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  1. Home > Articles & Issues >
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  3. An Expertise Recomme ...
Conference paper

An Expertise Recommender System Based on Data from an Institutional Repository (DiVA)

Milena Angelova (1), Vishnu Devagiri (2), Veselka Boeva (2), Peter Linde (2), Niklas Lavesson (2)
(1) Technical University of Sofia [Bulgaria]
(2) Blekinge Institute of Technology
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Publication details
Submitted on
June 20, 2018
Accepted on
June 20, 2018
Published on
June 20, 2018
Last modified on
March 31, 2025
Proceedings 1
Connecting the Knowledge Commons: From Projects to Sustainable Infrastructure
Long Papers
DOI
10.4000/proceedings.elpub.2018.17
License
Attribution 4.0 International (CC BY 4.0)
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An Expertise Recommender System Based on Data from an Institutional Repository (DiVA)

Milena Angelova (1), Vishnu Devagiri (2), Veselka Boeva (2), Peter Linde (2), Niklas Lavesson (2)
(1) Technical University of Sofia [Bulgaria]
(2) Blekinge Institute of Technology
Abstract
Finding experts in academics is an important practical problem, e.g. recruiting reviewers for reviewing conference, journal or project submissions, partner matching for research proposals, finding relevant M. Sc. or Ph. D. supervisors etc. In this work, we discuss an expertise recommender system that is built on data extracted from the Blekinge Institute of Technology (BTH) instance of the institutional repository system DiVA. The developed prototype system is evaluated and validated on information extracted from the BTH DiVA installation, concerning thesis supervision of researchers affiliated with BTH. The extracted DiVA classification terms are used to build an ontology that conceptualizes the thesis domain supported by the university. The supervisor profiles of the tutors affiliated with the BTH are constructed based on the extracted DiVA data. These profiles can further be used to identify and recommend relevant subject thesis supervisors.
Keywords
  • [SHS.INFO]Humanities and Social Sciences/Library and information sciences
  • natural language processing
  • data mining
  • DiVA
  • expertise retrieval
  • knowledge management
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