518
Views
0
CrossRef citations to date
0
Altmetric
Network Analysis

Fast Community Detection in Dynamic and Heterogeneous Networks

, &
Pages 487-500 | Received 23 Oct 2022, Accepted 24 Jun 2023, Published online: 05 Sep 2023

References

  • Abbe, E. (2017), “Community Detection and Stochastic Block Models: Recent Developments,” The Journal of Machine Learning Research, 18, 6446–6531.
  • Blondel, V. D., 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. DOI: 10.1088/1742-5468/2008/10/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. DOI: 10.1109/TKDE.2007.190689.
  • Chung, F., Fan, R., Chung, F. R., Graham, F. C., Lu, L., Chung, K. F., et al. (2006), Complex Graphs and Networks, no. 107. American Mathematical Society: Providence, RI: .
  • Clauset, A., Newman, M. E., and Moore, C. (2004), “Finding Community Structure in Very Large Networks,” Physical Review E, 70, 066111. DOI: 10.1103/PhysRevE.70.066111.
  • Danon, L., Diaz-Guilera, A., Duch, J., and Arenas, A. (2005), “Comparing Community Structure Identification,” Journal of Statistical Mechanics: Theory and Experiment, 2005, P09008. DOI: 10.1088/1742-5468/2005/09/P09008.
  • Fortunato, S. (2010), “Community Detection in Graphs,” Physics Reports, 486, 75–174. DOI: 10.1016/j.physrep.2009.11.002.
  • Guimera, R., Sales-Pardo, M., and Amaral, L. A. N. (2004), “Modularity from Fluctuations in Random Graphs and Complex Networks,” Physical Review E, 70, 025101. DOI: 10.1103/PhysRevE.70.025101.
  • Jiang, S., Koch, B., and Sun, Y. (2021), “Hints: Citation Time Sries Prediction for New Publications via Dynamic Heterogeneous Information Network Embedding,” in Proceedings of the Web Conference 2021, pp. 3158–3167.
  • Linden, G., Smith, B., and York, J. (2003), “Amazon. com Recommendations: Item-to-Item Collaborative Filtering,” IEEE Internet Computing, 7, 76–80. DOI: 10.1109/MIC.2003.1167344.
  • Massen, C. P., and Doye, J. P. (2005), “Identifying Communities Within Energy Landscapes,” Physical Review E, 71, 046101. DOI: 10.1103/PhysRevE.71.046101.
  • Milo, R., Shen-Orr, S., Itzkovitz, S., Kashtan, N., Chklovskii, D., and Alon, U. (2002), “Network Motifs: Simple Building Blocks of Complex Networks,” Science, 298, 824–827. DOI: 10.1126/science.298.5594.824.
  • Moody, J., and White, D. R. (2003), “Structural Cohesion and Embeddedness: A Hierarchical Concept of Social Groups,” American Sociological Review, 68, 103–127. DOI: 10.1177/000312240306800105.
  • Newman, M. E. (2006), “Finding Community Structure in Networks using the Eigenvectors of Matrices,” Physical Review E, 74, 036104. DOI: 10.1103/PhysRevE.74.036104.
  • Newman, M. E., and Girvan, M. (2004), “Finding and Evaluating Community Structure in Networks,” Physical Review E, 69, 026113. DOI: 10.1103/PhysRevE.69.026113.
  • Newman, M. E., Strogatz, S. H., and Watts, D. J. (2001), “Random Graphs with Arbitrary Degree Distributions and their Applications,” Physical Review E, 64, 026118. DOI: 10.1103/PhysRevE.64.026118.
  • Sengupta, S., and Chen, Y. (2015), “Spectral Clustering in Heterogeneous Networks,” Statistica Sinica, 25, 1081–1106. DOI: 10.5705/ss.2013.231.
  • Sørlie, T., Perou, C. M., Tibshirani, R., Aas, T., Geisler, S., Johnsen, H., Hastie, T., Eisen, M. B., Van De Rijn, M., Jeffrey, S. S., et al. (2001), “Gene Expression Patterns of Breast Carcinomas Distinguish Tumor Subclasses with Clinical Implications,” Proceedings of the National Academy of Sciences, 98, 10869–10874. DOI: 10.1073/pnas.191367098.
  • Sun, Y., Tang, J., Han, J., Gupta, M., and Zhao, B. (2010), “Community Evolution Detection in Dynamic Heterogeneous Information Networks,” in Proceedings of the Eighth Workshop on Mining and Learning with Graphs, pp. 137–146. DOI: 10.1145/1830252.1830270.
  • Wakita, K., and Tsurumi, T. (2007), “Finding Community Structure in Mega-Scale Social Networks,” in Proceedings of the 16th International Conference on World Wide Web, pp. 1275–1276.
  • Wang, X., Lu, Y., Shi, C., Wang, R., Cui, P., and Mou, S. (2022), “Dynamic Heterogeneous Information Network Embedding with Meta-Path based Proximity,” IEEE Transactions on Knowledge and Data Engineering, 34, 1117 – 1132. DOI: 10.1109/TKDE.2020.2993870.
  • Xue, H., Yang, L., Jiang, W., Wei, Y., Hu, Y., and Lin, Y. (2020), “Modeling Dynamic Heterogeneous Network for Link Prediction Using Hierarchical Attention with Temporal RNN,” arXiv preprint arXiv:2004.01024.
  • Yin, Y., Ji, L.-X., Zhang, J.-P., and Pei, Y.-L. (2019), “Dhne: Network Representation Learning Method for Dynamic Heterogeneous Networks,” IEEE Access, 7, 134782–134792. DOI: 10.1109/ACCESS.2019.2942221.
  • Zhang, J., and Cao, J. (2017), “Finding Common Modules in a Time-Varying Network with Application to the Drosophila Melanogaster Gene Regulation Network,” Journal of the American Statistical Association, 112, 994–1008. DOI: 10.1080/01621459.2016.1260465.
  • Zhang, J., and Chen, Y. (2017), “A Hypothesis Testing Framework for Modularity based Network Community Detection,” Statistica Sinica, 27, 437–456. DOI: 10.5705/ss.202015.0040.
  • Zhang, J., and Chen, Y. (2020), “Modularity based Community Detection in Heterogeneous Networks,” Statistica Sinica, 30, 601–629. DOI: 10.5705/ss.202017.0399.
  • Zhang, J., Sun, W. W., and Li, L. (2020), “Mixed-Effect Time-Varying Network Model and Application in Brain Connectivity Analysis,” Journal of the American Statistical Association, 115, 2022–2036. DOI: 10.1080/01621459.2019.1677242.
  • Zhang, Z., Huang, J., and Tan,Q (2022), “Multi-View Dynamic Heterogeneous Information Network Embedding,” The Computer Journal, 65, 2016–2033. DOI: 10.1093/comjnl/bxab041.

Reprints and Corporate Permissions

Please note: Selecting permissions does not provide access to the full text of the article, please see our help page How do I view content?

To request a reprint or corporate permissions for this article, please click on the relevant link below:

Academic Permissions

Please note: Selecting permissions does not provide access to the full text of the article, please see our help page How do I view content?

Obtain permissions instantly via Rightslink by clicking on the button below:

If you are unable to obtain permissions via Rightslink, please complete and submit this Permissions form. For more information, please visit our Permissions help page.