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      농식품 R&D 투자방향 설정을 위한 구조적 토픽모델 적용방안 = A study on the application of structural topic model for Korean government agri-food R&D investment strategy

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      https://www.riss.kr/link?id=A108589373

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      Korean national agri-food R&D is a representative area where investment strategy issues such as redundancy in similar fields and functions are always at issue. In the agri-food industry, technological innovation and R&D investment strategies are very ...

      Korean national agri-food R&D is a representative area where investment strategy issues such as redundancy in similar fields and functions are always at issue. In the agri-food industry, technological innovation and R&D investment strategies are very important to simultaneously meet the ambivalent values ​​of reducing inputs to respond to climate change and improving productivity to respond to increased food demand. Therefore, this study sought a new approach that can provide important implications in the stage of setting the direction of investment in agri-food R&D at the government level. When making investment decisions, quantitative secondary data such as discovery and prediction of promising future technologies and portfolio analysis are important along with statistical data. In this study, an application method of a structural topic model was presented in terms of discovering and utilizing promising technologies. This study excluded subjectivity and quantitatively discovered promising technology topics, and analyzed the relative differences between the appearance patterns of topics and the appearance patterns of topics between Korea and foreign countries according to time changes. And it is meaningful in that it visualized and presented the future direction of investment in topics through matrix analysis. In addition, as the analysis results are confirmed to be similar to the direction of the higher policy, it is believed that the approach proposed in this study can be used as a useful tool in setting the direction of future agri-food R&D investment.

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