Search result diversification via data fusion

Shengli Wu, Chunlan Huang

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

9 Citations (Scopus)

Abstract

In recent years, researchers have investigated search result diversification through a variety of approaches.In such situations, information retrieval systems need to consider both aspects of relevance and diversity for those retrieved documents.On the other hand, previous research has demonstrated that data fusionis useful for improving performance when we are only concerned with relevance.However, it is not clear if it helps when both relevance and diversity are both taken into consideration. In this short paper, we propose a few data fusion methods to tryto improve performance when both relevance and diversity are concerned.Experiments are carried out with 3 groups of top-ranked results submitted to theTREC web diversity task. We find that data fusion is still a useful approach to performance improvement for diversity as for relevance previously.
Original languageEnglish
Title of host publicationUnknown Host Publication
PublisherAssociation for Computing Machinery
Pages827-830
Number of pages4
DOIs
Publication statusPublished - 2014
EventThe 37th International ACM SIGIR Conference on Research and Development in Information Retrieval, SIGIR '14, Gold Coast , QLD, Australia - July 06 - 11, 2014 -
Duration: 1 Jan 2014 → …

Conference

ConferenceThe 37th International ACM SIGIR Conference on Research and Development in Information Retrieval, SIGIR '14, Gold Coast , QLD, Australia - July 06 - 11, 2014
Period1/01/14 → …

Keywords

  • Search result diversification
  • data fusion
  • linear combination
  • weight assignment

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  • Cite this

    Wu, S., & Huang, C. (2014). Search result diversification via data fusion. In Unknown Host Publication (pp. 827-830). Association for Computing Machinery. https://doi.org/10.1145/2600428.2609451