Explainable AI (XAI) is an approach that leverages artificial intelligence to support human decision-making. Recently, governments of several countries including Korea are attempting objective evidence-based analyses of R&D investments with returns by analyzing quantitative data. Over the past decade, governments have invested in relevant researches, allowing government officials to gain insights to help them evaluate past performances and discuss future policy directions. Compared to the size that has not been used yet, the utilization of the text information (accumulated in national DBs) so far is low level. The current study utilizes a text mining strategy for monitoring innovations along with a case study of smart-farms in the Honam region.

1. 서 론
2. 선행 연구
3. 연구방법
    3.1 분석 데이터
    3.2 기계학습 및 해석 방법론
    3.3 동시출현 네트워크
4. 분석 및 결과
5. 결 론
References

• Jung Sun Lim(한국과학기술정보연구원) | 임정선 Corresponding Author
• Seoung Hun Bae(한국국토정보공사 공간정보연구원) | 배성훈