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- W2910916582 abstract "In recent years, social networks analysis has attracted the attention of many researchers. Community detection is one of the highly studied problems in this field. It is considered an NP-hard problem, and several algorithms have been proposed to solve this problem. In this chapter, the authors present a new algorithm for community detection in social networks based on the Black Hole optimization algorithm. The authors use the modularity density evaluation measure as a function to maximize. They also propose the enhancement of the algorithm by using two new strategies: initialization and evolution. The proposed algorithm has been tested on famous synthetic and real-world networks; experimental results compared with three known algorithms show the effectiveness of using this algorithm for community detection in social networks." @default.
- W2910916582 created "2019-01-25" @default.
- W2910916582 creator A5043969619 @default.
- W2910916582 date "2018-01-01" @default.
- W2910916582 modified "2023-09-27" @default.
- W2910916582 title "A Discrete Black Hole Optimization Algorithm for Efficient Community Detection in Social Networks" @default.
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- W2910916582 doi "https://doi.org/10.4018/978-1-5225-3004-6.ch009" @default.
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