Frontiers of Data and Domputing ›› 2021, Vol. 3 ›› Issue (3): 111-125.doi: 10.11871/jfdc.issn.2096-742X.2021.03.010

• Technology and Applicaton • Previous Articles     Next Articles

A Survey on Short-text Generation Technology

ZHANG Chenyang1,2(),DU Yihua1,*()   

  1. 1. Computer Network Information Center, Chinese Academy of Science, Beijing 100190, China
    2. University of Chinese Academy of Sciences, Beijing 100049, China
  • Received:2021-01-06 Online:2021-06-20 Published:2021-07-09
  • Contact: DU Yihua E-mail:zhangchenyang@cnic.cn;yhdu@cashq.ac.cn

Abstract:

[Context] Research on short-text generation is of great importance in improving the efficiency of reading and writing, the impact of communication and guidance, the satisfaction of intelligent human-computer interaction and the capacity for machine semantic comprehension. However, short-text generation technology faces many difficulties and challenges due to the weakness of generation technology and the increasing complexity of realistic implementation requirements.[Methods] The neural network based generation method is a key artificial intelligence technology that has accomplished several pioneering achievements in short-text summary, dialogue generation, text generation of comments, poetry creation, and other linguistic tasks. [Results] This paper presents the research status and development of neural network based short-text generation technology in the aspects of the generation model, goal, and evaluation metric, providing a guide for further research into short-text generation technology. [Conclusions] we summarized the difficulties, challenges and trends of neural network based short-text generation technology.

Key words: Natural Language Generation (NLG), neural network model, short-text, evaluation method