TEXUS: Table Extraction System for PDF Documents

  • Roya Rastan
  • Hye-Young Paik
  • John Shepherd
  • Seung Hwan RyuEmail author
  • Amin Beheshti
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 10837)


Tables in documents are a rich and under-exploited source of structured data in otherwise unstructured documents. The extraction and understanding of tabular data is a challenging task which has attracted the attention of researchers from a range of disciplines such as information retrieval, machine learning and natural language processing. In this demonstration, we present an end-to-end table extraction and understanding system which takes a PDF file and automatically generates a set of XML and CSV files containing the extracted cells, rows and columns of tables, as well as a complete reading order analysis of the tables. Unlike many systems that work as a black-boxed, ad-hoc solution, our system design incorporates the open, reusable and extensible architecture to support research into, and development of, table-processing systems. During the demo, users will see how our system gradually transforms a PDF document into a set of structured files through a series of processing modules, namely: locating, segmenting and function/structure analysis.


Table extraction TEXUS Table processing Information extraction Document processing 


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Copyright information

© Springer International Publishing AG, part of Springer Nature 2018

Authors and Affiliations

  • Roya Rastan
    • 1
  • Hye-Young Paik
    • 1
  • John Shepherd
    • 1
  • Seung Hwan Ryu
    • 1
    Email author
  • Amin Beheshti
    • 2
  1. 1.School of Computer Science and EngineeringUniversity of New South WalesSydneyAustralia
  2. 2.Department of ComputingMacquarie UniversitySydneyAustralia

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