Data Mining in Complex Networks: Missing Link Prediction and Fuzzy Communities
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[1] M. Newman,et al. Random graphs with arbitrary degree distributions and their applications. , 2000, Physical review. E, Statistical, nonlinear, and soft matter physics.
[2] W. K. Hastings,et al. Monte Carlo Sampling Methods Using Markov Chains and Their Applications , 1970 .
[3] Joshua B. Tenenbaum,et al. The Large-Scale Structure of Semantic Networks: Statistical Analyses and a Model of Semantic Growth , 2001, Cogn. Sci..
[4] G. Caldarelli,et al. Detecting communities in large networks , 2004, cond-mat/0402499.
[5] Albert-László Barabási,et al. Statistical mechanics of complex networks , 2001, ArXiv.
[6] Duncan J. Watts,et al. Six Degrees: The Science of a Connected Age , 2003 .
[7] M. E. Galassi,et al. GNU SCIENTI C LIBRARY REFERENCE MANUAL , 2005 .
[8] M. M. Kessler. Bibliographic coupling between scientific papers , 1963 .
[9] Christopher R. Myers,et al. Software systems as complex networks: structure, function, and evolvability of software collaboration graphs , 2003, Physical review. E, Statistical, nonlinear, and soft matter physics.
[10] Terence Tao. Szemerédi's regularity lemma revisited , 2006, Contributions Discret. Math..
[11] S. Brenner,et al. The structure of the nervous system of the nematode Caenorhabditis elegans. , 1986, Philosophical transactions of the Royal Society of London. Series B, Biological sciences.
[12] B Jouve,et al. A mathematical approach to the connectivity between the cortical visual areas of the macaque monkey. , 1998, Cerebral cortex.
[13] Jon M. Kleinberg,et al. The link-prediction problem for social networks , 2007, J. Assoc. Inf. Sci. Technol..
[14] H. Simon,et al. ON A CLASS OF SKEW DISTRIBUTION FUNCTIONS , 1955 .
[15] P. Jaccard,et al. Etude comparative de la distribution florale dans une portion des Alpes et des Jura , 1901 .
[16] T. Nepusz,et al. Likelihood-based Clustering of Directed Graphs , 2007, 2007 International Symposium on Computational Intelligence and Intelligent Informatics.
[17] B. Bollobás. The evolution of random graphs , 1984 .
[18] D. J. Felleman,et al. Distributed hierarchical processing in the primate cerebral cortex. , 1991, Cerebral cortex.
[19] R. Guimerà,et al. Functional cartography of complex metabolic networks , 2005, Nature.
[20] Leo Katz,et al. A new status index derived from sociometric analysis , 1953 .
[21] M. Newman. 1 Who is the best connected scientist ? A study of scientific coauthorship networks , 2004 .
[22] P. ERDbS. ON THE STRENGTH OF CONNECTEDNESS OF A RANDOM GRAPH , 2001 .
[23] Mu Zhu,et al. Automatic dimensionality selection from the scree plot via the use of profile likelihood , 2006, Comput. Stat. Data Anal..
[24] Jorge Nocedal,et al. Algorithm 778: L-BFGS-B: Fortran subroutines for large-scale bound-constrained optimization , 1997, TOMS.
[25] S. Zeki,et al. The position and topography of the human colour centre as revealed by functional magnetic resonance imaging. , 1997, Brain : a journal of neurology.
[26] F. Chung. Laplacians and the Cheeger Inequality for Directed Graphs , 2005 .
[27] D. V. van Essen,et al. Corticocortical connections of visual, sensorimotor, and multimodal processing areas in the parietal lobe of the macaque monkey , 2000, The Journal of comparative neurology.
[28] Matthieu Latapy,et al. Computing Communities in Large Networks Using Random Walks , 2004, J. Graph Algorithms Appl..
[29] E. Ziv,et al. Information-theoretic approach to network modularity. , 2004, Physical review. E, Statistical, nonlinear, and soft matter physics.
[30] Bruce A. Reed,et al. A Critical Point for Random Graphs with a Given Degree Sequence , 1995, Random Struct. Algorithms.
[31] Anitha Pasupathy,et al. Neural basis of shape representation in the primate brain. , 2006, Progress in brain research.
[32] Sankar K. Pal,et al. Fuzzy models for pattern recognition : methods that search for structures in data , 1992 .
[33] U. Feige,et al. Spectral Graph Theory , 2015 .
[34] Alan M. Frieze,et al. Clustering Large Graphs via the Singular Value Decomposition , 2004, Machine Learning.
[35] M. Simonovits,et al. Szemeredi''s Regularity Lemma and its applications in graph theory , 1995 .
[36] K. Kaski,et al. Clustering and information in correlation based financial networks , 2003, cond-mat/0312682.
[37] P. Erdos,et al. On the strength of connectedness of a random graph , 1964 .
[38] Donald Geman,et al. Stochastic Relaxation, Gibbs Distributions, and the Bayesian Restoration of Images , 1984, IEEE Transactions on Pattern Analysis and Machine Intelligence.
[39] S. Zeki,et al. The architecture of the colour centre in the human visual brain: new results and a review * , 2000, The European journal of neuroscience.
