Applications of Artificial Intelligence Technology in the News Media Sector

Abstract

The application of artificial intelligence algorithms in news media systems is gradually forming an intelligent content ecosystem driven by deep models. We have constructed a multi module intelligent system that integrates Transformer, BERT, and knowledge graph, covering three major functions: semantic parsing, content recommendation, and intelligent generation. Based on multimodal embedding and Prompt optimization techniques, we have completed algorithm iterations on the basis of traditional CNN and LSTM architectures. The experiment showed that the BART model improved the BLEU score to 36.42 in the abstract generation task, which was 16.4% higher than that of Transformer; The Transformer in the recommendation system NDCG@10 Reaching 0.873, better than XGBoost and LSTM. The system exhibits significant advantages in both accuracy and response speed.