딥러닝 기반 지능형 기술가치평가에 관한 연구: 심층신경망 학습을 통한 정성평가 지표 예측 모형

The technology finance is emerging as a corporate innovation support strategy of government sectors in line with the low-growth economic trends. Therefore, some evaluation agencies are providing a web-based intelligent technology valuation framework, but there still exist limitations. In this study, we propose how to associate deep learning-based estimation results with cash flow calculation logics and how to automate them, without waiting until scoring qualitative factors among experts group. While holding theoretical validity based on technology valuation methodology generally accepted, it provides the demanders' convenience in that it enables commercialization support non-experts to easily identify the values of a technology, by deep learning-based estimation and automated calculation which required expertise knowledge regarding technology assessment. Ultimately, by deep learning-based algorithms we propose the objective, prompt valuation for a firm's technologies or patents will be feasible and it is expected that they minimize the limitations in terms of long-term and high-cost in valuation and support decision-making for technology-driven finance activities.