PDF-to-Tree: Parsing PDF Text Blocks into a Tree
Yue Zhang, Zhihao Zhang, Wenbin Lai, Chong Zhang, Tao Gui, Qi Zhang, Xuanjing Huang · 2024
In many PDF documents, the reading order of text blocks is missing, which can hinder machine understanding of the document's content.Existing works try to extract one universal reading order for a PDF file.However, applications, like Retrieval Augmented Generation (RAG), require breaking long articles into sections, subsections and table cells for better indexing.For this reason, this paper introduces a new task and dataset, PDF-to-Tree, which organizes the text blocks of a PDF into a tree structure.Since a PDF may contain thousands of text blocks, this paper proposes a transition-based parser that uses a greedy strategy to build the tree structure.Compared to the parser for plain text, we also use multi-modal features to encode the parser state.Experiments show that our approach achieves an accuracy of 93.93%, surpassing the performance of baseline methods by an improvement of 6.72%.The dataset is public available at https://github.com/yuezh000/PDF-to-Tree.