Detecting Technology Opportunities Based On Papers And Patents

With the rapid development of the informatization?digitization?networking environment, the speed of scientific technological revolution and market demand is increasing. The industry competition is more and more relative to technology competition, which put forward higher requirement for grasping technological and industrial revolution. Technology opportunities is one type of important factors that affects all technology innovation activities,besides that, it is one key factor for enterprise implementing technology innovation activities. It provides possibilities for technology innovation.At present, the most analysis about technology opportunities using patent data, a small number of analysis using paper data. As we all know, paper data focuses on basic scientific research and patent data focuses on technological research, but sometimes technological innovations are related to scientific output. Identifying the potential academic research domain and then generating crucial technologies is one of the most important challenges in technology and innovation management field. Using both paper data and patent data can grasp more technology opportunities. Up to now, technology opportunities analysis mainly concentrated on citation network and vector space model. This paper had the following innovations: We used Subject-Acition-Object(SAO) semantic analysis method to analysed technology opportunities. This method could avoid time lag problem about direct-citation analysis and the subjective factor about vector space model. We used word sense disambiguation method to improve the accuracy of SAO structures. The analysis procedure is: Firstly, paper data are retrieved from Web of Science(Wo S) database and patent data are retrieved from Derwent Innovations Index(DII) database. Then, extracting the subject-action-object(SAO) structures from the titles and abstracts of paper data and patent data. Then, we used word sense disambiguation method which improved the accuracy of SAO structures. Then, Eclipse tool computed the similarities about the SAO structures. After that, we need compute the similarities between papers and between patents. Then, we put the similarity matrix to the Statistics Analysis System(SAS)tool for computing subjects of papers and patents. Then, identifying the technology opportunities. Finally, we used the perovskite solar cells data as the case study, it confirmed the effectiveness and scientificity of our method.This paper has overcome the shortcomes about the previous studies, it enriched the technology opportunities analysis system. Additionally, it provided some guidance for determining the R&D goal for companys. Besides that, it provided some policy making suggestions for the government. In a word, it promotes us making fully use of the existing technologies and generating more new technologies.