A Vector Space Model for Ranking Entities and Its Application to Expert Search

  • Gianluca Demartini
  • Julien Gaugaz
  • Wolfgang Nejdl
Part of the Lecture Notes in Computer Science book series (LNCS, volume 5478)


Entity Ranking has recently become an important search task in Information Retrieval. The goal is not to find documents matching query terms, but, instead, finding entities. In this paper we propose a formal model to search entities as well as a complete Entity Ranking system, providing examples of its application to the enterprise context. We experimentally evaluate our system on the Expert Search task in order to show how it can be adapted to different scenarios. The results show that combining simple IR techniques we improve of 53% in terms of P@10 over our baseline.


Cosine Similarity Latent Semantic Analysis Mean Average Precision Vector Space Model Query Vector 
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 2009

Authors and Affiliations

  • Gianluca Demartini
    • 1
  • Julien Gaugaz
    • 1
  • Wolfgang Nejdl
    • 1
  1. 1.L3S Research CenterLeibniz Universität HannoverGermany

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