暂无分享,去创建一个
[1] Allan Sly,et al. Random graphs with a given degree sequence , 2010, 1005.1136.
[2] Jonathan W. Berry,et al. Tolerating the community detection resolution limit with edge weighting. , 2008, Physical review. E, Statistical, nonlinear, and soft matter physics.
[3] Mason A. Porter,et al. Comparing Community Structure to Characteristics in Online Collegiate Social Networks , 2008, SIAM Rev..
[4] Pascal Pons,et al. Post-processing hierarchical community structures: Quality improvements and multi-scale view , 2006, Theor. Comput. Sci..
[5] Robert H. Halstead,et al. Matrix Computations , 2011, Encyclopedia of Parallel Computing.
[6] Tom A. B. Snijders,et al. Social Network Analysis , 2011, International Encyclopedia of Statistical Science.
[7] H. A. David. Order Statistics , 2011, International Encyclopedia of Statistical Science.
[8] Benjamin H. Good,et al. Performance of modularity maximization in practical contexts. , 2009, Physical review. E, Statistical, nonlinear, and soft matter physics.
[9] F. Radicchi,et al. Statistical significance of communities in networks. , 2009, Physical review. E, Statistical, nonlinear, and soft matter physics.
[10] Charlotte M. Deane,et al. The function of communities in protein interaction networks at multiple scales , 2009, BMC Systems Biology.
[11] Sune Lehmann,et al. Link communities reveal multiscale complexity in networks , 2009, Nature.
[12] Youngdo Kim,et al. Finding communities in directed networks. , 2009, Physical review. E, Statistical, nonlinear, and soft matter physics.
[13] Jean-Charles Delvenne,et al. Stability of graph communities across time scales , 2008, Proceedings of the National Academy of Sciences.
[14] Carl T. Bergstrom,et al. Mapping Change in Large Networks , 2008, PloS one.
[15] P. Ronhovde,et al. Local resolution-limit-free Potts model for community detection. , 2008, Physical review. E, Statistical, nonlinear, and soft matter physics.
[16] A. Wirth. Correlation Clustering , 2010, Encyclopedia of Machine Learning and Data Mining.
[17] Charu C. Aggarwal,et al. Graph Clustering , 2010, Encyclopedia of Machine Learning and Data Mining.
[18] Andrea Lancichinetti,et al. Community detection algorithms: a comparative analysis: invited presentation, extended abstract , 2009, VALUETOOLS.
[19] Jiawei Han,et al. A Particle-and-Density Based Evolutionary Clustering Method for Dynamic Networks , 2009, Proc. VLDB Endow..
[20] Armen E. Allahverdyan,et al. Community detection with and without prior information , 2009, ArXiv.
[21] R. Lambiotte,et al. Line graphs, link partitions, and overlapping communities. , 2009, Physical review. E, Statistical, nonlinear, and soft matter physics.
[22] E. Holmström,et al. Modularity density of network community divisions , 2009 .
[23] Ernesto Estrada,et al. Communicability graph and community structures in complex networks , 2009, Appl. Math. Comput..
[24] Huawei Shen,et al. Quantifying and identifying the overlapping community structure in networks , 2009, 0905.2666.
[25] 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.
[26] K. A. Samani,et al. Eigenvectors of network complement reveal community structure more accurately , 2009 .
[27] Juan Mei,et al. Revealing network communities through modularity maximization by a contraction–dilation method , 2009 .
[28] Wei Ren,et al. Simple probabilistic algorithm for detecting community structure. , 2009, Physical review. E, Statistical, nonlinear, and soft matter physics.
[29] Yong-Yeol Ahn,et al. Communities and Hierarchical Organization of Links in Complex Networks , 2009 .
[30] M. Barber,et al. Detecting network communities by propagating labels under constraints. , 2009, Physical review. E, Statistical, nonlinear, and soft matter physics.
[31] François Fouss,et al. Graph nodes clustering with the sigmoid commute-time kernel: A comparative study , 2009, Data Knowl. Eng..
[32] Mason A. Porter,et al. Communities in Networks , 2009, ArXiv.
[33] Enhong Chen,et al. Finding Community Structure Based on Subgraph Similarity , 2009, CompleNet.
[34] Yiannis Kompatsiaris,et al. Bridge Bounding: A Local Approach for Efficient Community Discovery in Complex Networks , 2009, 0902.0871.
[35] Kevin E. Bassler,et al. Improved community structure detection using a modified fine-tuning strategy , 2009, ArXiv.
[36] Andreas Noack,et al. Multi-level Algorithms for Modularity Clustering , 2008, SEA.
[37] Pablo Jensen,et al. Analysis of community structure in networks of correlated data. , 2008, Physical review. E, Statistical, nonlinear, and soft matter physics.
[38] P. Mucha,et al. Spectral tripartitioning of networks. , 2008, Physical review. E, Statistical, nonlinear, and soft matter physics.
[39] P. Ronhovde,et al. Multiresolution community detection for megascale networks by information-based replica correlations. , 2008, Physical review. E, Statistical, nonlinear, and soft matter physics.
[40] E. N. Sawardecker,et al. Detection of node group membership in networks with group overlap , 2008, 0812.1243.
[41] Nick S. Jones,et al. Dynamic communities in multichannel data: an application to the foreign exchange market during the 2007-2008 credit crisis. , 2008, Chaos.
[42] V. Traag,et al. Community detection in networks with positive and negative links. , 2008, Physical review. E, Statistical, nonlinear, and soft matter physics.
[43] P. Pin,et al. Assessing the relevance of node features for network structure , 2008, Proceedings of the National Academy of Sciences.
[44] Jure Leskovec,et al. Community Structure in Large Networks: Natural Cluster Sizes and the Absence of Large Well-Defined Clusters , 2008, Internet Math..
[45] M. Mitrovic,et al. Spectral and dynamical properties in classes of sparse networks with mesoscopic inhomogeneities. , 2008, Physical review. E, Statistical, nonlinear, and soft matter physics.
[46] Fabrizio Lillo,et al. Correlation, Hierarchies, and Networks in Financial Markets , 2008, 0809.4615.
[47] Pietro Liò,et al. Towards real-time community detection in large networks. , 2008, Physical review. E, Statistical, nonlinear, and soft matter physics.
[48] Andreas Noack,et al. Modularity clustering is force-directed layout , 2008, Physical review. E, Statistical, nonlinear, and soft matter physics.
[49] Andrea Lancichinetti,et al. Detecting the overlapping and hierarchical community structure in complex networks , 2008, 0802.1218.
[50] V. Carchiolo,et al. Extending the definition of modularity to directed graphs with overlapping communities , 2008, 0801.1647.
[51] Claudio Castellano,et al. Community Structure in Graphs , 2007, Encyclopedia of Complexity and Systems Science.
[52] Srinivasan Parthasarathy,et al. An event-based framework for characterizing the evolutionary behavior of interaction graphs , 2007, KDD '07.
[53] Steve Gregory,et al. Finding Overlapping Communities Using Disjoint Community Detection Algorithms , 2009, CompleNet.
[54] S. Borgatti,et al. Analyzing Clique Overlap , 2009 .
[55] Robert A. Meyers,et al. Encyclopedia of Complexity and Systems Science , 2009 .
[56] Charalambos A. Charalambides,et al. Enumerative combinatorics , 2018, SIGA.
[57] Ying Wang,et al. Quantitative Function for Community Detection , 2012, Physical review. E, Statistical, nonlinear, and soft matter physics.
