Designing a Neural Question-Answering System for Times of (Information) Pandemics

Johannes Graf, Lancho Gino, Heinrich Kai, Frederik Möller, Schoormann Thorsten, Patrick Zschech

Publikation: Bidrag til tidsskriftTidsskriftartikelForskningpeer review

Abstract

Based on Ingwersen’s cognitive model of information retrieval interaction and natural language processing, this article presents (1) design knowledge in the form of requirements, principles, and features, and (2) an artifact to instantiate the design knowledge into a novel IT artifact for COVID-19 information retrieval. We conducted several evaluation episodes, encompassing technical validations and an experiment, to investigate the artifact’s performance. Our work contributes to managing information and designing artifacts to handle situations of uncertainty.
OriginalsprogEngelsk
TidsskriftInformation Systems Management
Vol/bindLatest articles
Antal sider21
ISSN1058-0530
DOI
StatusUdgivet - 2025

Emneord

  • Design science research
  • Information retrieval
  • Natural language processing
  • Neural QAS
  • Question answering

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