Recommending Better Queries from Click-Through Data

  • Georges Dupret
  • Marcelo Mendoza
Part of the Lecture Notes in Computer Science book series (LNCS, volume 3772)


We present a method to help a user redefine a query based on past users experience, namely the click-through data as recorded by a search engine. Unlike most previous works, the method we propose attempts to recommend better queries rather than related queries. It is effective at identifying query specialization or sub-topics because it take into account the co-occurrence of documents in individual query sessions. It is also particularly simple to implement.


Search Engine Pointed Query Query Expansion Recommendation Algorithm Original Query 
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 2005

Authors and Affiliations

  • Georges Dupret
    • 1
  • Marcelo Mendoza
    • 2
  1. 1.Center for Web Research, Department of Computer ScienceUniversidad de Chile 
  2. 2.Department of Computer ScienceUniversidad de Valparaiso 

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