Users, adaptivity, and bad abandonment

Alistair Moffat, Alfan Farizki Wicaksono

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

4 Citations (Scopus)

Abstract

We consider two recent proposals for effectiveness metrics that have been argued to be adaptive, those of Moffat et al. (ACM TOIS, 2017) and Jiang and Allan (CIKM, 2017), and consider the user interaction models that they give rise to. By categorizing non-relevant documents into those that are plausibly non-relevant and those that are egregiously non-relevant, we capture all of the attributes incorporated into the two proposals, and hence develop an effectiveness metric that better reflects user behavior when viewing the SERP, including bad abandonment.

Original languageEnglish
Title of host publication41st International ACM SIGIR Conference on Research and Development in Information Retrieval, SIGIR 2018
PublisherAssociation for Computing Machinery, Inc
Pages897-900
Number of pages4
ISBN (Electronic)9781450356572
DOIs
Publication statusPublished - 27 Jun 2018
Event41st Annual International ACM SIGIR Conference on Research and Development in Information Retrieval, SIGIR 2018 - Ann Arbor, United States
Duration: 8 Jul 201812 Jul 2018

Publication series

Name41st International ACM SIGIR Conference on Research and Development in Information Retrieval, SIGIR 2018

Conference

Conference41st Annual International ACM SIGIR Conference on Research and Development in Information Retrieval, SIGIR 2018
CountryUnited States
CityAnn Arbor
Period8/07/1812/07/18

Keywords

  • Adaptive
  • Evaluation
  • Precision
  • User model

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