Abstract This study investigates the development of Chinese 3D printing patents, focusing on application trends, geographic distribution, applicants, and International Patent Classifications. To uncover the underlying technical themes, we applied text mining techniques, specifically Latent Dirichlet Allocation, for topic recognition and hidden Markov models to trace their evolution over time. The analysis highlights how key technical topics have shifted, while also reflecting the rapid growth of 3D printing technology in China since 2013 and the notable rise in patent activity from 2019 onward. These findings provide useful insights for governments, enterprises, and research institutes seeking to understand market dynamics and the trajectory of 3D printing development.
Gu et al. (Sun,) studied this question.