Angelova , Milena and Devagiri , Vishnu , and Boeva , Veselka and Linde , Peter and Lavesson , Niklas - An Expertise Recommender System Based on Data from an Institutional Repository (DiVA)

elpub:4605 - ELectronic PUBlishing, June 20, 2018, Connecting the Knowledge Commons: From Projects to Sustainable Infrastructure
An Expertise Recommender System Based on Data from an Institutional Repository (DiVA)

Authors: Angelova , Milena and Devagiri , Vishnu , and Boeva , Veselka and Linde , Peter and Lavesson , Niklas

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.


Source : oai:HAL:hal-01816680v1
DOI : 10.4000/proceedings.elpub.2018.17
Volume: Connecting the Knowledge Commons: From Projects to Sustainable Infrastructure
Section: Long Papers
Published on: June 20, 2018
Submitted on: June 20, 2018
Keywords: data mining, DiVA, expertise retrieval, knowledge management, natural language processing, [ SHS.INFO ] Humanities and Social Sciences/Library and information sciences


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