[58] R. Lambiotte,et al. Random Walks, Markov Processes and the Multiscale Modular Organization of Complex Networks , 2008, IEEE Transactions on Network Science and Engineering.
[59] Christophe Ambroise,et al. Fast online graph clustering via Erdös-Rényi mixture , 2008, Pattern Recognit..
[60] Jun Yu,et al. Adaptive clustering algorithm for community detection in complex networks. , 2008, Physical review. E, Statistical, nonlinear, and soft matter physics.
[61] Mao-Bin Hu,et al. Detect overlapping and hierarchical community structure in networks , 2008, ArXiv.
[62] Alessandro Vespignani,et al. Dynamical Processes on Complex Networks , 2008 .
[63] José J. Ramasco,et al. Who is keeping you in that community? , 2008, ArXiv.
[64] Muhittin Mungan,et al. Stability of maximum-likelihood-based clustering methods: exploring the backbone of classifications , 2008, 0809.1398.
[65] Mason A. Porter,et al. Community Structure in Online Collegiate Social Networks , 2008 .
[66] Jure Leskovec,et al. Microscopic evolution of social networks , 2008, KDD.
[67] Amedeo Caflisch,et al. Multistep greedy algorithm identifies community structure in real-world and computer-generated networks , 2008, Physical review. E, Statistical, nonlinear, and soft matter physics.
[68] J M Buldú,et al. Synchronization interfaces and overlapping communities in complex networks. , 2008, Physical review letters.
[69] P. Csermely. Creative elements: network-based predictions of active centres in proteins and cellular and social networks. , 2008, Trends in biochemical sciences.
[70] M. Krawczyk. Differential equations as a tool for community identification. , 2008, Physical review. E, Statistical, nonlinear, and soft matter physics.
[71] Tiejun Li,et al. Optimal partition and effective dynamics of complex networks , 2008, Proceedings of the National Academy of Sciences.
[72] Ming Ouyang,et al. A vector partitioning approach to detecting community structure in complex networks , 2008, Comput. Math. Appl..
[73] F. Radicchi,et al. Benchmark graphs for testing community detection algorithms. , 2008, Physical review. E, Statistical, nonlinear, and soft matter physics.
[74] Kristina Lerman,et al. Community Detection Using a Measure of Global Influence , 2008, SNAKDD.
[75] A. Vázquez. Bayesian approach to clustering real value, categorical and network data: solution via variational methods , 2008, 0805.2689.
[76] J. Kumpula,et al. Sequential algorithm for fast clique percolation. , 2008, Physical review. E, Statistical, nonlinear, and soft matter physics.
[77] M. Newman,et al. Hierarchical structure and the prediction of missing links in networks , 2008, Nature.
[78] B. Wellman. The Development of Social Network Analysis: A Study in the Sociology of Science , 2008 .
[79] Bin Wu,et al. Overlapping Community Detection in Bipartite Networks , 2008, 2008 IEEE/WIC/ACM International Conference on Web Intelligence and Intelligent Agent Technology.
[80] J. Kumpula,et al. Detecting modules in dense weighted networks with the Potts method , 2008, 0804.3457.
[81] Yun Chi,et al. Facetnet: a framework for analyzing communities and their evolutions in dynamic networks , 2008, WWW.
[82] Falk Schreiber,et al. Analysis of Biological Networks , 2008 .
[83] J. Kertész,et al. On the equivalence of the label propagation method of community detection and a Potts model approach , 2008, 0803.2804.
[84] M. Barber,et al. Searching for Communities in Bipartite Networks , 2008, 0803.2854.
[85] P. Ronhovde,et al. A highly accurate and resolution-limit-free Potts model for community detection , 2008 .
[86] A. Coolen,et al. Entropies of complex networks with hierarchically constrained topologies. , 2008, Physical review. E, Statistical, nonlinear, and soft matter physics.
[87] William Y. C. Chen,et al. Community Structures of Networks , 2008, Math. Comput. Sci..
[88] Jean-Loup Guillaume,et al. Fast unfolding of communities in large networks , 2008, 0803.0476.
[89] Peng Zhang,et al. Comparative definition of community and corresponding identifying algorithm. , 2008, Physical review. E, Statistical, nonlinear, and soft matter physics.
[90] Jiming Liu,et al. Discovering global network communities based on local centralities , 2008, TWEB.
[91] S. Forrest,et al. A dual assortative measure of community structure , 2008, 0801.3290.
[92] Alexei Vazquez,et al. Population stratification using a statistical model on hypergraphs , 2007, Physical review. E, Statistical, nonlinear, and soft matter physics.
[93] Amedeo Caflisch,et al. Efficient modularity optimization by multistep greedy algorithm and vertex mover refinement. , 2007, Physical review. E, Statistical, nonlinear, and soft matter physics.
[94] Michele Leone,et al. (Un)detectable cluster structure in sparse networks. , 2007, Physical review letters.
[95] J. Ramasco,et al. Inversion method for content-based networks. , 2007, Physical review. E, Statistical, nonlinear, and soft matter physics.
[96] Z. Di,et al. Community detection by signaling on complex networks. , 2007, Physical review. E, Statistical, nonlinear, and soft matter physics.
[97] S. Lehmann,et al. Biclique communities. , 2007, Physical review. E, Statistical, nonlinear, and soft matter physics.
[98] Vladimir Gudkov,et al. Community Detection in Complex Networks by Dynamical Simplex Evolution , 2007, Physical review. E, Statistical, nonlinear, and soft matter physics.
[99] Z. Di,et al. Clustering coefficient and community structure of bipartite networks , 2007, 0710.0117.
[100] A. Arenas,et al. Motif-based communities in complex networks , 2007, 0710.0059.
[101] E A Leicht,et al. Community structure in directed networks. , 2007, Physical review letters.
[102] Chris H Wiggins,et al. Bayesian approach to network modularity. , 2007, Physical review letters.
[103] M. Newman,et al. Robustness of community structure in networks. , 2007, Physical review. E, Statistical, nonlinear, and soft matter physics.
[104] David Gfeller,et al. Spectral coarse graining and synchronization in oscillator networks. , 2007, Physical review letters.
[105] Amanda L. Traud,et al. Community Structure in Congressional Cosponsorship Networks , 2007, 0708.1191.
[106] T. Nepusz,et al. Fuzzy communities and the concept of bridgeness in complex networks. , 2007, Physical review. E, Statistical, nonlinear, and soft matter physics.
[107] Ernesto Estrada,et al. Communicability in complex networks. , 2007, Physical review. E, Statistical, nonlinear, and soft matter physics.
[108] Martin Rosvall,et al. Maps of random walks on complex networks reveal community structure , 2007, Proceedings of the National Academy of Sciences.
[109] James P. Bagrow. Evaluating local community methods in networks , 2007, 0706.3880.
[110] Weixiong Zhang,et al. Identifying network communities with a high resolution. , 2007, Physical review. E, Statistical, nonlinear, and soft matter physics.
[111] Alex Arenas,et al. Analysis of the structure of complex networks at different resolution levels , 2007, physics/0703218.
[112] Derek Greene,et al. Community Finding in Large Social Networks Through Problem Decomposition , 2008 .
[113] C. Bernido,et al. Stochastic and quantum dynamics of biomolecular systems : proceedings of the 5th Jagna International Workshop, Jagna, Bohol, Philippines 3-5 January 2008 , 2008 .
