Machine Learning of Generalized Document Templates for Data Extraction

  • Janusz Wnek
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 2423)

Abstract

The purpose of this research is to reverse engineer the process of encoding data in structured documents and subsequently automate the process of extracting it. We assume a broad category of structured documents for processing that goes beyond form processing. In fact, the documents may have flexible layouts and consist of multiple and varying numbers of pages. The data extraction method (DataX) employs general templates generated by the Inductive Template Generator (InTeGen). The InTeGen method utilizes inductive learning from examples of documents with identified data elements. Both methods achieve high automation with minimal user’s input.

Keywords

Data Element Reverse Engineering Document Image Optical Character Recognition Omission Error 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2002

Authors and Affiliations

  • Janusz Wnek
    • 1
  1. 1.Science Applications International CorporationViennaUSA

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