  Document structure analysis (aka document layout analysis) is crucial for
understanding the physical layout and logical structure of documents, with
applications in information retrieval, document summarization, knowledge
extraction, etc. In this paper, we concentrate on Hierarchical Document
Structure Analysis (HDSA) to explore hierarchical relationships within
structured documents created using authoring software employing hierarchical
schemas, such as LaTeX, Microsoft Word, and HTML. To comprehensively analyze
hierarchical document structures, we propose a tree construction based approach
that addresses multiple subtasks concurrently, including page object detection
(Detect), reading order prediction of identified objects (Order), and the
construction of intended hierarchical structure (Construct). We present an
effective end-to-end solution based on this framework to demonstrate its
performance. To assess our approach, we develop a comprehensive benchmark
called Comp-HRDoc, which evaluates the above subtasks simultaneously. Our
end-to-end system achieves state-of-the-art performance on two large-scale
document layout analysis datasets (PubLayNet and DocLayNet), a high-quality
hierarchical document structure reconstruction dataset (HRDoc), and our
Comp-HRDoc benchmark. The Comp-HRDoc benchmark will be released to facilitate
further research in this field.