[114] Christos Faloutsos,et al. Random walk with restart: fast solutions and applications , 2008, Knowledge and Information Systems.
[115] Lazaros G. Papageorgiou,et al. Finding community structures in complex networks using mixed integer optimisation , 2007 .
[116] Kevin H. Knuth,et al. Bayesian Inference and Maximum Entropy Methods in Science and Engineering: 27th International Workshop on Bayesian Inference and Maximum Entropy Methods , 2007 .
[117] C. J. Rhodes,et al. Social network topology: a Bayesian approach , 2007, J. Oper. Res. Soc..
[118] T. Snijders,et al. Bayesian inference for dynamic social network data , 2007 .
[119] Ulrike von Luxburg,et al. A tutorial on spectral clustering , 2007, Stat. Comput..
[120] Inderjit S. Dhillon,et al. Weighted Graph Cuts without Eigenvectors A Multilevel Approach , 2007, IEEE Transactions on Pattern Analysis and Machine Intelligence.
[121] Weixiong Zhang,et al. An Efficient Spectral Algorithm for Network Community Discovery and Its Applications to Biological and Social Networks , 2007, Seventh IEEE International Conference on Data Mining (ICDM 2007).
[122] Philip S. Yu,et al. Community Learning by Graph Approximation , 2007, Seventh IEEE International Conference on Data Mining (ICDM 2007).
[123] Jonathan W. Berry,et al. Community Detection via Facility Location , 2007, 0710.3800.
[124] Wei Ren,et al. A Simple Probabilistic Algorithm for Detecting Community Structure in Social Networks , 2007, 0710.3422.
[125] David Kempe,et al. Modularity-maximizing graph communities via mathematical programming , 2007, 0710.2533.
[126] Stan Matwin,et al. Proceedings of the 11th European conference on Principles and Practice of Knowledge Discovery in Databases , 2007 .
[127] Steve Gregory,et al. An Algorithm to Find Overlapping Community Structure in Networks , 2007, PKDD.
[128] Réka Albert,et al. Near linear time algorithm to detect community structures in large-scale networks. , 2007, Physical review. E, Statistical, nonlinear, and soft matter physics.
[129] M. Krawczyk,et al. Communities in networks - a continuous approach , 2007, 0709.0923.
[130] Xiaowei Xu,et al. A Novel Similarity-Based Modularity Function for Graph Partitioning , 2007, DaWaK.
[131] Pan Hui,et al. Distributed community detection in delay tolerant networks , 2007, MobiArch '07.
[132] Philip S. Yu,et al. GraphScope: parameter-free mining of large time-evolving graphs , 2007, KDD '07.
[133] Yun Chi,et al. Evolutionary spectral clustering by incorporating temporal smoothness , 2007, KDD '07.
[134] Douglas R. White,et al. Role models for complex networks , 2007, 0708.0958.
[135] Satu Elisa Schaeffer,et al. Graph Clustering , 2017, Encyclopedia of Machine Learning and Data Mining.
[136] G. Bianconi. The entropy of randomized network ensembles , 2007, 0708.0153.
[137] M. Barber. Modularity and community detection in bipartite networks. , 2007, Physical review. E, Statistical, nonlinear, and soft matter physics.
[138] Roger Guimerà,et al. A network-based method for target selection in metabolic networks , 2007, Bioinform..
[139] Guido Caldarelli,et al. Large Scale Structure and Dynamics of Complex Networks: From Information Technology to Finance and Natural Science , 2007 .
[140] David D. Jensen,et al. Graph clustering with network structure indices , 2007, ICML '07.
[141] János Kertész,et al. Noise and Stochastics in Complex Systems and Finance , 2007 .
[142] Dorothea Wagner,et al. Significance-Driven Graph Clustering , 2007, AAIM.
[143] David Gfeller,et al. Spectral coarse graining of complex networks. , 2007, Physical review letters.
[144] J. Reichardt,et al. Clustering of sparse data via network communities—a prototype study of a large online market , 2007 .
[145] Jari Saramäki,et al. Limited resolution and multiresolution methods in complex network community detection , 2007, SPIE International Symposium on Fluctuations and Noise.
[146] Guojun Gan,et al. Data Clustering: Theory, Algorithms, and Applications (ASA-SIAM Series on Statistics and Applied Probability) , 2007 .
[147] Santo Fortunato,et al. Quality functions in community detection , 2007, SPIE International Symposium on Fluctuations and Noise.
[148] Xin Liu,et al. Effective Algorithm for Detecting Community Structure in Complex Networks Based on GA and Clustering , 2007, International Conference on Computational Science.
[149] François Fouss,et al. Graph Nodes Clustering Based on the Commute-Time Kernel , 2007, PAKDD.
[150] Roger Guimerà,et al. Extracting the hierarchical organization of complex systems , 2007, Proceedings of the National Academy of Sciences.
[151] Marco Pellegrini,et al. Extraction and classification of dense communities in the web , 2007, WWW '07.
[152] Jon M. Kleinberg,et al. The link-prediction problem for social networks , 2007, J. Assoc. Inf. Sci. Technol..
[153] M. Meilă. Comparing clusterings---an information based distance , 2007 .
[154] A. Barabasi,et al. Quantifying social group evolution , 2007, Nature.
[155] T. Vicsek,et al. Weighted network modules , 2007, cond-mat/0703706.
[156] N. Alves. Unveiling community structures in weighted networks. , 2007, Physical review. E, Statistical, nonlinear, and soft matter physics.
[157] François Fouss,et al. Random-Walk Computation of Similarities between Nodes of a Graph with Application to Collaborative Recommendation , 2007, IEEE Transactions on Knowledge and Data Engineering.
[158] A. Raftery,et al. Model‐based clustering for social networks , 2007 .
[159] Ken Wakita,et al. Finding community structure in mega-scale social networks: [extended abstract] , 2007, WWW '07.
[160] Sergio Gómez,et al. Size reduction of complex networks preserving modularity , 2007, ArXiv.
[161] S. Lehmann,et al. Deterministic modularity optimization , 2007, physics/0701348.
[162] Shihua Zhang,et al. Identification of overlapping community structure in complex networks using fuzzy c-means clustering , 2007 .
[163] Yoshi Fujiwara,et al. A Gap in the Community-Size Distribution of a Large-Scale Social Networking Site , 2007, ArXiv.
[164] R. Guimerà,et al. Module identification in bipartite and directed networks. , 2007, Physical review. E, Statistical, nonlinear, and soft matter physics.
[165] Rajeev Sangal,et al. Proceedings of the 20th international joint conference on Artifical intelligence , 2007 .
[166] Marco Gori,et al. ItemRank: A Random-Walk Based Scoring Algorithm for Recommender Engines , 2007, IJCAI.
[167] Carl T. Bergstrom,et al. An information-theoretic framework for resolving community structure in complex networks , 2006, Proceedings of the National Academy of Sciences.
[168] E A Leicht,et al. Mixture models and exploratory analysis in networks , 2006, Proceedings of the National Academy of Sciences.
[169] A. Arenas,et al. Synchronization and modularity in complex networks , 2006, cond-mat/0610726.
[170] Z. Di,et al. Accuracy and precision of methods for community identification in weighted networks , 2006, physics/0607271.
[171] V. Latora,et al. Detecting complex network modularity by dynamical clustering. , 2006, Physical review. E, Statistical, nonlinear, and soft matter physics.
