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Figure Descriptive Text Extraction using Ontological Representation

arXiv 2208.06040 ↗First posted 11 Aug 2022cs.CL cs.LGcited by 0

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Abstract (arXiv)

Experimental research publications provide figure form resources including graphs, charts, and any type of images to effectively support and convey methods and results. To describe figures, authors add captions, which are often incomplete, and more descriptions reside in body text. This work presents a method to extract figure descriptive text from the body of scientific articles. We adopted ontological semantics to aid concept recognition of figure-related information, which generates human- and machine-readable knowledge representations from sentences. Our results show that conceptual models bring an improvement in figure descriptive sentence classification over word-based approaches.

Key facts. No citing papers in the map yet (data through 14 Oct 2026). Builds on 2 of its 20 references that are in the map. First posted on arXiv 11 Aug 2022.

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References · 2

  1. 2013Distributed Representations of Words and Phrases and their Compositionalitycited by 3,474
  2. 2017Recent Trends in Deep Learning Based Natural Language Processingcited by 263

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