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Predicting Research Collaboration Trends Based on the Similarity of Publications and Relationship of Scientists

  • Tuong Tri NguyenEmail author
  • Ngoc Thanh Nguyen
  • Dinh Tuyen Hoang
  • Van Cuong Tran
Conference paper
  • 294 Downloads
Part of the Lecture Notes in Computer Science book series (LNCS, volume 12033)

Abstract

Nowadays, collaboration is indispensable in solving increasingly complex problems. In the academic context, research collaboration influences many aspects of research problems approached. The research collaboration is beneficial for scientists, especially early-career scientists, to determine potential successful collaborations. Predicting the trend of collaboration is an important step in improving the quality of research collaboration between scientists. In this study, we propose a method for predicting research collaboration trends by taking into account the research similarity and the relationship between scientists. The research similarity is computed by considering the author’s profiles. The co-author graph is built to explore new collaborators based on the connections weigh between scientists. We are currently in the process of developing a real system and our system shows promising results in predicting the potential success collaborators.

Keywords

Research collaboration Collaboration Research trend 

Notes

Acknowledgment

This study is funded by Research Project No. DHH2018-03-109 of Hue University, Vietnam.

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Copyright information

© Springer Nature Switzerland AG 2020

Authors and Affiliations

  • Tuong Tri Nguyen
    • 1
    Email author
  • Ngoc Thanh Nguyen
    • 2
  • Dinh Tuyen Hoang
    • 3
    • 4
  • Van Cuong Tran
    • 4
  1. 1.University of Education, Hue UniversityHueVietnam
  2. 2.Faculty of Computer Science and ManagementWroclaw University of Science and TechnologyWroclawPoland
  3. 3.Department of Computer EngineeringYeungnam UniversityGyeongsanSouth Korea
  4. 4.Quang Binh UniversityDong HoiVietnam

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