The DOI matches its Crossref record; 51 of the 51 references it cites were found in a registry or an index.
A Multiobjective Genetic Algorithm to Find Communities in Complex Networks
Abstract
A multiobjective genetic algorithm to uncover community structure in complex network is proposed. The algorithm optimizes two objective functions able to identify densely connected groups of nodes having sparse inter-connections. The method generates a set of network divisions at different hierarchical levels in which solutions at deeper levels, consisting of a higher number of modules, are contained in solutions having a lower number of communities. The number of modules is automatically determined by the better tradeoff values of the objective functions. Experiments on synthetic and real life networks show that the algorithm successfully detects the network structure and it is competitive with state-of-the-art approaches.
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Cites
A fast and elitist multiobjective genetic algorithm: NSGA-II
Deb, K., Pratap, A., Agarwal, S., & Meyarivan, T. (2002) · IEEE Transactions on Evolutionary Computation · doi:10.1109/4235.996017 · Cited by 50,053
Fast unfolding of communities in large networks
Blondel, V. D., Guillaume, J.-L., Lambiotte, R., & Lefebvre, E. (2008) · Journal of Statistical Mechanics: Theory and Experiment · doi:10.1088/1742-5468/2008/10/p10008 · Cited by 21,424
Silhouettes: A graphical aid to the interpretation and validation of cluster analysis
Rousseeuw, P. J. (1987) · Journal of Computational and Applied Mathematics · doi:10.1016/0377-0427(87)90125-7 · Cited by 21,392
Community structure in social and biological networks
Girvan, M., & Newman, M. E. J. (2002) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.122653799 · Cited by 15,502
Multi-Objective Optimization Using Evolutionary Algorithms
Deb, K., & Kalyanmoy, D. (2001) · Andalas University Repository (Andalas University) · Cited by 14,918
Finding and evaluating community structure in networks
Newman, M. E. J., & Girvan, M. (2004) · Physical Review E · doi:10.1103/physreve.69.026113 · Cited by 13,931
Modularity and community structure in networks
Newman, M. E. J. (2006) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.0601602103 · Cited by 12,256
Fortunato, S. (2010) · Physics Reports · doi:10.1016/j.physrep.2009.11.002 · Cited by 11,293
Multiobjective evolutionary algorithms: a comparative case study and the strength Pareto approach
Zitzler, E., & Thiele, L. (1999) · IEEE Transactions on Evolutionary Computation · doi:10.1109/4235.797969 · Cited by 8,798
Algorithms for Clustering Data
Sarle, W. S. (1990) · Technometrics · doi:10.1080/00401706.1990.10484648 · Cited by 7,865
Cited by
Evolutionary Large-Scale Multi-Objective Optimization: A Survey
Tian, Y., Si, L., Zhang, X., Cheng, R., He, C., Tan, K. C., & Jin, Y. (2022) · ACM Computing Surveys · doi:10.1145/3470971 · Cited by 401
Community detection in social networks
Bedi, P., & Sharma, C. (2016) · WIREs Data Mining and Knowledge Discovery · doi:10.1002/widm.1178 · Cited by 346
Metadata
- Authors
- Pizzuti, C.
- Venue
- IEEE Transactions on Evolutionary Computation
- Published
- 2012-06
- Volume
- 16
- Issue
- 3
- Pages
- 418-430
- ISSN
- 1089-778X (ISSN-L)
- 1941-0026
- OpenAlex
- W2171552940
- Cited by
- 346
- References
- 51
- FWCI
- 7.22
- Type
- journal article
- Language
- en
- Open access
- closed
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