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|Title:||Cuckoo search for influence maximization in social networks|
|Citation:||Smart Innovation, Systems and Technologies, 2016, Vol.44, , pp.51-61|
|Abstract:||In a social network, the influence maximization is to find out the optimal set of seeds, by which influence can be maximized at the end of diffusion process. The approaches which are already existing are greedy approaches, genetic algorithm and ant colony optimization. Eventhough these existing algorithms take more time for diffusion, they are not able to generate a good number of influenced nodes. In this paper, a Cuckoo Search Diffusion Model (CSDM) is proposed which is based on a metaheuristic approach known as the Cuckoo Search Algorithm. It uses fewer parameters than any other metaheuristic approaches. Therefore parameter tuning is an easy task for this algorithm which is the main advantage of the Cuckoo Search algorithm. Experimental results show that this model gives better results than previous works. � Springer India 2016.|
|Appears in Collections:||2. Conference Papers|
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