factorization Approach , 2013, PloS one.
[118] S. Shen-Orr,et al. Network motifs: simple building blocks of complex networks. , 2002, Science.
[119] Derek Greene,et al. Tracking the Evolution of Communities in Dynamic Social Networks , 2010, 2010 International Conference on Advances in Social Networks Analysis and Mining.
[120] Jiawei Han,et al. A Particle-and-Density Based Evolutionary Clustering Method for Dynamic Networks , 2009, Proc. VLDB Endow..
[121] Daquan Tang,et al. Community Core Evolution in Mobile Social Networks , 2013, TheScientificWorldJournal.
[122] Riccardo Dondi,et al. Algorithmic Aspects in Information and Management , 2016, Lecture Notes in Computer Science.
[123] Santo Fortunato,et al. Community detection in networks: A user guide , 2016, ArXiv.
[124] M E J Newman,et al. Finding and evaluating community structure in networks. , 2003, Physical review. E, Statistical, nonlinear, and soft matter physics.
[125] Christos Faloutsos,et al. Graphs over time: densification laws, shrinking diameters and possible explanations , 2005, KDD '05.
[126] Lise Getoor,et al. Link mining: a survey , 2005, SKDD.
[127] Cristopher Moore,et al. Detectability thresholds and optimal algorithms for community structure in dynamic networks , 2015, ArXiv.
[128] Jean-Loup Guillaume,et al. Static community detection algorithms for evolving networks , 2010, 8th International Symposium on Modeling and Optimization in Mobile, Ad Hoc, and Wireless Networks.
[129] José Ignacio Alvarez-Hamelin,et al. Visualizing communities in dynamic networks , 2010 .
[130] Rolf Niedermeier,et al. Enumerating maximal cliques in temporal graphs , 2016, 2016 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining (ASONAM).
[131] Dorothea Wagner,et al. Modularity-Driven Clustering of Dynamic Graphs , 2010, SEA.
[132] Boleslaw K. Szymanski,et al. Overlapping community detection in networks: The state-of-the-art and comparative study , 2011, CSUR.
[133] Srinivasan Parthasarathy,et al. An event-based framework for characterizing the evolutionary behavior of interaction graphs , 2009, ACM Trans. Knowl. Discov. Data.
[134] Jalel Akaichi,et al. Overlapping community detection in social networks , 2013, 2013 IEEE International Conference on Bioinformatics and Biomedicine.
[135] Yihong Gong,et al. Detecting communities and their evolutions in dynamic social networks—a Bayesian approach , 2011, Machine Learning.
[136] Hongyuan Zha,et al. Discovering Temporal Communities from Social Network Documents , 2007, Seventh IEEE International Conference on Data Mining (ICDM 2007).
[137] Fabian Beck,et al. The State of the Art in Visualizing Group Structures in Graphs , 2015, EuroVis.
[138] Przemyslaw Kazienko,et al. Predicting community evolution in social networks , 2015, 2015 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining (ASONAM).
[139] Sylvain Peyronnet,et al. On the Evaluation Potential of Quality Functions in Community Detection for Different Contexts , 2015, NetSci-X.
[140] Maoguo Gong,et al. Community Detection in Dynamic Social Networks Based on Multiobjective Immune Algorithm , 2012, Journal of Computer Science and Technology.
[141] Hans-Peter Kriegel,et al. A Density-Based Algorithm for Discovering Clusters in Large Spatial Databases with Noise , 1996, KDD.
[142] M E J Newman,et al. Fast algorithm for detecting community structure in networks. , 2003, Physical review. E, Statistical, nonlinear, and soft matter physics.
[143] Jean-Loup Guillaume,et al. Communities in Evolving Networks: Definitions, Detection, and Analysis Techniques , 2013 .
[144] Santo Fortunato,et al. A benchmark model to assess community structure in evolving networks , 2015, Physical review. E, Statistical, nonlinear, and soft matter physics.
[145] Dino Pedreschi,et al. A classification for community discovery methods in complex networks , 2011, Stat. Anal. Data Min..
[146] Leto Peel,et al. The ground truth about metadata and community detection in networks , 2016, Science Advances.
[147] Laks V. S. Lakshmanan,et al. Incremental cluster evolution tracking from highly dynamic network data , 2014, 2014 IEEE 30th International Conference on Data Engineering.
[148] E. N. Sawardecker,et al. Detection of node group membership in networks with group overlap , 2008, 0812.1243.
[149] Pablo Jensen,et al. Revealing evolutions in dynamical networks , 2017, ArXiv.
[150] Vikas Kawadia,et al. Sequential detection of temporal communities by estrangement confinement , 2012, Scientific Reports.
[151] Bo Zhao,et al. Community evolution detection in dynamic heterogeneous information networks , 2010, MLG '10.
[152] Z. Di,et al. Accuracy and precision of methods for community identification in weighted networks , 2006, physics/0607271.
[153] A. Barabasi,et al. Quantifying social group evolution , 2007, Nature.
[154] Giulio Rossetti,et al. A Novel Approach to Evaluate Community Detection Algorithms on Ground Truth , 2016, CompleNet.
[155] Jitendra Malik,et al. Normalized Cuts and Image Segmentation , 2000, IEEE Trans. Pattern Anal. Mach. Intell..
[156] Andrea Lancichinetti,et al. Detecting the overlapping and hierarchical community structure in complex networks , 2008, 0802.1218.
[157] Dorothea Wagner,et al. Dynamic Graph Clustering Using Minimum-Cut Trees , 2009, J. Graph Algorithms Appl..
[158] Przemyslaw Kazienko,et al. Identification of Group Changes in Blogosphere , 2012, 2012 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining.
[159] Roger Guimerà,et al. Module identification in bipartite and directed networks. , 2007, Physical review. E, Statistical, nonlinear, and soft matter physics.
[160] Santo Fortunato,et al. Community detection in graphs , 2009, ArXiv.