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AdaptLIL: A Gaze-Adaptive Visualization for Ontology Mapping
November 18, 2024 Β· Declared Dead Β· π arXiv.org
"No code URL or promise found in abstract"
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Authors
Nicholas Chow, Bo Fu
arXiv ID
2411.11768
Category
cs.HC: Human-Computer Interaction
Cross-listed
cs.AI
Citations
1
Venue
arXiv.org
Last Checked
4 months ago
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.
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