Quality evaluation of teaching video content based on user behavior

Abstract

Abstract: Currently, the problem that subjective method is the main method for evaluating the quality of online teaching video content, lacking of objective criterion for defining its quality. In this paper, aonline teaching video quality evaluation method is proposed based on user behavior. In this method, the behavior data of single user watching a networked teaching video is collected first and normalized. Data tagging is then implemented based on evaluation standard of video quality and the quality classification of the networked teaching video content is conducted by the single user by means of fully connected neural network and Softmax. Finally, a classification weighted average of the ratings of all users watching this video gives a comprehensive evaluation of the video. The test result shows that the accuracy of this model will be 79.5% and the classification effect will be obvious, having higher practical value.

Key words: online teaching video, user behavior, standardization, fully connected neural network, comprehensive evaluation

CLC Number:

TP39

MA Dong-lin, WANG Xiao-tong, ZHANG Shu-huan, GUO Ya-ting. Quality evaluation of teaching video content based on user behavior[J]. Journal of Lanzhou University of Technology, 2020, 46(3): 110-115.

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