텍스트 마이닝 기법을 활용한 기후변화관련 식품분야 논문초록 분석 = Analysis of the abstracts of research articles in food related to climate change using a text-mining algorithm

다국어 초록 (Multilingual Abstract)

Research articles in food related to climate change were analyzed by implementing a text-mining algorithm, which is one of nonstructural data analysis tools in big data analysis with a focus on frequencies of terms appearing in the abstracts. As a first step, a term-document matrix was established, followed by implementing a hierarchical clustering algorithm based on dissimilarities among the selected terms and expertise in the field to classify the documents under consideration into a few labeled groups. Through this research, we were able to find out important topics appearing in the field of food related to climate change and their trends over past years. It is expected that the results of the article can be utilized for future research to make systematic responses and adaptation to climate change.

참고문헌 (Reference)

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