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  • 1.
    Angelova, Milena
    et al.
    Technical University of Sofia-branch Plovdiv, BUL.
    Vishnu Manasa, Devagiri
    Blekinge Institute of Technology, Faculty of Computing, Department of Computer Science and Engineering.
    Boeva, Veselka
    Blekinge Institute of Technology, Faculty of Computing, Department of Computer Science and Engineering.
    Linde, Peter
    Blekinge Institute of Technology, The Library.
    Lavesson, Niklas
    Blekinge Institute of Technology, Faculty of Computing, Department of Computer Science and Engineering.
    An Expertise Recommender System Based on Data from an Institutional Repository (DiVA)2018In: Proceedings of the 22nd edition of the International Conference on ELectronic PUBlishing, 2018Conference paper (Refereed)
    Abstract [en]

    Finding experts in academics is an important practical problem, e.g. recruiting reviewersfor reviewing conference, journal or project submissions, partner matching for researchproposals, finding relevant M. Sc. or Ph. D. supervisors etc. In this work, we discuss anexpertise recommender system that is built on data extracted from the Blekinge Instituteof Technology (BTH) instance of the institutional repository system DiVA (DigitalScientific Archive). DiVA is a publication and archiving platform for research publicationsand student essays used by 46 publicly funded universities and authorities in Sweden andthe rest of the Nordic countries (www.diva-portal.org). The DiVA classification system isbased on the Swedish Higher Education Authority (UKÄ) and the Statistic Sweden's (SCB)three levels classification system. Using the classification terms associated with studentM. Sc. and B. Sc. theses published in the DiVA platform, we have developed a prototypesystem which can be used to identify and recommend subject thesis supervisors inacademy.

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