Humans are capable of understanding the knowledge that is included in technical documents automatically by consciously combining the information that is presented in the document’s individual modalities. These modalities are mathematical formulas, charts, tables, diagram images and etc. In this paper, we significantly enhance a previously presented technical document understanding methodology³ that emulates the way that humans also perceive information. More specifically, we make the original diagram understanding methodology adaptive to larger architectures with more complex structures and modules. The overall understanding methodology results in the generation of a Stochastic Petri-net (SPN) graph that describes the system’s functionality. Finally, we conclude with the introduction of the hierarchical association of different diagram images from the same technical document. This processing step aims to provide a holistic understanding of all illustrated diagram information.

中文翻译：

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深入理解技术文档：对图表理解的增强

人类能够通过有意识地结合文档的各个模式中呈现的信息来自动理解技术文档中包含的知识。这些形式是数学公式、图表、表格、图表图像等。在本文中，我们显着增强了先前提出的技术文档理解方法³这模仿了人类感知信息的方式。更具体地说，我们使原始的图表理解方法适应具有更复杂结构和模块的更大架构。整体理解方法导致生成描述系统功能的随机 Petri 网 (SPN) 图。最后，我们以介绍来自同一技术文档的不同图表图像的层次关联作为结束。此处理步骤旨在提供对所有图解图表信息的整体理解。