论文标题
图描述性文本提取使用本体论表示
Figure Descriptive Text Extraction using Ontological Representation
论文作者
论文摘要
实验研究出版物提供了图形资源，包括图形，图表和任何类型的图像，以有效地支持和传达方法和结果。为了描述数字，作者添加了通常不完整的字幕，并且在身体文本中存在更多描述。这项工作提出了一种从科学文章的体系中提取描述性文本的方法。我们采用本体论语义来帮助概念识别与人物相关的信息，从而产生人类和机器可读的知识表示。我们的结果表明，概念模型对基于单词的方法的描述性句子分类有所改善。
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.
