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.
翻译:实验研究出版物提供图表形式资源,包括图表、图表和任何类型的图像,以有效支持和传递方法和结果。为描述数字,作者增加说明,这些说明往往不完整,更多的说明则包含在正文中。这项工作提供了从科学文章的正文中提取图表描述性文字的方法。我们采用了肿瘤语义来帮助人们从概念上认识与图形有关的信息,从而从句子中产生人和机器可读的知识表述。我们的结果显示,概念模型在图表描述性句分级方面比字法方法有所改进。