Answering comparative questions: Better than ten-blue-links?

Matthias Schildwächter, Matthias Hagen, Alexander Bondarenko, Chris Biemann, Julian Zenker, Alexander Panchenko

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

17 Citations (Scopus)

Abstract

We present CAM (comparative argumentative machine), a novel open-domain IR system to argumentatively compare objects with respect to information extracted from the Common Crawl. In a user study, the participants obtained 15% more accurate answers using CAM compared to a “traditional” keyword-based search and were 20% faster in finding the answer to comparative questions.

Original languageEnglish
Title of host publicationCHIIR 2019 - Proceedings of the 2019 Conference on Human Information Interaction and Retrieval
PublisherAssociation for Computing Machinery, Inc
Pages361-365
Number of pages5
ISBN (Electronic)9781450360258
DOIs
Publication statusPublished - 8 Mar 2019
Externally publishedYes
Event4th ACM SIGIR Conference on Information Interaction and Retrieval, CHIIR 2019 - Glasgow, United Kingdom
Duration: 10 Mar 201914 Mar 2019

Publication series

NameCHIIR 2019 - Proceedings of the 2019 Conference on Human Information Interaction and Retrieval

Conference

Conference4th ACM SIGIR Conference on Information Interaction and Retrieval, CHIIR 2019
Country/TerritoryUnited Kingdom
CityGlasgow
Period10/03/1914/03/19

Keywords

  • Comparative Question Answering
  • HCI
  • Keyword Search
  • Natural Language Processing

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