Technology opportunity discovery of proton exchange membrane fuel cell from the perspective of papers-patents correlation analysis

Papers and patents can respectively present the latest progress of scientific research and technological development. Combining the two for correlation analysis has certain reference significance for technology opportunity discovery. Therefore, this paper proposes a method for technology opportunity discovery of proton exchange membrane fuel cell from the perspective of papers-patents correlation analysis. Firstly, papers and patent data are collected from papers and patent databases and the LDA model is applied to extract paper and patent topics. Secondly, the indicators of topic heat and novelty are calculated to select high-value paper topics. After that, the similarity analysis between high-value paper topics and all patent topics is considered to select the patent topics with development potential. Finally, the patent texts with high relevance to these patent topics with development potential are positioned. The technical keywords in them are extracted by text mining tool and classified into innovation dimensions according to their attributes and the TEMPEST model. After that, the innovation rules in the SCAMPER model are introduced to combine with the technical keywords in each innovation dimension to identify specific technology opportunities. An empirical study on the technology of proton exchange membrane fuel cell provides sufficient evidence of the method’s ability to discover technology opportunities. This paper contributes by generating four specific technology opportunities, which can make up for the existing defects of proton exchange membrane fuel cells and provide useful guidance for companies to carry out technological innovation.