Discovering the backbone network with a novel designed ant colony algorithm - Fang LYU; Jun BAI; Junheng HUANG; Bailing WANG (Tongxin xuebao)
Forthe problem that in interactive network,the illegal and abnormal behaviors were becoming more hidden,moreover,the complex relation in real interactive network heightens the difficulty of detecting anomalous entities,an ant colony model was proposed for extracting the backbone network from the complex interactive network.The novel model simulated the relationships among entities based on the theory of path optimization,reduced the network size after quantifying the significance of each flow of information.Firstly,a strategy of initial location selection was proposed taking advantage of network centrality.Secondly,a novel path transfer mechanism was devised for the ant colony to fit the flow behavior of entities.Finally,an adaptive and dynamic pheromone update mechanism was designed for guiding the optimization of information flows.The experimental results show that the proposed model is superior to the traditional ant colony algorithm in both solving quality and solving performance,and has better coverage and accuracy than the greedy algorithm.