Classification Method of Ideological and Political Resources of Broadcasting and Hosting Professional Courses Based on SOM Artificial Neural Network

Abstract

In order to improve the classification effect of ideological and political resources of audio hosting professional courses and improve the classification accuracy of ideological and political resources of courses, this paper puts forward a classification method of ideological and political resources of broadcasting and hosting professional courses based on SOM artificial neural network. The adaptive sliding window mutual information method is used to extract the sample characteristics of ideological and political resources of broadcasting and hosting professional courses. This paper constructs the classification model of ideological and political resources of broadcasting and hosting professional courses through deep belief neural network, designs the ideological and political resources classifier of broadcasting and hosting professional courses according to SOM artificial network, constructs the ideological and political resources feature tree of broadcasting and hosting professional courses, and obtains the leaf nodes of the feature tree through hierarchical aggregation algorithm. The category of ideological and political resources of broadcasting and hosting professional courses is obtained by using the merging processing method, the classification operation results are verified by BIC criterion, the number of clusters with the maximum growth distance, that is, the final number of clusters, is calculated and brought into the classifier, and the classification results of SOM artificial network classifier are output to realize the classification of ideological and political resources of broadcasting and hosting professional courses. The experimental results show that, under this method, the accuracy of ideological and political resources classification of broadcasting and hosting professional courses can reach 99.18%, and the completeness is as high as 99.58%, and the F-measure value is effectively improved, which shows that this method can improve the effect of ideological and political resources classification of broadcasting and hosting professional courses.