Retrospect and Prospect of Artificial Intelligence Research in China

  • Jie Tang
  • Sha Yuan
  • Yuan Zhou


With the rapid development and application of artificial intelligence (AI), the computer technology has entered the era of new Information Technology (IT) called Intelligent Technology. AI can accelerate the information construction of science and technology. In the past two years, the AI research has been promoted to the level of the national development strategy in China. This chapter explores the origin and development of AI and the AI development in China. AMiner, a big data analysis and service platform for science and technology, is independently developed by China. It is a successful case in the informatization of science and technology in China. Based on the open dataset of AI in AMiner, we give the classification of the AI research in China. We overview the AI research situation in China based on the experts, chapters, and patents analysis. The AI applications, such as speech recognition, face recognition, automatic driving, and so on, are introduced in the chapter. We also discuss the opportunities and challenges of AI in China. In general, this chapter fills the gaps in the authoritative analysis of the AI research situation in China.


Artificial intelligence Research situation Application Opportunity and challenge 


  1. 1.
    Santo Fortunato, Carl T Bergstrom, Katy Börner, James A Evans, Dirk Helbing, Staša Milojević, et al. 2018. Science of science. Science 359, 6379 (2018).Google Scholar
  2. 2.
    Rosenblatt F. The perceptron: A probabilistic model for information storage and organization in the brain [J]. Psychological Review, 1958, 65(6):386.CrossRefGoogle Scholar
  3. 3.
    McCarthy J, Minsky M L, Rochester N, et al. A Proposal for the Dartmouth Summer Research Project on Artificial Intelligence [J]. Journal of Molecular Biology, 2006, 278(1):279–289.Google Scholar
  4. 4.
    Jie Tang, Jing Zhang, Limin Yao, Juanzi Li, Li Zhang, and Zhong Su. 2008. Arnetminer: extraction and mining of academic social networks. In Proceedings of the 14th ACM SIGKDD international conference on Knowledge discovery and data mining. ACM, 990–998.Google Scholar

Copyright information

© Publishing House of Electronics Industry 2020

Authors and Affiliations

  • Jie Tang
    • 1
  • Sha Yuan
    • 1
  • Yuan Zhou
    • 2
  1. 1.Department of Computer Science and TechnologyTsinghua UniversityBeijingChina
  2. 2.School of Public Policy and ManagementTsinghua UniversityBeijingChina

Personalised recommendations