[40] L. Cronbach. Coefficient alpha and the internal structure of tests , 1951 .
[41] J. C. Dunn,et al. A Fuzzy Relative of the ISODATA Process and Its Use in Detecting Compact Well-Separated Clusters , 1973 .
[42] Cristopher Moore,et al. Structural Inference of Hierarchies in Networks , 2006, SNA@ICML.
[43] Steven B. Andrews,et al. Structural Holes: The Social Structure of Competition , 1995, The SAGE Encyclopedia of Research Design.
[44] Charles M. Grinstead,et al. Introduction to probability , 1999, Statistics for the Behavioural Sciences.
[45] A. Barabasi,et al. Lethality and centrality in protein networks , 2001, Nature.
[46] László Kocsis,et al. Prediction of the main cortical areas and connections involved in the tactile function of the visual cortex by network analysis , 2006, The European journal of neuroscience.
[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] I. D. Hill,et al. An Efficient and Portable Pseudo‐Random Number Generator , 1982 .
[50] D. Rubin,et al. Maximum likelihood from incomplete data via the EM - algorithm plus discussions on the paper , 1977 .
[51] Lada A. Adamic,et al. Friends and neighbors on the Web , 2003, Soc. Networks.
[52] Leon Danon,et al. The effect of size heterogeneity on community identification in complex networks , 2006, physics/0601144.
[53] Vojtech Rödl,et al. The Algorithmic Aspects of the Regularity Lemma , 1994, J. Algorithms.
[54] D. V. Essen,et al. Surface-Based and Probabilistic Atlases of Primate Cerebral Cortex , 2007, Neuron.
[55] Jennifer Widom,et al. Scaling personalized web search , 2003, WWW '03.
[56] John Scott. What is social network analysis , 2010 .
[57] Albert-László Barabási,et al. Evolution of Networks: From Biological Nets to the Internet and WWW , 2004 .
[58] H. H. Rosenbrock,et al. An Automatic Method for Finding the Greatest or Least Value of a Function , 1960, Comput. J..
[59] Yaghout Nourani,et al. A comparison of simulated annealing cooling strategies , 1998 .
[60] K. Schittkowski,et al. NONLINEAR PROGRAMMING , 2022 .
[61] R. Solé,et al. Evolving protein interaction networks through gene duplication. , 2003, Journal of Theoretical Biology.
[62] Valentin I. Spitkovsky,et al. A dictionary based approach for gene annotation , 1999, J. Comput. Biol..
[63] T. Nepusz,et al. Fuzzy communities and the concept of bridgeness in complex networks. , 2007, Physical review. E, Statistical, nonlinear, and soft matter physics.
[64] John N. Tsitsiklis,et al. Introduction to Probability , 2002 .
[65] Shihua Zhang,et al. Identification of overlapping community structure in complex networks using fuzzy c-means clustering , 2007 .
[66] S. Dongen. A stochastic uncoupling process for graphs , 2000 .
[67] D. Marquardt. An Algorithm for Least-Squares Estimation of Nonlinear Parameters , 1963 .
[68] András A. Benczúr,et al. Telephone Call Network Data Mining: A Survey with Experiments , 2008 .
[69] Christos Faloutsos,et al. Graphs over time: densification laws, shrinking diameters and possible explanations , 2005, KDD '05.
[70] Gene H. Golub,et al. Calculating the singular values and pseudo-inverse of a matrix , 2007, Milestones in Matrix Computation.
[71] Tamás Nepusz,et al. Measuring tie-strength in virtual social networks , 2006 .
[72] 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.
[73] Jitendra Malik,et al. Normalized cuts and image segmentation , 1997, Proceedings of IEEE Computer Society Conference on Computer Vision and Pattern Recognition.
[74] W. Zachary,et al. An Information Flow Model for Conflict and Fission in Small Groups , 1977, Journal of Anthropological Research.
[75] Prof. Dr. Dr. Valentino Braitenberg,et al. Cortex: Statistics and Geometry of Neuronal Connectivity , 1998, Springer Berlin Heidelberg.
[76] Dimitri P. Bertsekas,et al. Nonlinear Programming , 1997 .
[77] Stefan Bornholdt,et al. Detecting fuzzy community structures in complex networks with a Potts model. , 2004, Physical review letters.
[78] Mark E. J. Newman,et al. Structure and Dynamics of Networks , 2009 .
[79] M E J Newman,et al. Fast algorithm for detecting community structure in networks. , 2003, Physical review. E, Statistical, nonlinear, and soft matter physics.
[80] T. Nepusz,et al. Maximum Likelihood Methods for Data Mining in Datasets Represented by Graphs , 2007, 2007 5th International Symposium on Intelligent Systems and Informatics.
[81] Naftali Tishby,et al. The information bottleneck method , 2000, ArXiv.
[82] Leon Danon,et al. Comparing community structure identification , 2005, cond-mat/0505245.
[83] D J PRICE,et al. NETWORKS OF SCIENTIFIC PAPERS. , 1965, Science.
[84] Albert-László Barabási,et al. Linked - how everything is connected to everything else and what it means for business, science, and everyday life , 2003 .
