The present study aimed at finding the least significant edges based on the target set selection. Selecting a target set
consists of a subset of influential and effector nodes in an active social subnet to maximize the influence on the entire nodes of a
network. The best heuristic algorithm only ensures that all nodes of a network can be influenced with a maximum of 63% of the target
set selection. The concepts of vertex cover were used to find the active and influential nodes. The edges between the active or effector
nodes were considered as significant edges while the other edges were considered as least significant. The experiment performed on
four laboratory data and a real data showed that the proposed algorithm was more optimized.
Sadegh Saeedi : MSc student of computer
engineering Department of Computer Engineering, Ahvaz
Branch, Islamic Azad University, Iran.
Dr. Mohammad Hossein Yektaei : Ph.D.
Assistant Professor, Department of Computer Engineering,
Abadan Branch, Islamic Azad University, Iran.
Social network, least significant edges, Dragonfly Algorithm, target set selection
Today networks are widespread everywhere Spread
of the networks in the world, It forces us to study
them, Their study is based on the method of creating
nodes and their relationship in the form of a model.
The purpose of this article is to find least-significant
edges.the least-significant edges will be obtained
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