The increasing number of technology transfers from public research institutes in Korea has led to a growing demand for patent recommendation platforms for SMEs. This is because selecting the right technology for commercialization is a critical factor in business success. This study developed a patent recommendation system that uses technology transfer data from the past 10 years to recommend patents that are suitable for SMEs. The system was developed in three stages. First, an item-based collaborative filtering system was developed to recommend patents based on the similarities between the patents that SMEs have previously transferred. Next, a content-based recommendation system based on TF-IDF was developed to analyze patent names and recommend patents with high similarity. Finally, a hybrid system was developed that combines the strengths of both recommendation systems. The experimental results showed that the hybrid system was able to recommend patents that were both similar and relevant to the SMEs' interests. This suggests that the system can be a valuable tool for SMEs that are looking to acquire new technologies.

1. 서 론
    1.1 연구 배경
    1.2 연구개발 필요성
2. 이론적 배경
    2.1 추천 모델링
    2.2 아이템 기반 협업 필터링
    2.3 TF-IDF 모델
    2.4 콘텐츠 기반 추천시스템
    2.5 하이브리드 추천시스템
3. 실험과정
    3.1 추천 모델링 구축을 위한 자료수집 및 전처리
    3.2 아이템 기반 협업 필터링 모델 구축
    3.3 콘텐츠 기반 TF-IDF 분석 모델 구축
    3.4 기술이전 데이터 활용 기술 추천 알고리즘 구축
4. 실험 결과 도출
5. 결 론
    5.1 연구 수행 결과
    5.2 시사점 및 향후 연구방향
Acknowledgement

• Junki Kim(Department of Convergence Management of Technology, Jeonbuk National University) | 김준기 (전북대학교 융합기술경영학과)
• Joonsoo Bae(Department of Convergence Management of Technology, Jeonbuk National University) | 배준수 (전북대학교 융합기술경영학과) Corresponding author
• Yeongheon Song(Department of Convergence Management of Technology, Jeonbuk National University) | 송영헌 (전북대학교 융합기술경영학과)
• Byungho Jeong(Department of Convergence Management of Technology, Jeonbuk National University) | 정병호 (전북대학교 융합기술경영학과)