arXiv Open Access 2024

AdaptLIL: A Gaze-Adaptive Visualization for Ontology Mapping

Nicholas Chow Bo Fu

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Abstrak

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.

Topik & Kata Kunci

cs.HC cs.AI

Penulis (2)

Nicholas Chow

Bo Fu

Format Sitasi

APA MLA BibTeX

Chow, N., Fu, B. (2024). AdaptLIL: A Gaze-Adaptive Visualization for Ontology Mapping. https://arxiv.org/abs/2411.11768

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Informasi Jurnal

Tahun Terbit: 2024
Bahasa: en
Sumber Database: arXiv
Akses: Open Access ✓