Research on Effective Classification of Network Information Based on Task Queue

Abstract:

Aiming at the problem that the online social network information propagation model is not classified in the event description and the latency of the waiting time is reduced, an effective method of nonlinear timevarying information propagation is proposed.On this basis, the EC model of event classification is established.Firstly, the dynamic network propagation model is used to propagate the relationship between the social network relationship and the user behavior.Then, based on the nonlinear timevarying relationship of task priority, waiting time and probability generating function, the model of online network information propagation is analyzed.And finally the Nexponential function was introduced to establish the EC model.The simulation results show that the probability chart of waiting time obeys the power law distribution.The improved model compares the favorable event with the traditional model.The effect of the waiting time probability distribution is 23.1%, and 21.8% for the harmful event And the theoretical simulation results are consistent with the trend of real data.The proposed EC model is reasonable and effective.