1. Research on the Popularity Prediction of Multimedia Network Information Based on Fast K Neighbor Algorithm.
- Author
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Mao, Xiaodong and Xu, Fei
- Subjects
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MULTIMEDIA communications , *INFORMATION networks , *MULTIMEDIA systems , *K-nearest neighbor classification , *POPULARITY , *ALGORITHMS , *DISTRIBUTED algorithms , *CLASSIFICATION algorithms - Abstract
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. [ABSTRACT FROM AUTHOR]
- Published
- 2022
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