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• W2489431168 startingPage "345" @default.
• W2489431168 abstract "The scientific problems that Big Data faces may be network scientific problems. Network analytics contributes a great deal to networked Big Data processing. Many network issues can be modeled as nonconvex optimization problems and consequently they can be addressed by optimization techniques. In the pipeline of nonconvex optimization techniques, evolutionary computation gives an outlet to handle these problems efficiently. Because, network community discovery is a critical research agenda of network analytics, in this chapter we focus on the evolutionary computation based nonconvex optimization for network community discovery. The single and multiple objective optimization models for the community discovery problem are thoroughly investigated. Several experimental studies are shown to demonstrate the effectiveness of optimization based approach for big network community analytics." @default.
• W2489431168 created "2016-08-23" @default.
• W2489431168 creator A5033300023 @default.
• W2489431168 creator A5039451864 @default.
• W2489431168 creator A5066912525 @default.
• W2489431168 creator A5091227928 @default.
• W2489431168 date "2016-01-01" @default.
• W2489431168 modified "2023-09-27" @default.
• W2489431168 title "Big Network Analytics Based on Nonconvex Optimization" @default.
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