RCES: Rapid Cues Exploratory Search Using Taxonomies for COVID-19

Wei Li, Rishi Choudhary, Arjumand Younus, Bruno Ohana, Nicole Baker, Brendan Leen, M. Atif Qureshi

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

Abstract

To assist the COVID-19 focused researchers in life science and healthcare in understanding the pandemic, we present an exploratory information retrieval system called RCES. The system employs a previously developed EVE (Explainable Vector-based Embedding) model using DBpedia and an adopted model using MeSH taxonomies to exploit concept relations related to COVID-19. Various expansion methods are also developed, along with explanations and facets that collectively form rapid cues for a valuable navigational and informed user experience.

Original languageEnglish
Title of host publicationCIKM 2021 - Proceedings of the 30th ACM International Conference on Information and Knowledge Management
PublisherAssociation for Computing Machinery
Pages4739-4743
Number of pages5
ISBN (Electronic)9781450384469
DOIs
Publication statusPublished - 26 Oct 2021
Event30th ACM International Conference on Information and Knowledge Management, CIKM 2021 - Virtual, Online, Australia
Duration: 1 Nov 20215 Nov 2021

Publication series

NameInternational Conference on Information and Knowledge Management, Proceedings

Conference

Conference30th ACM International Conference on Information and Knowledge Management, CIKM 2021
Country/TerritoryAustralia
CityVirtual, Online
Period1/11/215/11/21

Keywords

  • covid-19
  • explanations
  • exploratory search
  • facets
  • query expansion
  • rapid cues

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