A Multi-faceted Approach to Query Intent Classification

  • Cristina González-Caro
  • Ricardo Baeza-Yates
Part of the Lecture Notes in Computer Science book series (LNCS, volume 7024)

Abstract

In this paper we report results for automatic classification of queries in a wide set of facets that are useful to the identification of query intent. Our hypothesis is that the performance of single-faceted classification of queries can be improved by introducing information of multi-faceted training samples into the learning process. We test our hypothesis by performing a multi-faceted classification of queries based on the combination of correlated facets. Our experimental results show that this idea can significantly improve the quality of the classification. Since most of previous works in query intent classification are oriented to the study of single facets, these results are a first step to an integrated query intent classification model.

Keywords

Spatial Sensitivity Genre Category Automatic Prediction Query Topic Query Intent 
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 2011

Authors and Affiliations

  • Cristina González-Caro
    • 1
    • 3
  • Ricardo Baeza-Yates
    • 2
    • 3
  1. 1.Universidad Autónoma de BucaramangaBucaramangaColombia
  2. 2.Yahoo! Research BarcelonaBarcelonaSpain
  3. 3.Web Research Group Dept. of Information and CommunicationTechnologies Universitat Pompeu FabraBarcelonaSpain

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