Heck, Tamara and Hanraths, Oliver and Stock, Wolfgang G. (2011) Expert recommendation for knowledge management in academia. In: ASIST 2011: Association for Information Science and Technology, 9-12 Oct 2011, 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.
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Item Type: | Conference or Workshop Item (Commonwealth Reporting Category E) (Paper) |
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Refereed: | Yes |
Item Status: | Live Archive |
Faculty/School / Institute/Centre: | Historic - Australian Digital Futures Institute (8 Dec 2010 - 6 Jul 2016) |
Faculty/School / Institute/Centre: | Historic - Australian Digital Futures Institute (8 Dec 2010 - 6 Jul 2016) |
Date Deposited: | 19 Mar 2018 05:51 |
Last Modified: | 19 Mar 2018 05:51 |
Uncontrolled Keywords: | Academia; expert recommendation; knowledge management; similarity measurement; social bookmarking |
Fields of Research (2008): | 08 Information and Computing Sciences > 0806 Information Systems > 080699 Information Systems not elsewhere classified |
Identification Number or DOI: | https://doi.org/10.1002/meet.2011.14504801365 |
URI: | http://eprints.usq.edu.au/id/eprint/33358 |
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