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https://doi.org/10.17559/TV-20150317103835

An efficient multi-objective community detection algorithm in complex networks

Kun Deng ; College of Computer Science and Technology, Harbin Engineering University, Harbin 150001, China
Jian-Pei Zhang ; College of Computer Science and Technology, Harbin Engineering University, Harbin 150001, China
Jing Yang ; College of Computer Science and Technology, Harbin Engineering University, Harbin 150001, China

Puni tekst: engleski, pdf (433 KB) str. 319-328 preuzimanja: 289* citiraj
APA 6th Edition
Deng, K., Zhang, J. i Yang, J. (2015). An efficient multi-objective community detection algorithm in complex networks. Tehnički vjesnik, 22 (2), 319-328. https://doi.org/10.17559/TV-20150317103835
MLA 8th Edition
Deng, Kun, et al. "An efficient multi-objective community detection algorithm in complex networks." Tehnički vjesnik, vol. 22, br. 2, 2015, str. 319-328. https://doi.org/10.17559/TV-20150317103835. Citirano 19.10.2019.
Chicago 17th Edition
Deng, Kun, Jian-Pei Zhang i Jing Yang. "An efficient multi-objective community detection algorithm in complex networks." Tehnički vjesnik 22, br. 2 (2015): 319-328. https://doi.org/10.17559/TV-20150317103835
Harvard
Deng, K., Zhang, J., i Yang, J. (2015). 'An efficient multi-objective community detection algorithm in complex networks', Tehnički vjesnik, 22(2), str. 319-328. https://doi.org/10.17559/TV-20150317103835
Vancouver
Deng K, Zhang J, Yang J. An efficient multi-objective community detection algorithm in complex networks. Tehnički vjesnik [Internet]. 2015 [pristupljeno 19.10.2019.];22(2):319-328. https://doi.org/10.17559/TV-20150317103835
IEEE
K. Deng, J. Zhang i J. Yang, "An efficient multi-objective community detection algorithm in complex networks", Tehnički vjesnik, vol.22, br. 2, str. 319-328, 2015. [Online]. https://doi.org/10.17559/TV-20150317103835
Puni tekst: hrvatski, pdf (433 KB) str. 319-328 preuzimanja: 366* citiraj
APA 6th Edition
Deng, K., Zhang, J. i Yang, J. (2015). Učinkoviti višekriterijski algoritam za detekciju zajednice u složenim mrežama. Tehnički vjesnik, 22 (2), 319-328. https://doi.org/10.17559/TV-20150317103835
MLA 8th Edition
Deng, Kun, et al. "Učinkoviti višekriterijski algoritam za detekciju zajednice u složenim mrežama." Tehnički vjesnik, vol. 22, br. 2, 2015, str. 319-328. https://doi.org/10.17559/TV-20150317103835. Citirano 19.10.2019.
Chicago 17th Edition
Deng, Kun, Jian-Pei Zhang i Jing Yang. "Učinkoviti višekriterijski algoritam za detekciju zajednice u složenim mrežama." Tehnički vjesnik 22, br. 2 (2015): 319-328. https://doi.org/10.17559/TV-20150317103835
Harvard
Deng, K., Zhang, J., i Yang, J. (2015). 'Učinkoviti višekriterijski algoritam za detekciju zajednice u složenim mrežama', Tehnički vjesnik, 22(2), str. 319-328. https://doi.org/10.17559/TV-20150317103835
Vancouver
Deng K, Zhang J, Yang J. Učinkoviti višekriterijski algoritam za detekciju zajednice u složenim mrežama. Tehnički vjesnik [Internet]. 2015 [pristupljeno 19.10.2019.];22(2):319-328. https://doi.org/10.17559/TV-20150317103835
IEEE
K. Deng, J. Zhang i J. Yang, "Učinkoviti višekriterijski algoritam za detekciju zajednice u složenim mrežama", Tehnički vjesnik, vol.22, br. 2, str. 319-328, 2015. [Online]. https://doi.org/10.17559/TV-20150317103835

Sažetak
Community detection in complex networks is often regarded as the problem of single-objective optimization and it is hard for single-objective optimization to identify potential community structure of meaningfulness. Thus, algorithm of multi-objective optimization is applied to the field of community detection. However, multi-objective community detection algorithm is prone to local optimization and weak diversity of the set of Paretooptimal solutions. In view of this, based on the framework of NSGAII, a multi-objective community detection algorithm, named I-NSGAII, is proposed in this paper. This algorithm is able to optimize simultaneously the two conflicting objective functions evaluating the density of intra-community connections and the sparsity of inter-community connections, and obtain the set of Pareto optimal solutions having diverse hierarchal community structures; it also proposes diversity evolutionary strategy enabling the algorithm to expand searching space and thus avoids local optimization of the set of Pareto-optimal solutions. In addition, to improve algorithm’s searching ability, I-NSGAII algorithm adopts the strategies of locus-based adjacency representation, unified label, one-way crossover and local mutation. Tests on synthetic and real-world networks and comparisons with many state-of-theart algorithms verify the validity and feasibility of I-NSGAII.

Ključne riječi
complex networks; diversity evolutionary strategy; multi-objective community detection; NSGAII

Hrčak ID: 138083

URI
https://hrcak.srce.hr/138083

[hrvatski]

Posjeta: 889 *