"The Best of Both Worlds!": Integration of Web Page and Eye Tracking Data Driven Approaches for Automatic AOI Detection
- Submitting institution
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The University of Manchester
- Unit of assessment
- 11 - Computer Science and Informatics
- Output identifier
- 158583840
- Type
- D - Journal article
- DOI
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10.1145/3372497
- Title of journal
- ACM Transactions on the Web
- Article number
- 1
- First page
- -
- Volume
- 14
- Issue
- 1
- ISSN
- 1559-1131
- Open access status
- Compliant
- Month of publication
- January
- Year of publication
- 2020
- URL
-
-
- Supplementary information
-
-
- Request cross-referral to
- -
- Output has been delayed by COVID-19
- No
- COVID-19 affected output statement
- -
- Forensic science
- No
- Criminology
- No
- Interdisciplinary
- No
- Number of additional authors
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2
- Research group(s)
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A - Computer Science
- Citation count
- 1
- Proposed double-weighted
- No
- Reserve for an output with double weighting
- No
- Additional information
- "This paper describes the first use of Web page experience based on eye-gaze to automatically segment a page into areas of interest.
Other studies using this approach have received a Best Paper award at W4A Conference (2020/Taipei) and a 2019 BIT Journal paper with 2072 reads.
Keynote by Harper at the 16th International Web for All Conference 2019.
Enabled funded collaboration with Middle Eastern Technical University.
PGR (Eraslan) received the Steve Furber Medal for the Outstanding Doctoral Thesis in Computer Science in 2017. Eraslan then became an Assistant Professor at METU."
- Author contribution statement
- -
- Non-English
- No
- English abstract
- -
