An Ontological Approach Towards Automatic Creation of Infographics from Formal Text (Student Abstract)

Devin Garg, Tanuj Agarwal, Chiranjoy Chattopadhyay

AAAI 2022 pp. 12953-12954

doi:10.1609/AAAI.V36I11.21613 /aaai/2022/garg2022aaai-ontological/

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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Text

Garg et al. "An Ontological Approach Towards Automatic Creation of Infographics from Formal Text (Student Abstract)." AAAI Conference on Artificial Intelligence, 2022. doi:10.1609/AAAI.V36I11.21613

Markdown

[Garg et al. "An Ontological Approach Towards Automatic Creation of Infographics from Formal Text (Student Abstract)." AAAI Conference on Artificial Intelligence, 2022.](https://mlanthology.org/aaai/2022/garg2022aaai-ontological/) doi:10.1609/AAAI.V36I11.21613

BibTeX

@inproceedings{garg2022aaai-ontological,
  title     = {{An Ontological Approach Towards Automatic Creation of Infographics from Formal Text (Student Abstract)}},
  author    = {Garg, Devin and Agarwal, Tanuj and Chattopadhyay, Chiranjoy},
  booktitle = {AAAI Conference on Artificial Intelligence},
  year      = {2022},
  pages     = {12953-12954},
  doi       = {10.1609/AAAI.V36I11.21613},
  url       = {https://mlanthology.org/aaai/2022/garg2022aaai-ontological/}
}