Alligning Vertical Collection Relevance with User Intent

Ke Zhou, Thomas Demeester, Dong-Phuong Nguyen, Djoerd Hiemstra, Rudolf Berend Trieschnigg

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

3 Citations (Scopus)
20 Downloads (Pure)

Abstract

Selecting and aggregating different types of content from multiple vertical search engines is becoming popular in web search. The user vertical intent, the verticals the user expects to be relevant for a particular information need, might not correspond to the vertical collection relevance, the verticals containing the most relevant content. In this work we propose different approaches to define the set of relevant verticals based on document judgments. We correlate the collection-based relevant verticals obtained from these approaches to the real user vertical intent, and show that they can be aligned relatively well. The set of relevant verticals defined by those approaches could therefore serve as an approximate but reliable ground-truth for evaluating vertical selection, avoiding the need for collecting explicit user vertical intent, and vice versa.
Original languageUndefined
Title of host publicationProceedings of the 23rd ACM Conference on Information and Knowledge Management, CIKM 2014
Place of PublicationNew York
PublisherAssociation for Computing Machinery (ACM)
Pages1915-1918
Number of pages4
ISBN (Print)978-1-4503-2598-1
DOIs
Publication statusPublished - Nov 2014
Event23rd ACM International Conference on Information and Knowledge Management, CIKM 2014 - Shanghai, China
Duration: 3 Nov 20147 Nov 2014
Conference number: 23

Publication series

Name
PublisherACM

Conference

Conference23rd ACM International Conference on Information and Knowledge Management, CIKM 2014
Abbreviated titleCIKM
CountryChina
CityShanghai
Period3/11/147/11/14

Keywords

  • EWI-25655
  • IR-94307
  • METIS-309867

Cite this

Zhou, K., Demeester, T., Nguyen, D-P., Hiemstra, D., & Trieschnigg, R. B. (2014). Alligning Vertical Collection Relevance with User Intent. In Proceedings of the 23rd ACM Conference on Information and Knowledge Management, CIKM 2014 (pp. 1915-1918). New York: Association for Computing Machinery (ACM). https://doi.org/10.1145/2661829.2661941