Communities validity: methodical evaluation of community mining algorithms
暂无分享,去创建一个
[1] V. Batagelj,et al. Exploratory Social Network Analysis with Pajek: Revised and Expanded Edition for Updated Software , 2018 .
[2] M. Cugmas,et al. On comparing partitions , 2015 .
[3] Tetsuya Yoshida. Weighted line graphs for overlapping community discovery , 2013, Social Network Analysis and Mining.
[4] Guy Melançon,et al. Model for generating artificial social networks having community structures with small-world and scale-free properties , 2013, Social Network Analysis and Mining.
[5] Ricardo J. G. B. Campello,et al. Relative Validity Criteria for Community Mining Algorithms , 2012, 2012 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining.
[6] Santo Fortunato,et al. Consensus clustering in complex networks , 2012, Scientific Reports.
[7] Ignacio Marín,et al. Closed benchmarks for network community structure characterization , 2012, Physical review. E, Statistical, nonlinear, and soft matter physics.
[8] Bradley S. Rees,et al. Overlapping community detection using a community optimized graph swarm , 2012, Social Network Analysis and Mining.
[9] Young-Rae Cho,et al. Entropy-Based Graph Clustering: Application to Biological and Social Networks , 2011, 2011 IEEE 11th International Conference on Data Mining.
[10] Osmar R. Zaïane,et al. A Diffusion of Innovation-Based Closeness Measure for Network Associations , 2011, 2011 IEEE 11th International Conference on Data Mining Workshops.
[11] Malay K. Pakhira,et al. Computing approximate value of the pbm index for counting number of clusters using genetic algorithm , 2011, 2011 International Conference on Recent Trends in Information Systems.
[12] Hocine Cherifi,et al. Qualitative Comparison of Community Detection Algorithms , 2011, DICTAP.
[13] Steve Gregory. Fuzzy overlapping communities in networks , 2011 .
[14] Günce Keziban Orman,et al. The Effect of Network Realism on Community Detection Algorithms , 2010, 2010 International Conference on Advances in Social Networks Analysis and Mining.
[15] Ricardo J. G. B. Campello,et al. Relative clustering validity criteria: A comparative overview , 2010, Stat. Anal. Data Min..
[16] Ricardo J. G. B. Campello,et al. Generalized external indexes for comparing data partitions with overlapping categories , 2010, Pattern Recognit. Lett..
[17] Mason A. Porter,et al. Taxonomies of networks from community structure. , 2010, Physical review. E, Statistical, nonlinear, and soft matter physics.
[18] Mark Newman,et al. Networks: An Introduction , 2010 .
[19] Jure Leskovec,et al. Empirical comparison of algorithms for network community detection , 2010, WWW '10.
[20] Christopher D. Manning,et al. Introduction to Information Retrieval , 2010, J. Assoc. Inf. Sci. Technol..
[21] James Bailey,et al. Information Theoretic Measures for Clusterings Comparison: Variants, Properties, Normalization and Correction for Chance , 2010, J. Mach. Learn. Res..
[22] Andrea Lancichinetti,et al. Community detection algorithms: a comparative analysis: invited presentation, extended abstract , 2009, VALUETOOLS.
[23] Hui Xiong,et al. Adapting the right measures for K-means clustering , 2009, KDD.
[24] Randy Goebel,et al. Detecting Communities in Large Networks by Iterative Local Expansion , 2009, 2009 International Conference on Computational Aspects of Social Networks.
[25] James Bailey,et al. Information theoretic measures for clusterings comparison: is a correction for chance necessary? , 2009, ICML '09.
[26] Santo Fortunato,et al. Community detection in graphs , 2009, ArXiv.
[27] Mason A. Porter,et al. Communities in Networks , 2009, ArXiv.
[28] F. Radicchi,et al. Benchmark graphs for testing community detection algorithms. , 2008, Physical review. E, Statistical, nonlinear, and soft matter physics.
[29] Andrea Lancichinetti,et al. Detecting the overlapping and hierarchical community structure in complex networks , 2008, 0802.1218.
