Predicting information seeking intentions from search behaviors

Matthew Mitsui, Jiqun Liu, N. J. Belkin, Chirag Shah

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

33 Scopus citations

Abstract

It has been shown that people attempt to accomplish a variety of intentions during the course of an information seeking session, and there is reason to believe that these different information seeking intentions can benefit from system support tailored to each such intention. We address the problem of predicting the presence of such intentions during an information seeking session, through analysis of observable user search behaviors. We present results of a study of 40 participants, each working on two different journalism tasks, which investigated how their search behaviors could indicate their intentions. Using 725 query-segments captured from this study, we demonstrate that information seeking intentions can be predicted with a simple classification model using a linear combination of search behavior features that can be logged with a browser plug-in.

Original languageEnglish (US)
Title of host publicationSIGIR 2017 - Proceedings of the 40th International ACM SIGIR Conference on Research and Development in Information Retrieval
PublisherAssociation for Computing Machinery, Inc
Pages1121-1124
Number of pages4
ISBN (Electronic)9781450350228
DOIs
StatePublished - Aug 7 2017
Event40th International ACM SIGIR Conference on Research and Development in Information Retrieval, SIGIR 2017 - Tokyo, Shinjuku, Japan
Duration: Aug 7 2017Aug 11 2017

Publication series

NameSIGIR 2017 - Proceedings of the 40th International ACM SIGIR Conference on Research and Development in Information Retrieval

Other

Other40th International ACM SIGIR Conference on Research and Development in Information Retrieval, SIGIR 2017
Country/TerritoryJapan
CityTokyo, Shinjuku
Period8/7/178/11/17

All Science Journal Classification (ASJC) codes

  • Information Systems
  • Software
  • Computer Graphics and Computer-Aided Design

Keywords

  • Information seeking episode
  • Information seeking intentions
  • Motivating task
  • Search intentions
  • Search session analysis

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