Research on the Popularity Prediction of Multimedia Network Information Based on Fast K Neighbor Algorithm - Xiaodong Mao; Fei Xu (Journal of Electrical and Computer Engineering)
From the perspective of practical application, information popularity prediction is of positive significance for corporate marketing, advertising, traffic control, and risk management. This paper combines the fast K-nearest neighbor algorithm to predict and analyze the popularity of multimedia network information and improves the nonindependent and identically distributed KNN classification algorithm. Moreover, this paper proves that it is a superior measurement method when considering the nonindependent and identical distribution among data objects to measure similarity and the improved CS_KNN algorithm can greatly improve the classification performance. Finally, this paper constructs a prediction model of multimedia network information popularity based on the fast K neighbor algorithm. Through the experimental research results, it can be seen that the prediction effect of the multimedia network information popularity prediction system based on the fast K neighbor algorithm proposed in this study is very good.