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Integrating natural language understanding with document structure analysis

  • Published: March 1994
  • Volume 8, pages 255–276, (1994)
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Artificial Intelligence Review Aims and scope Submit manuscript
Integrating natural language understanding with document structure analysis
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  • Suzanne Liebowitz Taylor1,
  • Deborah A. Dahl1,
  • Mark Lipshutz1,
  • Carl Weir1,
  • Lewis M. Norton1,
  • Roslyn Weidner Nilson1 &
  • …
  • Marcia C. Linebarger1 
  • 81 Accesses

  • 5 Citations

  • Explore all metrics

Abstract

Document understanding, the interpretation of a document from its image form, is a technology area which benefits greatly from the integration of natural language processing with image processing. We have developed a prototype of an Intelligent Document Understanding System (IDUS) which employs several technologies: image processing, optical character recognition, document structure analysis and text understanding in a cooperative fashion. This paper discusses those areas of research during development of IDUS where we have found the most benefit from the integration of natural language processing and image processing: document structure analysis, optical character recognition (OCR) correction, and text analysis. We also discuss two applications which are supported by IDUS: text retrieval and automatic generation of hypertext links

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Authors and Affiliations

  1. Unisys Corporation, 70 E. Swedesford Road, Paoli, 19301, Pennsylvania

    Suzanne Liebowitz Taylor, Deborah A. Dahl, Mark Lipshutz, Carl Weir, Lewis M. Norton, Roslyn Weidner Nilson & Marcia C. Linebarger

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  1. Suzanne Liebowitz Taylor
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  2. Deborah A. Dahl
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  3. Mark Lipshutz
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  4. Carl Weir
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  6. Roslyn Weidner Nilson
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  7. Marcia C. Linebarger
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Taylor, S.L., Dahl, D.A., Lipshutz, M. et al. Integrating natural language understanding with document structure analysis. Artif Intell Rev 8, 255–276 (1994). https://doi.org/10.1007/BF00849077

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  • Issue date: March 1994

  • DOI: https://doi.org/10.1007/BF00849077

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Key words

  • document analysis
  • natural language processing
  • image processing
  • vision
  • optical character recognition

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