Search result diversification based on hierarchical intents

Sha Hu, Zhicheng Dou*, Xiaojie Wang, Tetsuya Sakai, Ji Rong Wen

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contribution

47 Citations (Scopus)

Abstract

A large percentage of queries issued to search engines are broad or ambiguous. Search result diversification aims to solve this problem, by returning diverse results that can fulfill as many different information needs as possible. Most existing intent-aware search result diversification algorithms formulate user intents for a query as a flat list of subtopics. In this paper, we introduce a new hierarchical structure to represent user intents and propose two general hierarchical diversification models to leverage hierarchical intents. Experimental results show that our hierarchical diversification models outperform state-of-the-art diversification methods that use traditional flat subtopics.

Original languageEnglish
Title of host publicationCIKM 2015 - Proceedings of the 24th ACM International Conference on Information and Knowledge Management
PublisherAssociation for Computing Machinery
Pages63-72
Number of pages10
ISBN (Electronic)9781450337946
DOIs
Publication statusPublished - 2015 Oct 17
Event24th ACM International Conference on Information and Knowledge Management, CIKM 2015 - Melbourne, Australia
Duration: 2015 Oct 192015 Oct 23

Publication series

NameInternational Conference on Information and Knowledge Management, Proceedings
Volume19-23-Oct-2015

Other

Other24th ACM International Conference on Information and Knowledge Management, CIKM 2015
Country/TerritoryAustralia
CityMelbourne
Period15/10/1915/10/23

Keywords

  • Hierarchical diversification
  • Hierarchical intents
  • Search result diversification

ASJC Scopus subject areas

  • Decision Sciences(all)
  • Business, Management and Accounting(all)

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