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Abdelgawad, L., Kluegl, P., Genc, E., Falkner, S., & Hutter, F. (2020). Optimizing Neural Networks for Patent Classification. In U. Brefeld et al. (Eds.), Machine Learning and Knowledge Discovery in Databases. ECML PKDD 2019. Lecture Notes in Computer Science (pp. 688-703). Springer.
https://doi.org/10.1007/978-3-030-46133-1_41

has been cited by the following article:

• TITLE: The Development Status, Technical Characteristics, and Competitive Dynamics of Blockchain-critical Technologies in China and the USA: From a Patent Perspective

  AUTHORS: Bobo Zhang, Dongphil Chun, Feng Yin, Yaoyao Guo

  KEYWORDS: Blockchain-critical Technologies, Patentometrics, Invention Patents, Technology Life Cycle

  JOURNAL NAME: iBusiness, Vol.15 No.4, December 12, 2023

  ABSTRACT: As an emerging technology, blockchain has attracted significant attention from countries worldwide. Based on patent measurement analysis methods, this paper conducts an in-depth study of invention patents related to crucial blockchain technologies in China and the United States from 2016 to 2022. The study found that the overall trend of the number of patents first increases and then declines, and the layout of the USA in this field is earlier than that of China, but the total number of patents in China exceeds that of the USA; the number of Chinese invention patents located in the core area of the international patent classification (IPC) large group exceeds that of the USA, and there are differences in the types of active technologies between China and the USA; the technology life cycle of China and the USA in this field as a whole has entered the declining period, but segmented technology areas such as privacy protection and cross-chain technology are still in the growth period.