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AdaptLIL: A Gaze-Adaptive Visualization for Ontology Mapping

  • arXiv (Cornell University)
  • Cornell University
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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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DOI
10.48550/arxiv.2411.11768
OpenAlex
W4404571235
Document type
preprint
Language
EN
Source
arXiv (Cornell University)
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