• Title/Summary/Keyword: Researcher

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Researcher Clustering Technique based on Weighted Researcher Network (가중치 정보를 가진 연구자 네트워크 기반의 연구자 클러스터링 기법)

  • Mun, Hyeon Jeong;Lee, Sang Min;Woo, Yong Tae
    • Journal of Korea Society of Digital Industry and Information Management
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    • v.5 no.2
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    • pp.1-11
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    • 2009

  • This study presents HCWS algorithm for researcher grouping on a weighted researcher network. The weights represent intensity of connections among researchers based on the number of co-authors and the number of co-authored research papers. To confirm the validity of the proposed technique, this study conducted an experimentation on about 80 research papers. As a consequence, it is proved that HCWS algorithm is able to bring about more realistic clustering compared with HCS algorithm which presents semantic relations among researchers in simple connections. In addition, it is found that HCWS algorithm can address the problems of existing HCS algorithm; researchers are disconnected since their connections are classified as weak even though they are strong, and vise versa. The technique described in this research paper can be applied to efficiently establish social networks of researchers considering relations such as collaboration histories among researchers or to create communities of researchers.

  • https://doi.org/10.17662/ksdim.2009.5.2.001 인용 PDF

Rainfall Frequency Atlas of Korea

  • Kim, Kyu-Ho;Kim, Yang-Su;Lee, Jin--Won;Kim, Sung;Seoh, Byung-Ha
    • Korean Journal of Hydrosciences
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    • v.1
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    • pp.39-48
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    • 1990

  • The objective of this study is to develop

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Researcher and Research Area Recommendation System for Promoting Convergence Research Using Text Mining and Messenger UI (텍스트 마이닝 방법론과 메신저UI를 활용한 융합연구 촉진을 위한 연구자 및 연구 분야 추천 시스템의 제안)

  • Yang, Nak-Yeong;Kim, Sung-Geun;Kang, Ju-Young
    • The Journal of Information Systems
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    • v.27 no.4
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    • pp.71-96
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    • 2018

  • Purpose Recently, social interest in the convergence research is at its peak. However, contrary to the keen interest in convergence research, an infrastructure that makes it easier to recruit researchers from other fields is not yet well established, which is why researchers are having considerable difficulty in carrying out real convergence research. In this study, we implemented a researcher recommendation system that helps researchers who want to collaborate easily recruit researchers from other fields, and we expect it to serve as a springboard for growth in the convergence research field. Design/methodology/approach In this study, we implemented a system that recommends proper researchers when users enter keyword in the field of research that they want to collaborate using word embedding techniques, word2vec. In addition, we also implemented function of keyword suggestions by using keywords drawn from LDA Topicmodeling Algorithm. Finally, the UI of the researcher recommendation system was completed by utilizing the collaborative messenger Slack to facilitate immediate exchange of information with the recommended researchers and to accommodate various applications for collaboration. Findings In this study, we validated the completed researcher recommendation system by ensuring that the list of researchers recommended by entering a specific keyword is accurate and that words learned as a similar word with a particular researcher match the researcher's field of research. The results showed 85.89% accuracy in the former, and in the latter case, mostly, the words drawn as similar words were found to match the researcher's field of research, leading to excellent performance of the researcher recommendation system.

  • https://doi.org/10.5859/KAIS.2018.27.4.71 인용 PDF KSCI HTML