Domain-independent information extraction in unstructured text

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Description

Extracting information from unstructured text has become an important research area in recent years due to the large amount of text now electronically available. This status report describes the findings and work done during the second year of a two-year Laboratory Directed Research and Development Project. Building on the first-year`s work of identifying important entities, this report details techniques used to group words into semantic categories and to output templates containing selective document content. Using word profiles and category clustering derived during a training run, the time-consuming knowledge-building task can be avoided. Though the output still lacks in completeness when ... continued below

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39 p.

Creation Information

Irwin, N.H. September 1, 1996.

Context

This report is part of the collection entitled: Office of Scientific & Technical Information Technical Reports and was provided by UNT Libraries Government Documents Department to Digital Library, a digital repository hosted by the UNT Libraries. It has been viewed 16 times , with 4 in the last month . More information about this report can be viewed below.

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Author

  • Irwin, N.H. Sandia National Labs., Albuquerque, NM (United States). Software Surety Dept.

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  • Sandia National Laboratories
    Publisher Info: Sandia National Labs., Albuquerque, NM (United States)
    Place of Publication: Albuquerque, New Mexico

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Description

Extracting information from unstructured text has become an important research area in recent years due to the large amount of text now electronically available. This status report describes the findings and work done during the second year of a two-year Laboratory Directed Research and Development Project. Building on the first-year`s work of identifying important entities, this report details techniques used to group words into semantic categories and to output templates containing selective document content. Using word profiles and category clustering derived during a training run, the time-consuming knowledge-building task can be avoided. Though the output still lacks in completeness when compared to systems with domain-specific knowledge bases, the results do look promising. The two approaches are compatible and could complement each other within the same system. Domain-independent approaches retain appeal as a system that adapts and learns will soon outpace a system with any amount of a priori knowledge.

Physical Description

39 p.

Notes

OSTI as DE96015325

Source

  • Other Information: PBD: Sep 1996

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Identifier

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  • Other: DE96015325
  • Report No.: SAND--96-2337
  • Grant Number: AC04-94AL85000
  • DOI: 10.2172/378821 | External Link
  • Office of Scientific & Technical Information Report Number: 378821
  • Archival Resource Key: ark:/67531/metadc675703

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Office of Scientific & Technical Information Technical Reports

Reports, articles and other documents harvested from the Office of Scientific and Technical Information.

Office of Scientific and Technical Information (OSTI) is the Department of Energy (DOE) office that collects, preserves, and disseminates DOE-sponsored research and development (R&D) results that are the outcomes of R&D projects or other funded activities at DOE labs and facilities nationwide and grantees at universities and other institutions.

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Creation Date

  • September 1, 1996

Added to The UNT Digital Library

  • July 25, 2015, 2:20 a.m.

Description Last Updated

  • April 13, 2016, 1:35 p.m.

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Citations, Rights, Re-Use

Irwin, N.H. Domain-independent information extraction in unstructured text, report, September 1, 1996; Albuquerque, New Mexico. (digital.library.unt.edu/ark:/67531/metadc675703/: accessed December 18, 2017), University of North Texas Libraries, Digital Library, digital.library.unt.edu; crediting UNT Libraries Government Documents Department.