[172] S. Fortunato,et al. Resolution limit in community detection , 2006, Proceedings of the National Academy of Sciences.
[173] J. Reichardt,et al. Partitioning and modularity of graphs with arbitrary degree distribution. , 2006, Physical review. E, Statistical, nonlinear, and soft matter physics.
[174] Jon Kleinberg,et al. KDD '07: Proceedings of the 13th ACM SIGKDD international conference on Knowledge discovery and data mining , 2007, KDD 2007.
[175] Yuval Rabani,et al. Linear Programming , 2007, Handbook of Approximation Algorithms and Metaheuristics.
[176] Dorothea Wagner,et al. How to Evaluate Clustering Techniques , 2007 .
[177] M. Kenward,et al. An Introduction to the Bootstrap , 2007 .
[178] J. Jeffry Howbert,et al. The Maximum Clique Problem , 2007 .
[179] D. Parkes,et al. Analysis of Bidding Networks in eBay: Aggregate Preference Identification through Community Detection , 2007 .
[180] Edoardo M. Airoldi,et al. Statistical Network Analysis: Models, Issues, and New Directions - ICML 2006 Workshop on Statistical Network Analysis, Pittsburgh, PA, USA, June 29, 2006, Revised Selected Papers , 2007, SNA@ICML.
[181] Haifeng Du,et al. An algorithm for detecting community structure of social networks based on prior knowledge and modularity , 2007, Complex..
[182] Hristo Djidjev,et al. A Scalable Multilevel Algorithm for Graph Clustering and Community Structure Detection , 2007, WAW.
[183] Sabine Van Huffel,et al. On the Design of a Web-Based Decision Support System for Brain Tumour Diagnosis Using Distributed Agents , 2006, 2006 IEEE/WIC/ACM International Conference on Web Intelligence and Intelligent Agent Technology Workshops.
[184] Kazuyuki Tanaka,et al. Nonadditive Volume and Community Detection Problem in Complex Networks , 2006 .
[185] Budapest University of Technology,et al. Limited resolution in complex network community detection with Potts model approach , 2006, cond-mat/0610370.
[186] J. Doye,et al. Thermodynamics of Community Structure , 2006, cond-mat/0610077.
[187] Jingchun Chen,et al. Detecting functional modules in the yeast protein-protein interaction network , 2006, Bioinform..
[188] Deepayan Chakrabarti,et al. Evolutionary clustering , 2006, KDD '06.
[189] Ravi Kumar,et al. Structure and evolution of online social networks , 2006, KDD '06.
[190] Jon M. Kleinberg,et al. Group formation in large social networks: membership, growth, and evolution , 2006, KDD '06.
[191] David D. Jensen,et al. Using structure indices for efficient approximation of network properties , 2006, KDD '06.
[192] Binghong Wang,et al. Notes on the Algorithm for Calculating Betweenness , 2005, physics/0511084.
[193] Andrzej Kloczkowski,et al. Functional clustering of yeast proteins from the protein-protein interaction network , 2006, BMC Bioinformatics.
[194] Javier Béjar,et al. Clustering algorithm for determining community structure in large networks. , 2006, Physical review. E, Statistical, nonlinear, and soft matter physics.
[195] Z. Di,et al. The analysis and dissimilarity comparison of community structure , 2006 .
[196] I Vragović,et al. Network community structure and loop coefficient method. , 2006, Physical review. E, Statistical, nonlinear, and soft matter physics.
[197] Cristopher Moore,et al. Structural Inference of Hierarchies in Networks , 2006, SNA@ICML.
[198] S. Bornholdt,et al. When are networks truly modular , 2006, cond-mat/0606220.
[199] M. Newman,et al. Finding community structure in networks using the eigenvectors of matrices. , 2006, Physical review. E, Statistical, nonlinear, and soft matter physics.
[200] Johannes Berg,et al. Cross-species analysis of biological networks by Bayesian alignment. , 2006, Proceedings of the National Academy of Sciences of the United States of America.
[201] M. Hastings. Community detection as an inference problem. , 2006, Physical review. E, Statistical, nonlinear, and soft matter physics.
[202] Haluk Bingol,et al. Community Detection in Complex Networks Using Genetic Algorithms , 2006, 0711.0491.
[203] J. Reichardt,et al. Statistical mechanics of community detection. , 2006, Physical review. E, Statistical, nonlinear, and soft matter physics.
[204] L. D. Costa,et al. Fast Community Identification by Hierarchical Growth , 2006, physics/0602144.
[205] M E J Newman,et al. Modularity and community structure in networks. , 2006, Proceedings of the National Academy of Sciences of the United States of America.
[206] Mason A. Porter,et al. Community Structure in the United States House of Representatives , 2007, ArXiv.
[207] Illés J. Farkas,et al. CFinder: locating cliques and overlapping modules in biological networks , 2006, Bioinform..
[208] Monika Sharma,et al. Chemical oscillations , 2006 .
[209] T. Vicsek,et al. Preferential attachment of communities: The same principle, but a higher level , 2006, cond-mat/0601579.
[210] Alan M. Frieze,et al. Random graphs , 2006, SODA '06.
[211] Leon Danon,et al. The effect of size heterogeneity on community identification in complex networks , 2006, physics/0601144.
[212] M. Gustafsson,et al. Comparison and validation of community structures in complex networks , 2006, physics/0601057.
[213] A. Ruttenberg,et al. Edge‐count probabilities for the identification of local protein communities and their organization , 2005, Proteins.
[214] I. Ispolatov,et al. Finding mesoscopic communities in sparse networks , 2005, Journal of statistical mechanics.
[215] A. Arenas,et al. Synchronization reveals topological scales in complex networks. , 2005, Physical review letters.
[216] Jirí Síma,et al. On the NP-Completeness of Some Graph Cluster Measures , 2005, SOFSEM.
[217] Hawoong Jeong,et al. Random field Ising model and community structure in complex networks , 2005, cond-mat/0502672.
[218] Matthieu Latapy,et al. Computing Communities in Large Networks Using Random Walks , 2004, J. Graph Algorithms Appl..
[219] Sven Kosub,et al. The complexity of detecting fixed-density clusters , 2003, Discret. Appl. Math..
[220] Stéphane Lafon,et al. Diffusion maps , 2006 .
[221] J. Pinney,et al. Betweenness-based decomposition methods for social and biological networks , 2006 .
[222] Ulrik Brandes,et al. On Modularity - NP-Completeness and Beyond , 2006 .
[223] Casey M. Warmbrand,et al. A Network Analysis of Committees in the U.S. House of Representatives , 2013, Proceedings of the National Academy of Sciences of the United States of America.
[224] Paul A. Bates,et al. Cluster analysis of networks generated through homology: automatic identification of important protein communities involved in cancer metastasis , 2006, BMC Bioinformatics.
[225] A. Medus,et al. Detection of community structures in networks via global optimization , 2005 .
[226] I. Simonsen. Diffusion and networks: A powerful combination! , 2005, cond-mat/0508632.
[227] Christos Faloutsos,et al. Graphs over time: densification laws, shrinking diameters and possible explanations , 2005, KDD '05.
[228] David J. Earl,et al. Parallel tempering: theory, applications, and new perspectives. , 2005, Physical chemistry chemical physics : PCCP.
[229] Nicole A. Lazar,et al. Statistics of Extremes: Theory and Applications , 2005, Technometrics.
