Focus paragraph detection for online zero-effort queries: Lessons learned from eye-tracking data

Research output: Contribution to book/conference proceedings/anthology/reportConference contributionContributedpeer-review

Contributors

Abstract

In order to realize zero-e ort retrieval in a web-context, it is crucial to identify the part of the web page the user is focusing on. In this paper, we investigate the identification of focus paragraphs in web pages. Starting from a naive baseline for paragraph and focus paragraph detection, we conducted an eye-tracking study to evaluate the most promising features. We found that single features (mouse position, paragraph position, mouse activity) are less predictive for gaze which confirms findings from other studies. The results indicate that an algorithm for focus paragraph detection needs to incorporate a weighted combination of those features as well as additional features, e. g. semantic context derived from the user's web history.

Details

Original languageEnglish
Title of host publicationCHIIR 2017 - Proceedings of the 2017 Conference Human Information Interaction and Retrieval
PublisherAssociation for Computing Machinery, Inc
Pages301-304
Number of pages4
ISBN (electronic)9781450346771
Publication statusPublished - 7 Mar 2017
Peer-reviewedYes

Publication series

SeriesCHIIR 2017 - Proceedings of the 2017 Conference Human Information Interaction and Retrieval

Conference

Title2nd ACM SIGIR Conference on Information Interaction and Retrieval, CHIIR 2017
Duration7 - 11 March 2017
CityOslo
CountryNorway

External IDs

ORCID /0000-0002-2176-876X/work/159606449
ORCID /0000-0001-8667-0926/work/159607995

Keywords

Keywords

  • Eye tracking, Focus paragraph detection, Zero-eort queries