A Survey of Deep Learning-Based Generative Text Summarization
With the rapid development of the Internet,text data has shown exponential growth,bringing unprecedented challenges to text pro-cessing tasks such as document management,text classification,and information retrieval.Although researchers have developed various deep learning(DL)based generative summarization(ATS)models,most of the most advanced ATS models are based on the DL architecture,and there is still a lack of comprehensive literature review in the field of DL based generative text summarization.To this end,a comprehensive sur-vey of DL based ATS was provided.Firstly,the concept of ATS is outlined,followed by a summary of typical models of DL based ATS and their main challenges and solutions.Finally,some open challenges in ATS tasks,as well as current hot and difficult issues and future research trends,are emphasized to help researchers better understand the latest developments in this field and provide guidance and inspiration for fu-ture research.
automatic text summarizationdeep learninggenerative summarizationnatural language processingnatural language genera-tion
国家科技期刊平台
NSTL
万方数据
