Leveraging social media networks for classification
暂无分享,去创建一个
[1] A. Moore,et al. Dynamic social network analysis using latent space models , 2005, SKDD.
[2] Donald Geman,et al. Stochastic Relaxation, Gibbs Distributions, and the Bayesian Restoration of Images , 1984, IEEE Transactions on Pattern Analysis and Machine Intelligence.
[3] Lise Getoor,et al. Link-Based Classification , 2003, Encyclopedia of Machine Learning and Data Mining.
[4] Ravi Kumar,et al. Structure and evolution of online social networks , 2006, KDD '06.
[5] Xiaojin Zhu,et al. --1 CONTENTS , 2006 .
[6] Jure Leskovec,et al. Empirical comparison of algorithms for network community detection , 2010, WWW '10.
[7] S. Fortunato,et al. Resolution limit in community detection , 2006, Proceedings of the National Academy of Sciences.
[8] Gang Chen,et al. Semi-supervised Multi-label Learning by Solving a Sylvester Equation , 2008, SDM.
[9] Foster J. Provost,et al. Classification in Networked Data: a Toolkit and a Univariate Case Study , 2007, J. Mach. Learn. Res..
[10] Mike Thelwall,et al. Homophily in MySpace , 2009, J. Assoc. Inf. Sci. Technol..
[11] Ulrike von Luxburg,et al. A tutorial on spectral clustering , 2007, Stat. Comput..
[12] Huan Liu,et al. Community Detection and Mining in Social Media , 2010, Community Detection and Mining in Social Media.
[13] Ben Taskar,et al. Discriminative Probabilistic Models for Relational Data , 2002, UAI.
[14] Chris H. Q. Ding,et al. Spectral Relaxation for K-means Clustering , 2001, NIPS.
[15] Hao Wang,et al. PSVM : Parallelizing Support Vector Machines on Distributed Computers , 2007 .
[16] Risi Kondor,et al. Diffusion kernels on graphs and other discrete structures , 2002, ICML 2002.
[17] John D. Lafferty,et al. Diffusion Kernels on Graphs and Other Discrete Input Spaces , 2002, ICML.
[18] 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.
[19] M. Newman,et al. Finding community structure in networks using the eigenvectors of matrices. , 2006, Physical review. E, Statistical, nonlinear, and soft matter physics.
[20] Jure Leskovec,et al. Statistical properties of community structure in large social and information networks , 2008, WWW.
[21] Stanley Milgram,et al. An Experimental Study of the Small World Problem , 1969 .
[22] Gene H. Golub,et al. Matrix computations (3rd ed.) , 1996 .
[23] Ben Taskar,et al. Introduction to statistical relational learning , 2007 .
[24] Bart Selman,et al. Natural communities in large linked networks , 2003, KDD '03.
[25] T. Snijders,et al. Estimation and Prediction for Stochastic Blockstructures , 2001 .
[26] Ben Taskar,et al. Probabilistic Classification and Clustering in Relational Data , 2001, IJCAI.
[27] B. Wellman. The School Child’s Choice of Companions , 1926 .
[28] Mahdi Shafiei,et al. Mixed-Membership Stochastic Block-Models for Transactional Data , 2009 .
[29] Edoardo M. Airoldi,et al. Stochastic Block Models of Mixed Membership , 2006 .
[30] Charles Elkan,et al. Predicting labels for dyadic data , 2010, Data Mining and Knowledge Discovery.
[31] Huan Liu,et al. Scalable learning of collective behavior based on sparse social dimensions , 2009, CIKM.
[32] Grigorios Tsoumakas,et al. Multi-Label Classification: An Overview , 2007, Int. J. Data Warehous. Min..
[33] William Stafford Noble,et al. Learning kernels from biological networks by maximizing entropy , 2004, ISMB/ECCB.
[34] Peter D. Hoff,et al. Latent Space Approaches to Social Network Analysis , 2002 .
[35] A. Raftery,et al. Model‐based clustering for social networks , 2007 .
[36] Gene H. Golub,et al. Matrix computations , 1983 .
[37] Yi Liu,et al. Semi-supervised Multi-label Learning by Constrained Non-negative Matrix Factorization , 2006, AAAI.
[38] Volker Tresp,et al. Nonparametric Relational Learning for Social Network Analysis , 2008 .
[39] Lise Getoor,et al. Collective Classification in Network Data , 2008, AI Mag..
[40] Saso Dzeroski,et al. Proceedings of the 4th international workshop on Multi-relational mining , 2005 .
[41] Stanley Wasserman,et al. Social Network Analysis: Methods and Applications , 1994, Structural analysis in the social sciences.
[42] M. McPherson,et al. Birds of a Feather: Homophily in Social Networks , 2001 .
[43] Huan Liu,et al. Relational learning via latent social dimensions , 2009, KDD.
[44] Jitendra Malik,et al. Normalized Cuts and Image Segmentation , 2000, IEEE Trans. Pattern Anal. Mach. Intell..
[45] Chih-Jen Lin,et al. A Study on Threshold Selection for Multi-label Classification , 2007 .
[46] Christos Faloutsos,et al. Graph mining: Laws, generators, and algorithms , 2006, CSUR.
[47] C. Lee Giles,et al. Advances in Social Network Mining and Analysis, Second International Workshop, SNAKDD 2008, Las Vegas, NV, USA, August 24-27, 2008, Revised Selected Papers , 2010, SNAKDD.
[48] Edward Y. Chang,et al. Parallelizing Support Vector Machines on Distributed Computers , 2007, NIPS.
[49] Edward Y. Chang,et al. Parallel Spectral Clustering in Distributed Systems , 2011, IEEE Transactions on Pattern Analysis and Machine Intelligence.
[50] Christos Faloutsos,et al. Using ghost edges for classification in sparsely labeled networks , 2008, KDD.
[51] Ben Taskar,et al. Introduction to Statistical Relational Learning (Adaptive Computation and Machine Learning) , 2007 .
[52] Stuart German,et al. Stochastic relaxation, Gibbs distributions, and the Bayesian restoration of images , 1988 .
[53] Lei Tang,et al. Large scale multi-label classification via metalabeler , 2009, WWW '09.
[54] Igor Durdanovic,et al. Parallel Support Vector Machines: The Cascade SVM , 2004, NIPS.
[55] Foster Provost,et al. A Simple Relational Classifier , 2003 .
[56] Donald Geman,et al. Stochastic relaxation, Gibbs distributions, and the Bayesian restoration of images , 1984 .
[57] Piotr Indyk,et al. Enhanced hypertext categorization using hyperlinks , 1998, SIGMOD '98.
[58] Zoubin Ghahramani,et al. Combining active learning and semi-supervised learning using Gaussian fields and harmonic functions , 2003, ICML 2003.
[59] Bernhard Schölkopf,et al. Learning with Local and Global Consistency , 2003, NIPS.
[60] Judith S. Donath,et al. Homophily in online dating: when do you like someone like yourself? , 2005, CHI Extended Abstracts.
[61] Jennifer Neville,et al. Why collective inference improves relational classification , 2004, KDD.