English

AdaptLIL: A Gaze-Adaptive Visualization for Ontology Mapping

Human-Computer Interaction 2024-12-17 v2 Artificial Intelligence

Abstract

This paper showcases AdaptLIL, a real-time adaptive link-indented list ontology mapping visualization that uses eye gaze as the primary input source. Through a multimodal combination of real-time systems, deep learning, and web development applications, this system uniquely curtails graphical overlays (adaptations) to pairwise mappings of link-indented list ontology visualizations for individual users based solely on their eye gaze.

Cite

@article{arxiv.2411.11768,
  title  = {AdaptLIL: A Gaze-Adaptive Visualization for Ontology Mapping},
  author = {Nicholas Chow and Bo Fu},
  journal= {arXiv preprint arXiv:2411.11768},
  year   = {2024}
}

Comments

The paper was submitted without the consent of all authors. It is being withdrawn until full consent is obtained

R2 v1 2026-06-28T20:03:50.528Z