[230] 刘金明,et al. IL-13受体α2降低血吸虫病肉芽肿的炎症反应并延长宿主存活时间[英]/Mentink-Kane MM,Cheever AW,Thompson RW,et al//Proc Natl Acad Sci U S A , 2005 .
[231] M. A. Muñoz,et al. Modeling Cooperative Behavior in the Social Sciences , 2005 .
[232] T. Vicsek,et al. Uncovering the overlapping community structure of complex networks in nature and society , 2005, Nature.
[233] David Bawden,et al. Book Review: Evolution and Structure of the Internet: A Statistical Physics Approach. , 2006 .
[234] Gediminas Adomavicius,et al. Toward the next generation of recommender systems: a survey of the state-of-the-art and possible extensions , 2005, IEEE Transactions on Knowledge and Data Engineering.
[235] Malik Magdon-Ismail,et al. Efficient Identification of Overlapping Communities , 2005, ISI.
[236] Mason A. Porter,et al. A network analysis of committees in the United States House of Representatives , 2005, ArXiv.
[237] Pekka Orponen,et al. Local Clustering of Large Graphs by Approximate Fiedler Vectors , 2005, WEA.
[238] Leon Danon,et al. Comparing community structure identification , 2005, cond-mat/0505245.
[239] T. Vicsek,et al. Clique percolation in random networks. , 2005, Physical review letters.
[240] M. A. Muñoz,et al. Improved spectral algorithm for the detection of network communities , 2005, physics/0504059.
[241] Mark A. Pitt,et al. Advances in Minimum Description Length: Theory and Applications , 2005 .
[242] Jean-Cédric Chappelier,et al. Finding instabilities in the community structure of complex networks. , 2005, Physical review. E, Statistical, nonlinear, and soft matter physics.
[243] B. Nadler,et al. Diffusion maps, spectral clustering and reaction coordinates of dynamical systems , 2005, math/0503445.
[244] F. Rao,et al. Local modularity measure for network clusterizations. , 2005, Physical review. E, Statistical, nonlinear, and soft matter physics.
[245] A. Clauset. Finding local community structure in networks. , 2005, Physical review. E, Statistical, nonlinear, and soft matter physics.
[246] R. Guimerà,et al. Functional cartography of complex metabolic networks , 2005, Nature.
[247] Roger Guimerà,et al. Cartography of complex networks: modules and universal roles , 2005, Journal of statistical mechanics.
[248] A. Arenas,et al. Community detection in complex networks using extremal optimization. , 2005, Physical review. E, Statistical, nonlinear, and soft matter physics.
[249] J. Doye,et al. Identifying communities within energy landscapes. , 2004, Physical review. E, Statistical, nonlinear, and soft matter physics.
[250] E. Bollt,et al. Local method for detecting communities. , 2004, Physical review. E, Statistical, nonlinear, and soft matter physics.
[251] E. Ziv,et al. Information-theoretic approach to network modularity. , 2004, Physical review. E, Statistical, nonlinear, and soft matter physics.
[252] Uri Alon,et al. Coarse-graining and self-dissimilarity of complex networks. , 2004, Physical review. E, Statistical, nonlinear, and soft matter physics.
[253] G. Caldarelli,et al. Detecting communities in large networks , 2004, cond-mat/0402499.
[254] M. Newman. A measure of betweenness centrality based on random walks , 2003, Soc. Networks.
[255] Dennis M. Wilkinson,et al. E-Mail as Spectroscopy: Automated Discovery of Community Structure within Organizations , 2003, Inf. Soc..
[256] Padhraic Smyth,et al. A Spectral Clustering Approach To Finding Communities in Graph , 2005, SDM.
[257] Yicheng Zhang,et al. Referee networks and their spectral properties , 2005 .
[258] Salil P. Vadhan,et al. Computational Complexity , 2005, Encyclopedia of Cryptography and Security.
[259] M. Jackson,et al. Identifying Community Structures from Network Data , 2005 .
[260] Malik Magdon-Ismail,et al. Finding communities by clustering a graph into overlapping subgraphs , 2005, IADIS AC.
[261] Frank Dudbridge,et al. The Use of Edge-Betweenness Clustering to Investigate Biological Function in Protein Interaction Networks , 2005, BMC Bioinformatics.
[262] Andrzej Kudlicki,et al. Bayesian modeling of protein interaction networks , 2004 .
[263] V. Latora,et al. CHANGING OPINIONS IN A CHANGING WORLD: A NEW PERSPECTIVE IN SOCIOPHYSICS , 2004, cond-mat/0410217.
[264] Albert-László Barabási,et al. Evolution of Networks: From Biological Nets to the Internet and WWW , 2004 .
[265] Deepayan Chakrabarti,et al. AutoPart: Parameter-Free Graph Partitioning and Outlier Detection , 2004, PKDD.
[266] François Fouss,et al. The Principal Components Analysis of a Graph, and Its Relationships to Spectral Clustering , 2004, ECML.
[267] Jiawei Han,et al. Mining scale-free networks using geodesic clustering , 2004, KDD.
[268] M. Newman,et al. Finding community structure in very large networks. , 2004, Physical review. E, Statistical, nonlinear, and soft matter physics.
[269] Thomas A. Schreiber,et al. The University of South Florida free association, rhyme, and word fragment norms , 2004, Behavior research methods, instruments, & computers : a journal of the Psychonomic Society, Inc.
[270] M. Pellegrini,et al. Protein Interaction Networks , 2004, Expert review of proteomics.
[271] L. Freeman,et al. The Development of Social Network Analysis: A Study in the Sociology of Science , 2005 .
[272] M. Newman. Analysis of weighted networks. , 2004, Physical review. E, Statistical, nonlinear, and soft matter physics.
[273] Reinhard Lipowsky,et al. Network Brownian Motion: A New Method to Measure Vertex-Vertex Proximity and to Identify Communities and Subcommunities , 2004, International Conference on Computational Science.
[274] L. D. Costa. Hub-Based Community Finding , 2004, cond-mat/0405022.
[275] M. A. Muñoz,et al. Detecting network communities: a new systematic and efficient algorithm , 2004, cond-mat/0404652.
[276] 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.
[277] R. Guimerà,et al. Modularity from fluctuations in random graphs and complex networks. , 2004, Physical review. E, Statistical, nonlinear, and soft matter physics.
[278] Mark Newman,et al. Detecting community structure in networks , 2004 .
[279] D. Parisi,et al. Self-contained algorithms to detect communities in networks , 2004 .
[280] V. Latora,et al. Method to find community structures based on information centrality. , 2004, Physical review. E, Statistical, nonlinear, and soft matter physics.
[281] J. Reichardt,et al. Detecting fuzzy community structures in complex networks with a Potts model. , 2004, Physical review letters.
[282] Alessandro Vespignani,et al. Evolution and Structure of the Internet: A Statistical Physics Approach , 2004 .
[283] K. Sneppen,et al. Diffusion on complex networks: a way to probe their large-scale topological structures , 2003, cond-mat/0312476.
[284] A. Vespignani,et al. The architecture of complex weighted networks. , 2003, Proceedings of the National Academy of Sciences of the United States of America.
[285] M. Newman. Fast algorithm for detecting community structure in networks. , 2003, Physical review. E, Statistical, nonlinear, and soft matter physics.
[286] Claudio Castellano,et al. Defining and identifying communities in networks. , 2003, Proceedings of the National Academy of Sciences of the United States of America.
