References
- Agarwal, G. and Kempe, D. (2008). Modularity-maximizing graph communities via mathematical programming. The European Physical Journal B-Condensed Matter and Complex Systems, 66, 409-418. https://doi.org/10.1140/epjb/e2008-00425-1
- Arenas, A., Duch, J., Fernandez, A. and Gomez, S. (2007). Size reduction of complex networks preserving modularity. New Journal of Physics, 9, 176. https://doi.org/10.1088/1367-2630/9/6/176
- Blondel, V., Guillaume, J. L., Lambiotte, R. and Lefebvre, E. (2008). Fast unfolding of communities in large networks. Journal of Statistical Mechanics: Theory and Experiment, 2008, P10008.
- Brandes, U., Delling, D., Gaertler, M., Gorke, R., Hoefer, M., Nikoloski, Z. and Wagner, D. (2008). On modularity clustering. IEEE Transactions on Knowledge and Data Engineering, 20, 172-188. https://doi.org/10.1109/TKDE.2007.190689
- Carpenter, M. P. and Narin, F. (1973). Clustering of scientific journals. Journal of the American Society for Information Science, 24, 425-436. https://doi.org/10.1002/asi.4630240604
- Clauset, A., Newman, M. and Moore, C. (2004). Finding community structure in very large networks. Physical Review E, 70, 66111. https://doi.org/10.1103/PhysRevE.70.066111
- Dinh, T. N. and Thai, M. T. (2013). Towards optimal community detection: From trees to general weighted networks. Internet Mathematics (accepted pending revision).
- Fawcett, T. (2006). An introduction to ROC analysis. Pattern recognition letters, 27, 861-874. https://doi.org/10.1016/j.patrec.2005.10.010
- Fortunato, S. (2010). Community detection in graphs. Physics Reports, 486, 74-174.
- Girvan, M. and Newman, M. E. (2002). Community structure in social and biological networks. Proceedings of the National Academy of Sciences, 99, 7821-7826. https://doi.org/10.1073/pnas.122653799
- Jeong, E. S., Cho, D. Y., Suh, I. W. and Yeo, W. D. (2008). Emerging research field selection of construction & transportation sectors using scientometrics. The Journal of the Korea Contents Association, 8, 231-238. https://doi.org/10.5392/JKCA.2008.8.2.231
- Kim, H. (2008). Citation flow of the ASIST proceedings using pathfinder network analysis. Journal of the Korean Society for Information Management, 25, 157-166. https://doi.org/10.3743/KOSIM.2008.25.2.157
- Kim, J. A. and Lee, H. S. (2008). A study on network analysis for science and technology activity. Proceedings of the Autumn Conference of the Korean Operations Research and Management Science Society, 498-503.
- Lancichinetti, A. and Fortunato, S. (2009a). Benchmarks for testing community detection algorithms on directed and weighted graphs with overlapping communities. Physical Review E, 80, 016118. https://doi.org/10.1103/PhysRevE.80.016118
- Lancichinetti, A. and Fortunato, S. (2009b). Community detection algorithms: A comparative analysis. Physical review E, 80, 056117. https://doi.org/10.1103/PhysRevE.80.056117
- Levorato, V. and Petermann, C. (2011). Detection of communities in directed networks based on strongly p-connected components. International Conference on Computational Aspects of Social Networks, CASoN, IEEE, 211-216.
- Leydesdorff, L. (2004). Clusters and Maps of Science Journals Based on Bi-connected Graphs in the Journal Citation Reports. Journal of Documentation, 9, 715-723.
- Lin, W., Kong, X., Yu, P. S., Wu, Q., Jia, Y. and Li, C. (2012). Community detection in incomplete information networks. In Proceedings of the 21st international conference on World Wide Web, ACM, 341-350.
- Malliaros, F. D. and Vazirgiannis, M. (2013). Clustering and community detection in directed networks:A survey. Physics Reports Journal, 533, 95-142. https://doi.org/10.1016/j.physrep.2013.08.002
- Narin, F., Carpenter, M. and Berlt, N. (1972). Interrelationships of scientific journals. Journal of the American Society for Information Science, 23, 323-331. https://doi.org/10.1002/asi.4630230508
- Newman, M. and Girvan, M. (2003). Mixing patterns and community structure in networks. in Statistical Mechanics of Complex Networks, 625, 66-87. https://doi.org/10.1007/978-3-540-44943-0_5
- Newman, M. and Girvan, M. (2004). Finding and evaluating community structure in networks. Physical Review E, 69, 26113. https://doi.org/10.1103/PhysRevE.69.026113
- Newman, M. E. (2004). Fast algorithm for detecting community structure in networks. Physical review E, 69, 066133. https://doi.org/10.1103/PhysRevE.69.066133
- Newman, M. E. and Leicht, E. A. (2007). Mixture models and exploratory analysis in networks. Proceedings of the National Academy of Sciences, 104, 9564-9569. https://doi.org/10.1073/pnas.0610537104
- Park, C. (2013). Simple principle component analysis using Lasso. Journal of the Korean Data & Information Science Society, 24, 533-541. https://doi.org/10.7465/jkdi.2013.24.3.533
- Pons, P. and Latapy, M. (2006). Computing communities in large networks using random walks. Journal of Graph Algorithms and Applications,, 10, 191-218. https://doi.org/10.7155/jgaa.00124
- Radicchi, F., Castellano, C., Cecconi, F., Loreto, V. and Parisi, D. (2004). Defining and identifying communities in networks. Proceedings of the National Academy of Sciences of the United States of America, 101, 2658-2663. https://doi.org/10.1073/pnas.0400054101
- Raghavan, U. N., Albert, R. and Kumara, S. (2007). Near linear time algorithm to detect community structures in large-scale networks. Physical Review E, 76, 036106. https://doi.org/10.1103/PhysRevE.76.036106
- Rosvall, M. and Bergstrom, C. T. (2008). Maps of random walks on complex networks reveal community structure. Proceedings of the National Academy of Sciences, 105, 1118-1123. https://doi.org/10.1073/pnas.0706851105
- Schaeffer, S. E. (2007). Graph clustering. Computer Science Review, 1, 27-64. https://doi.org/10.1016/j.cosrev.2007.05.001
- Ward Jr, J. H. (1963). Hierarchical grouping to optimize an objective function. Journal of the American statistical association, 58, 236-244. https://doi.org/10.1080/01621459.1963.10500845
- Zhang, A., Ren, G., Cao, H., zhu Jia, B. and bin Zhang, S. (2013). Generalization of label propagation algorithm in complex networks. In Control and Decision Conference (CCDC), 2013 25th Chinese, IEEE, 1306-1309.
- Zhang, L., Liu, X., Janssens, F., Liang, L. and Glanzel, W. (2010). Subject clustering analysis based on ISI category classification. Journal of Informetrics, 4, 185-193. https://doi.org/10.1016/j.joi.2009.11.005
Cited by
- A classification of the journals in KCI using network clustering methods vol.27, pp.4, 2016, https://doi.org/10.7465/jkdi.2016.27.4.947