[85] R. Fisher,et al. On the Mathematical Foundations of Theoretical Statistics , 1922 .
[86] Duncan J. Watts,et al. Collective dynamics of ‘small-world’ networks , 1998, Nature.
[87] Albert,et al. Emergence of scaling in random networks , 1999, Science.
[88] A. Rapoport,et al. Connectivity of random nets , 1951 .
[89] E A Leicht,et al. Community structure in directed networks. , 2007, Physical review letters.
[90] Takuji Nishimura,et al. Mersenne twister: a 623-dimensionally equidistributed uniform pseudo-random number generator , 1998, TOMC.
[91] D. Shanno. Conditioning of Quasi-Newton Methods for Function Minimization , 1970 .
[92] S. N. Dorogovtsev,et al. Structure of Growing Networks: Exact Solution of the Barabasi--Albert's Model , 2000, cond-mat/0004434.
[93] Kenneth Levenberg. A METHOD FOR THE SOLUTION OF CERTAIN NON – LINEAR PROBLEMS IN LEAST SQUARES , 1944 .
[94] L. Devroye. Non-Uniform Random Variate Generation , 1986 .
[95] Gábor E. Tusnády,et al. Reconstructing Cortical Networks: Case of Directed Graphs with High Level of Reciprocity , 2008 .
[96] Sharon L. Milgram,et al. The Small World Problem , 1967 .
[97] Charles R. Johnson,et al. Matrix analysis , 1985, Statistical Inference for Engineers and Data Scientists.
[98] Sergey Brin,et al. The Anatomy of a Large-Scale Hypertextual Web Search Engine , 1998, Comput. Networks.
[99] Jennifer Widom,et al. SimRank: a measure of structural-context similarity , 2002, KDD.
[100] Derek de Solla Price,et al. A general theory of bibliometric and other cumulative advantage processes , 1976, J. Am. Soc. Inf. Sci..
[101] S. N. Dorogovtsev,et al. Structure of growing networks with preferential linking. , 2000, Physical review letters.
[102] 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.
[103] B. Matthews. Comparison of the predicted and observed secondary structure of T4 phage lysozyme. , 1975, Biochimica et biophysica acta.
[104] O. Sporns,et al. Organization, development and function of complex brain networks , 2004, Trends in Cognitive Sciences.
[105] Eli Upfal,et al. Stochastic models for the Web graph , 2000, Proceedings 41st Annual Symposium on Foundations of Computer Science.
[106] Gábor Csárdi,et al. The igraph software package for complex network research , 2006 .
[107] Alan M. Frieze,et al. Random graphs , 2006, SODA '06.
[108] Michael Mitzenmacher,et al. A Brief History of Generative Models for Power Law and Lognormal Distributions , 2004, Internet Math..
[109] Dániel Fogaras. Where to Start Browsing the Web? , 2003, IICS.
[110] Geoffrey E. Hinton,et al. A View of the Em Algorithm that Justifies Incremental, Sparse, and other Variants , 1998, Learning in Graphical Models.
[111] Michalis Faloutsos,et al. On power-law relationships of the Internet topology , 1999, SIGCOMM '99.
[112] Mark Buchanan,et al. Nexus: Small Worlds and the Groundbreaking Science of Networks , 2002 .
[113] M. Newman,et al. Finding community structure in networks using the eigenvectors of matrices. , 2006, Physical review. E, Statistical, nonlinear, and soft matter physics.
[114] Ana L. N. Fred,et al. Robust data clustering , 2003, 2003 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, 2003. Proceedings..
[115] Enrique H. Ruspini,et al. Numerical methods for fuzzy clustering , 1970, Inf. Sci..
[116] P. Erdos,et al. On the evolution of random graphs , 1984 .
[117] Ravi Montenegro,et al. Mathematical Aspects of Mixing Times in Markov Chains , 2006, Found. Trends Theor. Comput. Sci..
[118] Bill Cheswick,et al. Mapping and Visualizing the Internet , 2000, USENIX Annual Technical Conference, General Track.
[119] Henry G. Small,et al. Co-citation in the scientific literature: A new measure of the relationship between two documents , 1973, J. Am. Soc. Inf. Sci..
[120] R. Albert,et al. The large-scale organization of metabolic networks , 2000, Nature.
[121] M. Newman,et al. Finding community structure in very large networks. , 2004, Physical review. E, Statistical, nonlinear, and soft matter physics.
[122] James C. Bezdek,et al. Pattern Recognition with Fuzzy Objective Function Algorithms , 1981, Advanced Applications in Pattern Recognition.
[123] H. Akaike. A new look at the statistical model identification , 1974 .
[124] Huaiyu Zhu. On Information and Sufficiency , 1997 .
[125] Karl J. Friston,et al. The colour centre in the cerebral cortex of man , 1989, Nature.
[126] E. Szemerédi. Regular Partitions of Graphs , 1975 .
[127] Casper Goffman,et al. And What is Your Erdös Number , 1969 .
[128] Luciano da Fontoura Costa,et al. Predicting the connectivity of primate cortical networks from topological and spatial node properties , 2007, BMC Systems Biology.