Focus paragraph detection for online zero-effort queries: Lessons learned from eye-tracking data
Research output: Contribution to book/conference proceedings/anthology/report › Conference contribution › Contributed › peer-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 language | English |
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Title of host publication | CHIIR 2017 - Proceedings of the 2017 Conference Human Information Interaction and Retrieval |
Publisher | Association for Computing Machinery, Inc |
Pages | 301-304 |
Number of pages | 4 |
ISBN (electronic) | 9781450346771 |
Publication status | Published - 7 Mar 2017 |
Peer-reviewed | Yes |
Publication series
Series | CHIIR 2017 - Proceedings of the 2017 Conference Human Information Interaction and Retrieval |
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Conference
Title | 2nd ACM SIGIR Conference on Information Interaction and Retrieval, CHIIR 2017 |
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Duration | 7 - 11 March 2017 |
City | Oslo |
Country | Norway |
External IDs
ORCID | /0000-0002-2176-876X/work/159606449 |
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ORCID | /0000-0001-8667-0926/work/159607995 |
Keywords
ASJC Scopus subject areas
Keywords
- Eye tracking, Focus paragraph detection, Zero-eort queries