Stud.IP Uni Oldenburg
University of Oldenburg
30.09.2022 16:56:45
ThesisTopics

Personal details

Title Relevance-based Adaption of Documents based on Eye Tracking
Description

In this thesis, you will implement a system that adapts the visualization of a document based on real-time relevance feedback. You will use/implement a machine learning model that predicts text relevance based on the users eye movements to, e.g., highlight relevant or hide irrelevant information from the user.

Anna Maria Feit, Lukas Vordemann, Seonwook Park, Caterina Berube, and Otmar Hilliges. 2020. Detecting relevance during decision-making from eye movements for UI adaptation. In Eye Tracking Research and Applications Symposium (ETRA), 1–11. https://doi.org/10.1145/3379155.3391321

Nilavra Bhattacharya, Somnath Rakshit, and Jacek Gwizdka. 2020. Towards Real-time Webpage Relevance Prediction Using Convex Hull Based Eye-tracking Features. In ACM Symposium on Eye Tracking Research and Applications, 10. https://doi.org/10.1145/3379157.3391302

Home institution Department of Computing Science
Type of work not specified
Type of thesis Bachelor's or Master's degree
Author M. Sc. Ilira Troshani
Status assigned
Problem statement
Requirement
Created 07/03/22

Study data

Departments
  • Applied Artificial Intelligence
  • DFKI
Degree programmes Not assigned to any degree programmes
Assigned courses No courses assigned
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