Query recommendation using query logs in search engines

  • Authors:
  • Ricardo Baeza-Yates;Carlos Hurtado;Marcelo Mendoza

  • Affiliations:
  • Center for Web Research, Department of Computer Science, Universidad de Chile;Center for Web Research, Department of Computer Science, Universidad de Chile;Department of Computer Science, Universidad de Valparaiso

  • Venue:
  • EDBT'04 Proceedings of the 2004 international conference on Current Trends in Database Technology
  • Year:
  • 2004

Quantified Score

Hi-index 0.00

Visualization

Abstract

In this paper we propose a method that, given a query submitted to a search engine, suggests a list of related queries The related queries are based in previously issued queries, and can be issued by the user to the search engine to tune or redirect the search process The method proposed is based on a query clustering process in which groups of semantically similar queries are identified The clustering process uses the content of historical preferences of users registered in the query log of the search engine The method not only discovers the related queries, but also ranks them according to a relevance criterion Finally, we show with experiments over the query log of a search engine the effectiveness of the method.