Hybrid Method for Personalized Search in Scientific Digital Libraries

  • Thanh-Trung Van
  • Michel Beigbeder
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4919)

Abstract

Users of information retrieval systems usually have to repeat the tedious process of searching, browsing, and refining queries until they find relevant documents. This is because different users have different information needs, but user queries are often short and, hence, ambiguous. In this paper we study personalized search in digital libraries using user profile. The search results could be re-ranked by taking into account specific information needs of different people. We study many methods for this purpose: citation-based method, content-based method and hybrid method. We conducted experiments to compare performances of these methods. Experimental results show that our approaches are promising and applicable in digital libraries.

Keywords

Digital Library Mean Average Precision Information Retrieval System Bibliographic Coupling Citation Database 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.
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Copyright information

© Springer-Verlag Berlin Heidelberg 2008

Authors and Affiliations

  • Thanh-Trung Van
    • 1
  • Michel Beigbeder
    • 1
  1. 1.Centre G2I/Département RIM, Ecole Nationale Supérieure des Mines de Saint EtienneSaint EtienneFrance

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