Technology Trend Forecasting and Technology Opportunity Discovery Based on Text Mining: The Case of Refrigerated Container Technology

Abstract

How to detect potential useful technical information hidden in patents and scientific papers is crucial for technology trend forecasting and potential research opportunities. Using the text mining method to extract hidden technical information is helpful in assisting strategic decision-making and predicting the tendency of technological development. This study proposes a framework to combine patent analysis and scientific paper analysis to predict technology trends and discover technology opportunities. By mining the hidden technical information, we compared an analysis of patents and scientific papers to reveal the technological development trajectory and future development trends and discover potential technological innovation opportunities. First, we extracted the knowledge contained in patents and scientific papers by text mining. Then, we cleaned and coded the data through natural language processing. We used the Latent Dirichlet Allocation topic model to cluster topics and list the multi-dimensional hierarchical structure diagram. We compared and analyzed results, combined them with expert knowledge, and drew a technology roadmap to predict future development trends and discover technological opportunities. Finally, we used refrigerated container technology as an example for validation. Results showed that the framework proposed in this study can directly and comprehensively display the development trend of technology and discover potential technological innovation opportunities to verify the effectiveness of the framework. The proposed method also provides an effective reference and inspiration for future research.