Research on Text Summarization Generation Based on Key Words and Transformer
Traditional summarization generation techniques overlook the role of keyword information in generating sum-maries,resulting in difficulty in focusing on key information in the generated summaries.To solve this problem,a text sum-marization generation method based on the Transformer model,and integrating keywords and convolutional neural networks is proposed to achieve keyword guided summarization generation.The experiment is conducted on the CSDS dataset,and the results shows that the method improved on the ROUGE scores,verifying the effectiveness of the proposed method.
text summarizationkeywords extractionconvolutional neural networksTransformer
万方数据
维普
