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http://dx.doi.org/10.5762/KAIS.2021.22.3.568

Investigating the Characteristics of Academia-Industrial Cooperation-based Patents for their Long-term Use  

Park, Sang-Young (Department of Industrial Engineering, Ajou University)
Choi, Youngjae (Department of Artificial Intelligence, Ajou University)
Lee, Sungjoo (Department of Industrial Engineering, Ajou University)
Publication Information
Journal of the Korea Academia-Industrial cooperation Society / v.22, no.3, 2021 , pp. 568-578 More about this Journal
Abstract
Patents that are research results from industry-university cooperation (IUC) are a source of innovation, and play an important role in economic growth, such as technology transfer and commercialization. For this reason, there are many efforts to revitalize IUC, but in general, company patents are achievements that can be commercialized, rather than research achievements, so not all patents are used for business, even after their creation as the outcome of IUC. Therefore, this research supports the design of measures in which IUC can ultimately be linked to successful utilization of patents by identifying the purposes of IUC, even after it has been successfully promoted, and patents have been filed as a result. To this end, first, the patents registered for industry-academia cooperation in the United States are collected, and second, a predictive model is designed, with unexpired and expired patents predicted using machine learning techniques. The final identified patents are intended to derive available factors in terms of marketability and technicality. This study is expected to help predict the utilization of unexpired and expired patents, and is expected to contribute to setting goals for research results from technical cooperation between corporate and university officials planning early IUC.
Keywords
Industry-University Cooperation(IUC); Alive Patent; Expired Patent; Machine learning; Patent value verification;
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