Trust-Based Recommendations for Scientific Papers Based on the Researcher’s Current Interest

  • Shaikhah Alotaibi
  • Julita Vassileva
Conference paper

DOI: 10.1007/978-3-642-39112-5_96

Part of the Lecture Notes in Computer Science book series (LNCS, volume 7926)
Cite this paper as:
Alotaibi S., Vassileva J. (2013) Trust-Based Recommendations for Scientific Papers Based on the Researcher’s Current Interest. In: Lane H.C., Yacef K., Mostow J., Pavlik P. (eds) Artificial Intelligence in Education. AIED 2013. Lecture Notes in Computer Science, vol 7926. Springer, Berlin, Heidelberg

Abstract

Social reference management systems, such as Mendeley, Zotero or CiteUlike offer many services to their users: finding and managing references, finding other users, grouping users with similar research interests. Harnessing these systems to build personalized recommendations could be useful both for novice researchers (graduate students) and for experienced researchers to keep them updated in their areas. We propose a trust-based hybrid recommender system that infers the user’s ratings of papers and builds a social trust network for an area of recent research interest. We will evaluate the accuracy of predicting the most relevant papers for the current interest and experience level of the researcher and the user satisfaction of the system.

Keywords

recommender system personalization trust and reputation user modeling hybrid approach digital library information retrieval social network 

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Copyright information

© Springer-Verlag Berlin Heidelberg 2013

Authors and Affiliations

  • Shaikhah Alotaibi
    • 1
  • Julita Vassileva
    • 1
  1. 1.Department of Computer ScienceUniversity of SaskatchewanSaskatoonCanada

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