2022
AAAI
AAAI 2022
An Ontological Approach towards Automatic Creation of Infographics from Formal Text (Student Abstract)
Abstract
Abstract Infographics deal with representing data or information visually in a perceptually compelling manner. Recently, infographics have gained widespread popularity, giving rise to automated infographics synthesis from texts. Our research follows an ontological approach to automatically extract the necessary indicators from an input sentence and synthesize an infographic corresponding to it. This work includes (1) the creation of a dataset, (2) an end-to-end domain-agnostic framework, and (3) demonstrating the application of the proposed framework. The results demonstrate our framework's ability to extract the necessary textual cues from real-world textual descriptions (from various domains) and synthesize meaningful infographics.
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Interdisciplinary Bridge
— Artificial Intelligence and Computer Science and Interdisciplinary and Knowledge & Reasoning and Natural Language Processing
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Keyword Pioneer
— infographics generation
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Cross-Pollinator
— Artificial Intelligence, Computer Science, Computer Vision, Data Science & Analytics, Deep Learning, Healthcare & Medicine, Interdisciplinary, Knowledge & Reasoning, Machine Learning, Mathematics & Optimization, Natural Language Processing, Reinforcement Learning, Robotics, Security & Privacy, Speech & Audio
Authors
Topics
Knowledge & Reasoning > Representation > Ontology Learning
Computer Science > Systems > Computer Graphics
Computer Science > Applications > Document Analysis
Interdisciplinary > Digital Humanities
Natural Language Processing > Applications > Text Generation
Artificial Intelligence > Core AI > Knowledge Representation
Computer Science > Applications > Computer Graphics