WNTC: An Efficient Weight News Text Classification Model

News text classification plays an important part in the field of news recommendation and intelligent office. Based on the above problem, we use the real open-source data Sogou CS as the research object of this paper to carry out related work, test the accuracy of multiple AI algorithm models, use models with good prediction results, and calculate weights based on the accuracy of each model to form a composite model, named WNTC model. Experimental results on the above real dataset show that our WNTC model significantly outperforms the traditional model, in detail, the accuracy, recall rate, F1-score of the model is 94.27%, 96.02%, 95.14%, which is improved to be compared to the prediction effect of a single AI algorithm model.

Automated summary

This study uses real open-source data to test the accuracy of multiple AI algorithm models and form a composite model named WNTC, which significantly outperforms the traditional model in news text classification tasks.