[287] M. Newman,et al. Finding and evaluating community structure in networks. , 2003, Physical review. E, Statistical, nonlinear, and soft matter physics.
[288] Dennis M. Wilkinson,et al. A method for finding communities of related genes , 2004, Proceedings of the National Academy of Sciences of the United States of America.
[289] Michael I. Jordan,et al. An Introduction to Variational Methods for Graphical Models , 1999, Machine Learning.
[290] David J. C. MacKay,et al. Information Theory, Inference, and Learning Algorithms , 2004, IEEE Transactions on Information Theory.
[291] Shengrui Wang,et al. A direct approach to graph clustering , 2004, Neural Networks and Computational Intelligence.
[292] Marina Meila,et al. An Experimental Comparison of Model-Based Clustering Methods , 2004, Machine Learning.
[293] D. Mason,et al. Compartments revealed in food-web structure , 2003, Nature.
[294] Fang Wu,et al. Finding communities in linear time: a physics approach , 2003, ArXiv.
[295] Vladimir Batagelj,et al. An O(m) Algorithm for Cores Decomposition of Networks , 2003, ArXiv.
[296] L. Mirny,et al. Protein complexes and functional modules in molecular networks , 2003, Proceedings of the National Academy of Sciences of the United States of America.
[297] René Peeters,et al. The maximum edge biclique problem is NP-complete , 2003, Discret. Appl. Math..
[298] Ulrik Brandes,et al. Experiments on Graph Clustering Algorithms , 2003, ESA.
[299] Padhraic Smyth,et al. Algorithms for estimating relative importance in networks , 2003, KDD '03.
[300] Eric R. Ziegel,et al. The Elements of Statistical Learning , 2003, Technometrics.
[301] Pablo M. Gleiser,et al. Community Structure in Jazz , 2003, Adv. Complex Syst..
[302] David Lusseau,et al. The emergent properties of a dolphin social network , 2003, Proceedings of the Royal Society of London. Series B: Biological Sciences.
[303] David R. Anderson,et al. Model selection and multimodel inference : a practical information-theoretic approach , 2003 .
[304] Adilson E Motter,et al. Heterogeneity in oscillator networks: are smaller worlds easier to synchronize? , 2003, Physical review letters.
[305] Abraham Kandel,et al. Graph Representations for Web Document Clustering , 2003, IbPRIA.
[306] Ravi Kumar,et al. On the Bursty Evolution of Blogspace , 2003, WWW '03.
[307] Christos Faloutsos,et al. Electricity Based External Similarity of Categorical Attributes , 2003, PAKDD.
[308] Mark E. J. Newman,et al. The Structure and Function of Complex Networks , 2003, SIAM Rev..
[309] Sergey N. Dorogovtsev,et al. Evolution of Networks: From Biological Nets to the Internet and WWW (Physics) , 2003 .
[310] K. Kaski,et al. Dynamics of market correlations: taxonomy and portfolio analysis. , 2003, Physical review. E, Statistical, nonlinear, and soft matter physics.
[311] Haijun Zhou. Network landscape from a Brownian particle's perspective. , 2003, Physical review. E, Statistical, nonlinear, and soft matter physics.
[312] Haijun Zhou. Distance, dissimilarity index, and network community structure. , 2003, Physical review. E, Statistical, nonlinear, and soft matter physics.
[313] D. R. White,et al. Structural cohesion and embeddedness: A hierarchical concept of social groups , 2003 .
[314] Alexander Rives,et al. Modular organization of cellular networks , 2003, Proceedings of the National Academy of Sciences of the United States of America.
[315] K. Sneppen,et al. Modularity and extreme edges of the internet. , 2002, Physical review letters.
[316] F. Lillo,et al. Topology of correlation-based minimal spanning trees in real and model markets. , 2002, Physical review. E, Statistical, nonlinear, and soft matter physics.
[317] A. Arenas,et al. Self-similar community structure in a network of human interactions. , 2002, Physical review. E, Statistical, nonlinear, and soft matter physics.
[318] Petter Holme,et al. Subnetwork hierarchies of biochemical pathways , 2002, Bioinform..
[319] A. Barabasi,et al. Hierarchical organization in complex networks. , 2002, Physical review. E, Statistical, nonlinear, and soft matter physics.
[320] Stefan Boettcher,et al. Optimization with Extremal Dynamics , 2000, Complex..
[321] E. Wenger,et al. Communities and technologies , 2003 .
[322] Matthew J. Beal. Variational algorithms for approximate Bayesian inference , 2003 .
[323] Masaru Kitsuregawa,et al. A Graph Based Approach to Extract a Neighborhood Customer Community for Collaborative Filtering , 2002, DNIS.
[324] S. Shen-Orr,et al. Network motifs: simple building blocks of complex networks. , 2002, Science.
[325] Refael Hassin,et al. Complexity of finding dense subgraphs , 2002, Discret. Appl. Math..
[326] A. Barabasi,et al. Hierarchical Organization of Modularity in Metabolic Networks , 2002, Science.
[327] K. Kaski,et al. Dynamic asset trees and portfolio analysis , 2002, cond-mat/0208131.
[328] M. Mézard,et al. The Cavity Method at Zero Temperature , 2002, cond-mat/0207121.
[329] H. Rieger,et al. Numerical study of the disorder-driven roughening transition in an elastic manifold in a periodic potential. , 2002, Physical review. E, Statistical, nonlinear, and soft matter physics.
[330] Dan Gusfield,et al. Partition-distance: A problem and class of perfect graphs arising in clustering , 2002, Inf. Process. Lett..
[331] C. Lee Giles,et al. Self-Organization and Identification of Web Communities , 2002, Computer.
[332] L. Pecora,et al. Synchronization in small-world systems. , 2001, Physical review letters.
[333] 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.
[334] Jean-Pierre Eckmann,et al. Curvature of co-links uncovers hidden thematic layers in the World Wide Web , 2001, Proceedings of the National Academy of Sciences of the United States of America.
[335] A. Middleton,et al. Three-dimensional random-field Ising magnet: Interfaces, scaling, and the nature of states , 2001, cond-mat/0107489.
[336] S. N. Dorogovtsev,et al. Evolution of networks , 2001, cond-mat/0106144.
[337] Jie Wu,et al. Small Worlds: The Dynamics of Networks between Order and Randomness , 2003 .
[338] Niththiyanathan Jeyaratnarajah. Cluster-Based Networks , 2002 .
[339] Jon M. Kleinberg,et al. An Impossibility Theorem for Clustering , 2002, NIPS.
[340] David Harel,et al. On Clustering Using Random Walks , 2001, FSTTCS.
[341] T. Snijders,et al. Estimation and Prediction for Stochastic Blockstructures , 2001 .
[342] H. Rieger,et al. Disorder-driven critical behavior of periodic elastic media in a crystal potential. , 2001, Physical review letters.
[343] Albert-László Barabási,et al. Statistical mechanics of complex networks , 2001, ArXiv.
[344] U. Brandes. A faster algorithm for betweenness centrality , 2001 .
[345] Uriel Feige,et al. The Dense k -Subgraph Problem , 2001, Algorithmica.
[346] V. Latora,et al. Efficient behavior of small-world networks. , 2001, Physical review letters.
[347] Charles E. Perkins,et al. Ad Hoc Networking , 2001 .
[348] Michael I. Jordan,et al. On Spectral Clustering: Analysis and an algorithm , 2001, NIPS.