[30] Martin Rosvall,et al. Maps of random walks on complex networks reveal community structure , 2007, Proceedings of the National Academy of Sciences.
[31] M. Meilă. Comparing clusterings---an information based distance , 2007 .
[32] Feng Luo,et al. Exploring Local Community Structures in Large Networks , 2006, 2006 IEEE/WIC/ACM International Conference on Web Intelligence (WI 2006 Main Conference Proceedings)(WI'06).
[33] Carl T. Bergstrom,et al. An information-theoretic framework for resolving community structure in complex networks , 2006, Proceedings of the National Academy of Sciences.
[34] Ricardo J. G. B. Campello,et al. A fuzzy extension of the silhouette width criterion for cluster analysis , 2006, Fuzzy Sets Syst..
[35] Ahmed Albatineh,et al. On Similarity Indices and Correction for Chance Agreement , 2006, J. Classif..
[36] S. Fortunato,et al. Resolution limit in community detection , 2006, Proceedings of the National Academy of Sciences.
[37] 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.
[38] M. Gustafsson,et al. Comparison and validation of community structures in complex networks , 2006, physics/0601057.
[39] Christos Faloutsos,et al. Graphs over time: densification laws, shrinking diameters and possible explanations , 2005, KDD '05.
[40] T. Vicsek,et al. Uncovering the overlapping community structure of complex networks in nature and society , 2005, Nature.
[41] Leon Danon,et al. Comparing community structure identification , 2005, cond-mat/0505245.
[42] A. Clauset. Finding local community structure in networks. , 2005, Physical review. E, Statistical, nonlinear, and soft matter physics.
[43] M. Newman,et al. Finding and evaluating community structure in networks. , 2003, Physical review. E, Statistical, nonlinear, and soft matter physics.
[44] Joydeep Ghosh,et al. Cluster Ensembles --- A Knowledge Reuse Framework for Combining Multiple Partitions , 2002, J. Mach. Learn. Res..
[45] A. Barabasi,et al. Hierarchical Organization of Modularity in Metabolic Networks , 2002, Science.
[46] 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.
[47] Michalis Vazirgiannis,et al. On Clustering Validation Techniques , 2001, Journal of Intelligent Information Systems.
[48] V. J. Rayward-Smith,et al. Fuzzy Cluster Analysis: Methods for Classification, Data Analysis and Image Recognition , 1999 .
[49] Stanley Wasserman,et al. Social Network Analysis: Methods and Applications , 1994, Structural analysis in the social sciences.
[50] L. Collins,et al. Omega: A General Formulation of the Rand Index of Cluster Recovery Suitable for Non-disjoint Solutions. , 1988, Multivariate behavioral research.
[51] P. Rousseeuw. Silhouettes: a graphical aid to the interpretation and validation of cluster analysis , 1987 .
[52] James C. Bezdek,et al. Pattern Recognition with Fuzzy Objective Function Algorithms , 1981, Advanced Applications in Pattern Recognition.
[53] Donald W. Bouldin,et al. A Cluster Separation Measure , 1979, IEEE Transactions on Pattern Analysis and Machine Intelligence.
[54] W. Zachary,et al. An Information Flow Model for Conflict and Fission in Small Groups , 1977, Journal of Anthropological Research.
[55] L. Hubert,et al. A general statistical framework for assessing categorical clustering in free recall. , 1976 .
[56] E. C. Dalrymple-Alford. Measurement of clustering in free recall. , 1970 .
[57] Osmar R. Zaïane,et al. Top Leaders Community Detection Approach in Information Networks , 2010 .
[58] Randy Goebel,et al. Detecting Communities in Social Networks Using Max-Min Modularity , 2009, SDM.
[59] Sergios Theodoridis,et al. Chapter 16 – Cluster Validity , 2006 .
[60] André Hardy,et al. An examination of procedures for determining the number of clusters in a data set , 1994 .
[61] R. Carter. 11 – IT and society , 1991 .
[62] T. Caliński,et al. A dendrite method for cluster analysis , 1974 .
[63] J. Dunn. Well-Separated Clusters and Optimal Fuzzy Partitions , 1974 .