기술이전 데이터를 활용한 TF-IDF기반 특허추천 알고리즘 연구

• 영문명: A Research on TF-IDF-based Patent Recommendation Algorithm using Technology Transfer Data
• 발행기관: 한국산업경영시스템학회
• 저자명: 김준기 배준수 송영헌 정병호
• 간행물 정보: 『산업경영시스템학회지』제46권 제3호, 78~88쪽, 전체 11쪽
• 주제분류: 공학 > 산업공학
• 파일형태: PDF
• 발행일자: 2023.09.30

영문 초록

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.

목차

1. 서 론

2. 이론적 배경

3. 실험과정

4. 실험 결과 도출

5. 결 론

References

키워드

Recommendation System Patent Recommendation TF-IDF Collaborate filtering Data Mining