[349] Alessandro Vespignani,et al. Epidemic spreading in scale-free networks. , 2000, Physical review letters.
[350] M. Newman,et al. The structure of scientific collaboration networks. , 2000, Proceedings of the National Academy of Sciences of the United States of America.
[351] Jürgen Kurths,et al. Synchronization - A Universal Concept in Nonlinear Sciences , 2001, Cambridge Nonlinear Science Series.
[352] Jianbo Shi,et al. A Random Walks View of Spectral Segmentation , 2001, AISTATS.
[353] Balachander Krishnamurthy,et al. On network-aware clustering of Web clients , 2000, SIGCOMM.
[354] C. Lee Giles,et al. Efficient identification of Web communities , 2000, KDD '00.
[355] A. Barabasi,et al. Error and attack tolerance of complex networks , 2000, Nature.
[356] Cohen,et al. Resilience of the internet to random breakdowns , 2000, Physical review letters.
[357] Gérard Govaert,et al. Assessing a Mixture Model for Clustering with the Integrated Completed Likelihood , 2000, IEEE Trans. Pattern Anal. Mach. Intell..
[358] S. Dongen. Graph clustering by flow simulation , 2000 .
[359] M. Ashburner,et al. Gene Ontology: tool for the unification of biology , 2000, Nature Genetics.
[360] Naftali Tishby,et al. The information bottleneck method , 2000, ArXiv.
[361] Neo D. Martinez,et al. Simple rules yield complex food webs , 2000, Nature.
[362] R. Mantegna,et al. Taxonomy of stock market indices , 2000, Physical review. E, Statistical physics, plasmas, fluids, and related interdisciplinary topics.
[363] Jack Dongarra,et al. Templates for the Solution of Algebraic Eigenvalue Problems , 2000, Software, environments, tools.
[364] S. Dongen. Performance criteria for graph clustering and Markov cluster experiments , 2000 .
[365] D. Watts,et al. Small Worlds: The Dynamics of Networks between Order and Randomness , 2001 .
[366] Rosario N. Mantegna,et al. Book Review: An Introduction to Econophysics, Correlations, and Complexity in Finance, N. Rosario, H. Mantegna, and H. E. Stanley, Cambridge University Press, Cambridge, 2000. , 2000 .
[367] Albert,et al. Emergence of scaling in random networks , 1999, Science.
[368] Richard M. Karp,et al. Algorithms for graph partitioning on the planted partition model , 1999, Random Struct. Algorithms.
[369] Albert-László Barabási,et al. Internet: Diameter of the World-Wide Web , 1999, Nature.
[370] Gerard T. Barkema,et al. Monte Carlo Methods in Statistical Physics , 1999 .
[371] Thorsten von Eicken,et al. 技術解説 IEEE Computer , 1999 .
[372] Hideo Matsuda,et al. Classifying Molecular Sequences Using a Linkage Graph With Their Pairwise Similarities , 1999, Theor. Comput. Sci..
[373] R. Mantegna. Hierarchical structure in financial markets , 1998, cond-mat/9802256.
[374] Vladimir Batagelj,et al. Generalized blockmodeling , 2005, Structural analysis in the social sciences.
[375] P. Pardalos,et al. Handbook of Combinatorial Optimization , 1998 .
[376] Emden R. Gansner,et al. Using automatic clustering to produce high-level system organizations of source code , 1998, Proceedings. 6th International Workshop on Program Comprehension. IWPC'98 (Cat. No.98TB100242).
[377] Duncan J. Watts,et al. Collective dynamics of ‘small-world’ networks , 1998, Nature.
[378] C. Lee Giles,et al. CiteSeer: an automatic citation indexing system , 1998, DL '98.
[379] Sergey Brin,et al. The Anatomy of a Large-Scale Hypertextual Web Search Engine , 1998, Comput. Networks.
[380] I. H. Witten,et al. Digital Libraries 98 : the third ACM Conference on Digital Libraries, June 23-26, 1998, Pittsburgh, PA, , 1998 .
[381] Jitendra Malik,et al. Normalized cuts and image segmentation , 1997, Proceedings of IEEE Computer Society Conference on Computer Vision and Pattern Recognition.
[382] Alex Pothen,et al. Graph Partitioning Algorithms with Applications to Scientific Computing , 1997 .
[383] Huaiyu Zhu. On Information and Sufficiency , 1997 .
[384] T. Snijders,et al. Estimation and Prediction for Stochastic Blockmodels for Graphs with Latent Block Structure , 1997 .
[385] Blatt,et al. Superparamagnetic clustering of data. , 1998, Physical review letters.
[386] Fan Chung,et al. Spectral Graph Theory , 1996 .
[387] Shang-Hua Teng,et al. Spectral partitioning works: planar graphs and finite element meshes , 1996, Proceedings of 37th Conference on Foundations of Computer Science.
[388] Boris Mirkin,et al. Mathematical Classification and Clustering , 1996 .
[389] A. Mookerjee. The Spin Glass , 1996 .
[390] Bruce A. Reed,et al. A Critical Point for Random Graphs with a Given Degree Sequence , 1995, Random Struct. Algorithms.
[391] S. McDonough. Grooming. , 1995, The Veterinary clinics of North America. Small animal practice.
[392] S. Borgatti,et al. Regular equivalence: general theory , 1994 .
[393] H. V. Jagadish,et al. Algorithms for Searching Massive Graphs , 1994, IEEE Trans. Knowl. Data Eng..
[394] Martine D. F. Schlag,et al. Spectral K-Way Ratio-Cut Partitioning and Clustering , 1993, 30th ACM/IEEE Design Automation Conference.
[395] M. Randic,et al. Resistance distance , 1993 .
[396] Ravindra K. Ahuja,et al. Network Flows: Theory, Algorithms, and Applications , 1993 .
[397] Andrew B. Kahng,et al. New spectral methods for ratio cut partitioning and clustering , 1991, IEEE Trans. Comput. Aided Des. Integr. Circuits Syst..
[398] John Scott. Social Network Analysis , 1988 .
[399] V. N. Bogaevski,et al. Matrix Perturbation Theory , 1991 .
[400] HERBERT A. SIMON,et al. The Architecture of Complexity , 1991 .
[401] S. Borgatti,et al. LS sets, lambda sets and other cohesive subsets , 1990 .
[402] Farhad Shahrokhi,et al. Sparsest cuts and bottlenecks in graphs , 1990, Discret. Appl. Math..
[403] Chung-Kuan Cheng,et al. Towards efficient hierarchical designs by ratio cut partitioning , 1989, 1989 IEEE International Conference on Computer-Aided Design. Digest of Technical Papers.
[404] Prabhakar Raghavan,et al. The electrical resistance of a graph captures its commute and cover times , 1989, STOC '89.
[405] G. Kedem,et al. An algorithm for quadrisection and its application to standard cell placement , 1988 .
[406] John Scott. What is social network analysis , 2010 .
[407] P. Bonacich. Power and Centrality: A Family of Measures , 1987, American Journal of Sociology.
[408] M. Mézard,et al. Spin Glass Theory and Beyond , 1987 .
[409] Carsten Peterson,et al. A Mean Field Theory Learning Algorithm for Neural Networks , 1987, Complex Syst..
[410] Andrew V. Goldberg,et al. A new approach to the maximum flow problem , 1986, STOC '86.
