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A Modular Diversity Based Reviewer Recommendation System

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Intelligent Information and Database Systems (ACIIDS 2020)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 1178))

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Abstract

A new approach for solving the problem of reviewer recommendation for conference or journal submissions is proposed. Instead of assigning one best reviewer and then looking for a second-best match, we want to start from a single reviewer and look for a diverse group of other possible candidates, that would complement the first one in order to cover multiple areas of the review. We present the idea of an overall modular system for determining a grouping of reviewers, as well as three modules for such a system: a keyword-based module, a social graph module, and a linguistic module. The added value of modular diversity is seen primarily for larger groups of reviewers. The paper also contains a proof of concept of the method.

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Notes

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  2. 2.

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Acknowledgments

This research within Polish-German cooperation program is financially supported by the German Academic Exchange Service (DAAD) under grant PPP 57391625 and by the Wrocław University of Science and Technology under project 0401/0221/18. This research was also financially supported by the Brazilian National Council for Scientific and Technological Development (CNPq) – Science without Borders Program.

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Authors and Affiliations

  1. Wroclaw University of Science and Technology, 50-370, Wroclaw, Poland

    Marcin Maleszka, Bernadetta Maleszka & Dariusz Król

  2. Wroclaw University of Economics, Wroclaw, Poland

    Marcin Hernes

  3. WWU Munster, Munster, Germany

    Denis Mayr Lima Martins, Leschek Homann & Gottfried Vossen

Authors
  1. Marcin Maleszka
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  2. Bernadetta Maleszka
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  3. Dariusz Król
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  4. Marcin Hernes
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  5. Denis Mayr Lima Martins
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  6. Leschek Homann
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  7. Gottfried Vossen
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Corresponding author

Correspondence to Marcin Maleszka .

Editor information

Editors and Affiliations

  1. Kielce University of Technology, Kielce, Poland

    Paweł Sitek

  2. Wrocław University of Science and Technology, Wrocław, Poland

    Marcin Pietranik

  3. Wrocław University of Science and Technology, Wrocław, Poland

    Marek Krótkiewicz

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

    Chutimet Srinilta

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Maleszka, M. et al. (2020). A Modular Diversity Based Reviewer Recommendation System. In: Sitek, P., Pietranik, M., Krótkiewicz, M., Srinilta, C. (eds) Intelligent Information and Database Systems. ACIIDS 2020. Communications in Computer and Information Science, vol 1178. Springer, Singapore. https://doi.org/10.1007/978-981-15-3380-8_48

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  • DOI: https://doi.org/10.1007/978-981-15-3380-8_48

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  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-15-3379-2

  • Online ISBN: 978-981-15-3380-8

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