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.

This study identifies the commercialization success factors that can be an important indicator for the transfer and commercialization of national R&D results in the agricultural sector. Unlike other industries, the agricultural sector has a non-systematically scaled and processed industrial structure, and R&D is led by government rather than the private sector. Although the quantitative performance of national agricultural R&D, especially the number of patents and publications, has increased rapidly with the quantitative expansion of the government R&D budget, the technology commercialization of the results of agricultural R&D has been accompanied by difficulties for SMEs. Therefore, this study summarized the success factors for commercialization of state-owned technologies presented in previous studies, and based on them, analysed the success factors for commercialization specific to the agricultural sector. It also conducted a questionnaire survey using Delphi and focus group interviews (FGI) with experts from academia, research and industry, and a survey of agricultural companies to derive success factors for commercialization in the agricultural sector using logistic regression analysis. As a result, five indicators with positive correlation and three indicators with negative correlation within technology characteristics, suppliers, adopters, policy and market factors were finally derived as key factors for agricultural commercialization. In the future, it is expected that independent factor analysis of the food and seed sectors, which have independent industry characteristics from the agricultural sector, will be needed.

기존 건축물의 구조 안전성평가와 보수 보강 시에는 해당 건축물의 상태를 정확히 알기 위해 현장 또는 실험실에서의 실험을 수행하는 경우가 많고 최초설계 단계와 다르게 시공된 건축물의 실제 상태 등을 구조해석 모델에 반영하게 된다. 이 경우, 각종 실험값을 전통적인 통계학적 방법은 구조기술자가 지닌 경험과 지식은 구조모델링 및 해석에서 아무런 가치를 더할 수가 없다. 본 논문은 현장 및 실험실에서 얻은 단순한 실험값을 구조기술자의 축적된 경험과 지식을 변수로 활용하여 보다 유효하게 구조해석 모델에 필요한 데이터로 개선하는 방법으로서 통계학적인 베이스 경신법을 이용한 안전성평가 방법에 대해 살펴보았다. 구조기술자의 적절한 판단이 변수로서 포함되면 적은 개수의 샘플 수로도 비교적 정확한 값의 최종 예측값을 산정할 수 있어 전통적인 통계학적 접근에 비해 보다 실제값에 근접한 예측값을 구할 수 있는 것을 확인하였다.