Novel Multirole-Oriented Deep Learning Text Classification Model

In order to improve the analysis of multiple roles in novels, this article applies the deep learning text classification model to the analysis of novel roles. Moreover, in this article, the scale space formed by multiple text images of the same size is called an octave, and the text image size of adjacent groups is halved to construct a Gaussian pyramid. In text classification, this article uses the argument and amplitude information to form a direction gradient histogram and takes the argument corresponding to the largest peak as a main direction of the key point. Finally, this article constructs an intelligent analysis model. The research results show that the deep learning text classification model for multiple roles in novels proposed in this article has good effects on role analysis and text classification. For film and television scripts, the classification analysis of analysis texts and the contrast creation have very good application help.