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Predicting link of R&D network to stimulate collaboration among education, industry, and research
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Mi-yeon Park (Process of technology policy cooperation, Yonsei University)
Sangheon Lee (Department of Information and Industrial Engineering, Yonsei University)
Guocheng Jin (Department of Information and Industrial Engineering, Yonsei University)
Hongme Shen (Department of Information and Industrial Engineering, Yonsei University)
Wooju Kim (Department of Information and Industrial Engineering, Yonsei University)
Vol. 21, No. 3, Page: 59 ~ 75
10.13088/jiis.2015.21.3.59
Keywords
Industry-university, Network analysis, activation, National R&D, link prediction
Abstract
The recent global trends display expansion and growing solidity in both cooperative collaboration between industry, education, and research and R&D network systems. A greater support for the network and cooperative research sector would open greater possibilities for the evolution of new scholar and industrial fields and the development of new theories evoked from synergized educational research.<br /> Similarly, the national need for a strategy that can most efficiently and effectively support R&D network that are established through the government’s R&D project research is on the rise.<br /> Despite the growing urgency, due to the habitual dependency on simple individual personal information data regarding R&D industry participants and generalized statistical data references, the policies concerning network system are disappointing and inadequate.<br /> Accordingly, analyses of the relationships involved for each subject who is participating in the R&D industry was conducted and on the foundation of an educational-industrial-research network system, possible changes within and of the network that may arise were predicted.<br /> To predict the R&D network transitions, Common Neighbor and Jaccard’s Coefficient models were designated as the basic foundational models, upon which a new prediction model was proposed to address the limitations of the two aforementioned former models and to increase the accuracy of Link Prediction, with which a comparative analysis was made between the two models. Through the effective predictions regarding R&D network changes and transitions, such study result serves as a stepping-stone for an establishment of a prospective strategy that supports a desirable educational-industrial-research network and proposes a measure to promote the national policy to one that can effectively and efficiently sponsor integrated R&D industries.<br /> Though both weighted applications of Common Neighbor and Jaccard’s Coefficient models provided positive outcomes, improved accuracy was comparatively more prevalent in the weighted Common Neighbor. An un-weighted Common Neighbor model predicted 650 out of 4,136 whereas a weighted Common Neighbor model predicted 50 more results at a total of 700 predictions. While the Jaccard’s model demonstrated slight performance improvements in numeric terms, the differences were found to be insignificant.
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산학연 협업 활성화를 위한 R&D 네트워크 연결 예측 연구
박미연 (연세대학교 기술정책협동과)
이상헌 (연세대학교 정보산업공학과)
김국성 (연세대학교 정보산업공학과)
심홍매 (연세대학교 정보산업공학과)
김우주 (연세대학교 정보산업공학과 교수)
Keywords
산학연, 네트워크 분석, 활성화, 국가 R&D, 관계 예측
Abstract
최근 전세계적으로 R&D 네트워크 및 산학연 협력 등을 강화하고 있는 추세이다. 네트워크 및 협업연구 부문에 대한 지원이 증가하면 학제간 융합 연구를 통한 새로운 이론의 창출과 새로운 학문․사업 분야로의 확장 가능성을 높일 수 있다. <br /> 우리나라도 정부의 R&D 과제 수행을 통해 형성된 R&D 네트워크를 효율적으로 지원할 수 있는 전략의 필요성이 증대되고 있다. 그럼에도 불구하고 우리나라는 국가 R&D 사업 참여자에 대한 개별인력정보와 일반화된 통계 자료에만 의존하여 네트워크 관점에서의 정책은 미흡한 실정이다. 이에 따라 R&D 사업에 참여하는 각 주체들 간의 관계를 분석하고 산학연 R&D 네트워크를 기반으로 향후 발생할 수 있는 네트워크의 변화를 예측하고자 한다. R&D 네트워크 변화 예측을 위해 Common Neighbor 모형과 Jaccard’s Coefficient 모형을 기반 모델로서 채택하고자 하며, 이들의 한계점을 보완하고 Link Prediction 정확도를 향상시킨 새로운 예측 모형을 제안하고 이들간의 비교분석 결과를 도출하고자 한다. 이와 같은 연구 결과는 향후 R&D 네트워크의 변화에 대한 효과적인 예측을 통해 선제적인 산학연 사업 지원 전략을 수립하고, 융합 R&D사업 등을 효과적으로 지원할 수 있는 국가 정책을 도모하기 위한 방안을 제시한다는 점에서 의의가 있다. 본 연구 결과 가중치의 적용은 Common Neighbor 모형과 Jaccard’s coefficient 모형 모두에서 긍정적인 성과를 나타냈는데 상대적으로는 가중치가 적용된 Common Neighbor 모형에서의 정확도가 더 개선된 것으로 도출되었다. 즉, Common Neighbor 모형에서는 4,136개 중 650개를 예측한 반면, 가중치를 적용한 Common Neighbor 모형에서는50개의 정답이 증가한 700개를 예측하는 효과를 보였다. 한편, 상대적으로 Jaccard 계수의 경우는 약간의 성능 개선은 있으나 그 차이가 미미한 것으로 나타났다.
Cite this article
JIIS(APA) Style
Park, M.-y., Lee, S., Jin, G., Shen, H., & Kim, W. (2015). Predicting link of R&D network to stimulate collaboration among education, industry, and research. Journal of Intelligence and Information Systems, 21(3), 59-75.

IEEE Style
Mi-yeon Park, Sangheon Lee, Guocheng Jin, Hongme Shen, and Wooju Kim, "Predicting link of R&D network to stimulate collaboration among education, industry, and research", Journal of Intelligence and Information Systems, vol. 21, no. 3, pp. 59~75, 2015.

ACM Style
Park, M.-y., Lee, S., Jin, G., Shen, H., & Kim, W., 2015. Predicting link of R&D network to stimulate collaboration among education, industry, and research. Journal of Intelligence and Information Systems. 21, 3, 59--75.
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@article{Park:JIIS:2015:624,
author = {Park, Mi-yeon and Lee, Sangheon and Jin, Guocheng and Shen, Hongme and Kim, Wooju},
title = {Predicting link of R&D network to stimulate collaboration among education, industry, and research},
journal = {Journal of Intelligence and Information Systems},
issue_date = {September 2015},
volume = {21},
number = {3},
month = Sep,
year = {2015},
issn = {2288-4866},
pages = {59--75},
url = {http://dx.doi.org/10.13088/jiis.2015.21.3.59 },
doi = {10.13088/jiis.2015.21.3.59},
publisher = {Korea Intelligent Information System Society},
address = {Seoul, Republic of Korea},
keywords = { Industry-university, Network analysis, activation, National R&D and link prediction },
}
%0 Journal Article
%1 624
%A Mi-yeon Park
%A Sangheon Lee
%A Guocheng Jin
%A Hongme Shen
%A Wooju Kim
%T Predicting link of R&D network to stimulate collaboration among education, industry, and research
%J Journal of Intelligence and Information Systems
%@ 2288-4866
%V 21
%N 3
%P 59-75
%D 2015
%R 10.13088/jiis.2015.21.3.59
%I Korea Intelligent Information System Society