Research on the Detection of Frontier Technologies in Future Industries Based on Multisource Data : A Case Study of Brain-Computer Interfaces

With the intensification of global technological competition, the detection of frontier technologies has become increasingly important in the development of future industries. This study focuses on the development of brain-computer interface (BCI), introducing four data sources: papers, patents, books, and funding projects, to analyze the frontier technologies. Hierarchical Dirichlet Process topic model is used to identify the topics of each data source, and Vector Space Model is applied to fuse the semantic topics of multisource data to determine frontier technology topics. The research identifies eight frontier technology themes in the BCI industry, providing an in-depth interpretation of the characteristics. The results indicate that frontier technology detection is not only a necessary means to ensure technological leadership but also an important driver for promoting high-quality economic development, offering valuable references for the layout and policy formulation of future frontier technologies.