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

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Intelligent Information and Database Systems (ACIIDS 2020)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 12033))

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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.

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Acknowledgment

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

Author information

Authors and Affiliations

  1. University of Education, Hue University, Hue, Vietnam

    Tuong Tri Nguyen

  2. Faculty of Computer Science and Management, Wroclaw University of Science and Technology, Wroclaw, Poland

    Ngoc Thanh Nguyen

  3. Department of Computer Engineering, Yeungnam University, Gyeongsan, South Korea

    Dinh Tuyen Hoang

  4. Quang Binh University, Dong Hoi, Vietnam

    Dinh Tuyen Hoang & Van Cuong Tran

Authors
  1. Tuong Tri Nguyen
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  2. Ngoc Thanh Nguyen
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  3. Dinh Tuyen Hoang
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  4. Van Cuong Tran
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Corresponding author

Correspondence to Tuong Tri Nguyen .

Editor information

Editors and Affiliations

  1. Department of Applied Informatics, Wrocław University of Science and Technology, Wrocław, Poland

    Ngoc Thanh Nguyen

  2. King Mongkut's Institute of Technology Ladkrabang, Bangkok, Thailand

    Kietikul Jearanaitanakij

  3. Faculty of Computer Science and Information, University Teknologi Malaysia, Kuala Lumpur, Malaysia

    Ali Selamat

  4. Department of Applied Informatics, Wrocław University of Science and Technology, Wrocław, Poland

    Bogdan Trawiński

  5. King Mongkut's Institute of Technology Ladkrabang, Bangkok, Thailand

    Suphamit Chittayasothorn

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Nguyen, T.T., Nguyen, N.T., Hoang, D.T., Tran, V.C. (2020). Predicting Research Collaboration Trends Based on the Similarity of Publications and Relationship of Scientists. In: Nguyen, N., Jearanaitanakij, K., Selamat, A., Trawiński, B., Chittayasothorn, S. (eds) Intelligent Information and Database Systems. ACIIDS 2020. Lecture Notes in Computer Science(), vol 12033. Springer, Cham. https://doi.org/10.1007/978-3-030-41964-6_2

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  • DOI: https://doi.org/10.1007/978-3-030-41964-6_2

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-41963-9

  • Online ISBN: 978-3-030-41964-6

  • eBook Packages: Computer ScienceComputer Science (R0)

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