Vertical selection in the information domain of children

Sergio Duarte Torres, Djoerd Hiemstra, Theo W.C. Huibers

Research output: Chapter in Book/Report/Conference proceedingConference contributionAcademicpeer-review

4 Citations (Scopus)
36 Downloads (Pure)

Abstract

In this paper we explore the vertical selection methods in aggregated search in the specific domain of topics for children between 7 and 12 years old. A test collection consisting of 25 verticals, 3.8K queries and relevant assessments for a large sample of these queries mapping relevant verticals to queries was built. We gather relevant assessment by envisaging two aggregated search systems: one in which the Web vertical is always displayed and in which each vertical is assessed independently from the web vertical. We show that both approaches lead to a different set of relevant verticals and that the former is prone to bias of visually oriented verticals. In the second part of this paper we estimate the size of the verticals for the target domain. We show that employing the global size and domain specific size estimation of the verticals lead to significant improvements when using state-of-the art methods of vertical selection. We also introduce a novel vertical and query representation based on tags from social media and we show that its use lead to significant performance gains.
Original languageUndefined
Title of host publicationProceedings of the 13th ACM/IEEE-CS Joint Conference on Digital Libraries, JDCL 2013
Place of PublicationNew York
PublisherAssociation for Computing Machinery (ACM)
Pages57-66
Number of pages10
ISBN (Print)978-1-4503-2077-1
DOIs
Publication statusPublished - Jul 2013

Publication series

Name
PublisherACM

Keywords

  • EWI-23993
  • CR-H.3.3
  • Social Media
  • vertical selection
  • IR-88361
  • Aggregated search
  • Evaluation
  • METIS-300171
  • Children

Cite this

Duarte Torres, S., Hiemstra, D., & Huibers, T. W. C. (2013). Vertical selection in the information domain of children. In Proceedings of the 13th ACM/IEEE-CS Joint Conference on Digital Libraries, JDCL 2013 (pp. 57-66). New York: Association for Computing Machinery (ACM). https://doi.org/10.1145/2467696.2467714