Survey and evaluation of query intent detection methods

  • Brenes D
  • Gayo-Avello D
  • Pérez-González K
  • 76

    Readers

    Mendeley users who have this article in their library.
  • 26

    Citations

    Citations of this article.

Abstract

User interactions with search engines reveal three main underlying intents, namely navigational, informational, and transactional. By providing more accurate results depending on such query intents the performance of search engines can be greatly improved. Therefore, query classification has been an active research topic for the last years. However, while query topic classification has deserved a specific bakeoff, no evaluation campaign has been devoted to the study of automatic query intent detection. In this paper some of the available query intent detection techniques are reviewed, an evaluation framework is proposed, and it is used to compare those methods in order to shed light on their relative performance and drawbacks. As it will be shown, manually prepared goldstandard files are much needed, and traditional pooling is not the most feasible evaluation method. In addition to this, future lines of work in both query intent detection and its evaluation are proposed.

Get free article suggestions today

Mendeley saves you time finding and organizing research

Sign up here
Already have an account ?Sign in

Find this document

Authors

  • David J. Brenes

  • Daniel Gayo-Avello

  • Kilian Pérez-González

Cite this document

Choose a citation style from the tabs below

Save time finding and organizing research with Mendeley

Sign up for free