Research on the Popularity Prediction of Multimedia Network Information Based on Fast K Neighbor Algorithm
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 netwo...
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| Main Authors: | , |
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| Format: | Article |
| Language: | English |
| Published: |
Wiley
2022-01-01
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| Series: | Journal of Electrical and Computer Engineering |
| Online Access: | http://dx.doi.org/10.1155/2022/8745492 |
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| Summary: | 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. |
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| ISSN: | 2090-0155 |