[411] P. Anderson,et al. Application of statistical mechanics to NP-complete problems in combinatorial optimisation , 1986 .
[412] Fred W. Glover,et al. Future paths for integer programming and links to artificial intelligence , 1986, Comput. Oper. Res..
[413] Yoshiki Kuramoto,et al. Chemical Oscillations, Waves, and Turbulence , 1984, Springer Series in Synergetics.
[414] Emil Grosswald,et al. The Theory of Partitions , 1984 .
[415] Ian T. Jolliffe,et al. A Method for Comparing Two Hierarchical Clusterings: Comment , 1983 .
[416] Stephen B. Seidman,et al. Network structure and minimum degree , 1983 .
[417] C. Mallows,et al. A Method for Comparing Two Hierarchical Clusterings , 1983 .
[418] Kathryn B. Laskey,et al. Stochastic blockmodels: First steps , 1983 .
[419] K. Reitz,et al. Graph and Semigroup Homomorphisms on Networks of Relations , 1983 .
[420] C. D. Gelatt,et al. Optimization by Simulated Annealing , 1983, Science.
[421] G. Pólya,et al. Problems and theorems in analysis , 1983 .
[422] S. P. Lloyd,et al. Least squares quantization in PCM , 1982, IEEE Trans. Inf. Theory.
[423] F. Y. Wu. The Potts model , 1982 .
[424] E. Barnes. An algorithm for partitioning the nodes of a graph , 1981, 1981 20th IEEE Conference on Decision and Control including the Symposium on Adaptive Processes.
[425] James C. Bezdek,et al. Pattern Recognition with Fuzzy Objective Function Algorithms , 1981, Advanced Applications in Pattern Recognition.
[426] S. Fienberg,et al. Categorical Data Analysis of Single Sociometric Relations , 1981 .
[427] S. Pimm,et al. The structure of food webs. , 1979, Theoretical population biology.
[428] L. Lovász. Combinatorial problems and exercises , 1979 .
[429] J. Rissanen,et al. Modeling By Shortest Data Description* , 1978, Autom..
[430] G. Schwarz. Estimating the Dimension of a Model , 1978 .
[431] Stephen B. Seidman,et al. A graph‐theoretic generalization of the clique concept* , 1978 .
[432] David S. Johnson,et al. Computers and Intractability: A Guide to the Theory of NP-Completeness , 1978 .
[433] R. J. Mokken,et al. Cliques, clubs and clans , 1979 .
[434] W. Zachary,et al. An Information Flow Model for Conflict and Fission in Small Groups , 1977, Journal of Anthropological Research.
[435] D. Rubin,et al. Maximum likelihood from incomplete data via the EM - algorithm plus discussions on the paper , 1977 .
[436] Leonard M. Freeman,et al. A set of measures of centrality based upon betweenness , 1977 .
[437] Ronald S. Burt,et al. Positions in Networks , 1976 .
[438] Derek de Solla Price,et al. A general theory of bibliometric and other cumulative advantage processes , 1976, J. Am. Soc. Inf. Sci..
[439] S. Kirkpatrick,et al. Solvable Model of a Spin-Glass , 1975 .
[440] M. Fiedler. A property of eigenvectors of nonnegative symmetric matrices and its application to graph theory , 1975 .
[441] John H. Holland,et al. Adaptation in Natural and Artificial Systems: An Introductory Analysis with Applications to Biology, Control, and Artificial Intelligence , 1992 .
[442] H. Akaike. A new look at the statistical model identification , 1974 .
[443] Dennis V. Lindley,et al. An Introduction to Bayesian Inference and Decision , 1974 .
[444] A. Hoffman,et al. Lower bounds for the partitioning of graphs , 1973 .
[445] C. Bron,et al. Algorithm 457: finding all cliques of an undirected graph , 1973 .
[446] R. Alba. A graph‐theoretic definition of a sociometric clique† , 1973 .
[447] Mark S. Granovetter. The Strength of Weak Ties , 1973, American Journal of Sociology.
[448] M. Fiedler. Algebraic connectivity of graphs , 1973 .
[449] J. C. Dunn,et al. A Fuzzy Relative of the ISODATA Process and Its Use in Detecting Compact Well-Separated Clusters , 1973 .
[450] Coenraad Bron,et al. Finding all cliques of an undirected graph , 1973 .
[451] P. Bonacich. Factoring and weighting approaches to status scores and clique identification , 1972 .
[452] R. L. Winkler. An Introduction to Bayesian Inference and Decision , 1972 .
[453] William M. Rand,et al. Objective Criteria for the Evaluation of Clustering Methods , 1971 .
[454] J. Anthonisse. The rush in a directed graph , 1971 .
[455] Brian W. Kernighan,et al. An efficient heuristic procedure for partitioning graphs , 1970, Bell Syst. Tech. J..
[456] Stanley Milgram,et al. An Experimental Study of the Small World Problem , 1969 .
[457] F. Luccio,et al. On the Decomposition of Networks in Minimally Interconnected Subnetworks , 1969 .
[458] H. L. Le Roy,et al. Proceedings of the Fifth Berkeley Symposium on Mathematical Statistics and Probability; Vol. IV , 1969 .
[459] C. S. Wallace,et al. An Information Measure for Classification , 1968, Comput. J..
[460] Patrick Rivett,et al. Introduction to operations research , 1968 .
[461] R. Faure,et al. Introduction to operations research , 1968 .
[462] E. Sunderland. Human Groups , 1967, Nature.
[463] Sharon L. Milgram,et al. The Small World Problem , 1967 .
[464] J. MacQueen. Some methods for classification and analysis of multivariate observations , 1967 .
[465] C. Parrack. Cliques , 1966, The Mathematical Gazette.
[466] E. A. Maxwell,et al. Introduction to Mathematical Sociology , 1965 .
[467] D J PRICE,et al. NETWORKS OF SCIENTIFIC PAPERS. , 1965, Science.
[468] J. H. Ward. Hierarchical Grouping to Optimize an Objective Function , 1963 .
[469] L. Goddard. Information Theory , 1962, Nature.
[470] Robert G. Gallager,et al. Low-density parity-check codes , 1962, IRE Trans. Inf. Theory.
[471] Peter Elias,et al. A note on the maximum flow through a network , 1956, IRE Trans. Inf. Theory.
[472] D. R. Fulkerson,et al. Maximal Flow Through a Network , 1956, Canadian Journal of Mathematics.
[473] H. Simon,et al. ON A CLASS OF SKEW DISTRIBUTION FUNCTIONS , 1955 .
[474] R. Weiss,et al. A Method for the Analysis of the Structure of Complex Organizations , 1955 .
[475] P. Bohannan. Cultural Anthropology , 2020, Nature.
[476] David A. Huffman,et al. A method for the construction of minimum-redundancy codes , 1952, Proceedings of the IRE.
[477] A. Rapoport,et al. Connectivity of random nets , 1951 .
[478] C. Lanczos. An iteration method for the solution of the eigenvalue problem of linear differential and integral operators , 1950 .
[479] R. Luce,et al. Connectivity and generalized cliques in sociometric group structure , 1950, Psychometrika.
[480] R. Luce,et al. A method of matrix analysis of group structure , 1949, Psychometrika.
[481] Stuart A. Rice,et al. The Identification of Blocs in Small Political Bodies , 1927, American Political Science Review.
[482] K. Pearson,et al. Biometrika , 1902, The American Naturalist.
[483] Physics Reports , 2022 .