Expert recommendation for knowledge management in academia

Paper


Heck, Tamara, Hanraths, Oliver and Stock, Wolfgang G.. 2011. "Expert recommendation for knowledge management in academia." ASIST 2011: Association for Information Science and Technology Annual Meeting. New Orleans, United States 09 - 12 Oct 2011 United States. https://doi.org/10.1002/meet.2011.14504801365
Paper/Presentation Title

Expert recommendation for knowledge management in academia

Presentation TypePaper
AuthorsHeck, Tamara (Author), Hanraths, Oliver (Author) and Stock, Wolfgang G. (Author)
Journal or Proceedings TitleProceedings of the ASIST Annual Meeting 2011
Journal Citation48 (1), pp. 1-4
Number of Pages4
Year2011
Place of PublicationUnited States
Digital Object Identifier (DOI)https://doi.org/10.1002/meet.2011.14504801365
Web Address (URL) of Paperhttps://onlinelibrary.wiley.com/doi/abs/10.1002/meet.2011.14504801365
Conference/EventASIST 2011: Association for Information Science and Technology Annual Meeting
Event Details
ASIST 2011: Association for Information Science and Technology Annual Meeting
Parent
ASIST Annual Meeting
Event Date
09 to end of 12 Oct 2011
Event Location
New Orleans, United States
Abstract

Recommendation systems are not only important in ecommerce, but in academia as well: They support scientists in finding relevant literature and also potential collaboration partners. It is essential that such a recommendation system proposes the most relevant people. Scientometric similarity measurements like co-citation and bibliographic coupling analysis have proved to give a good representation of research activities and hence it can be said that they put authors with similar research together and detect possible collaborations. Our aim is to implement a recommendation system for a target author who searches for collaboration colleagues. The research question is: 1) Can we propose a relevant author cluster for a target scientist? Furthermore we try to apply user data from the social bookmarking system CiteULike. The second research question is: 2) Is this user-based data also relevant for our target scientist and does it recommend different results? Our first outcomes of this work in progress are evaluated by our target authors. Copyright notice continues right here.

KeywordsAcademia; expert recommendation; knowledge management; similarity measurement; social bookmarking
ANZSRC Field of Research 2020460999. Information systems not elsewhere classified
Byline AffiliationsHeinrich Heine University Düsseldorf, Germany
Heinrich Heine University, Germany
Institution of OriginUniversity of Southern Queensland
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