Published May 17, 2020 | Version v2
Conference paper Open

Figure Descriptive Text Extraction Using Ontological Representation

  • 1. Brookhaven National Laboratory
  • 2. Purdue University

Description

Experimental research publications provide figure form re-sources including graphs, charts, and any type of images to effectively support and convey methods and results. To de-scribe 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.

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