Information fusion for automatic text classification

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Analysis and classification of free text documents encompass decision-making processes that rely on several clues derived from text and other contextual information. When using multiple clues, it is generally not known a priori how these should be integrated into a decision. An algorithmic sensor based on Latent Semantic Indexing (LSI) (a recent successful method for text retrieval rather than classification) is the primary sensor used in our work, but its utility is limited by the {ital reference}{ital library} of documents. Thus, there is an important need to complement or at least supplement this sensor. We have developed a system that ... continued below

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8 p.

Creation Information

Dasigi, V.; Mann, R.C. & Protopopescu, V.A. August 1, 1996.

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This article 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. More information about this article can be viewed below.

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  • Dasigi, V. Department of Computer Science and Information Technology, Sacred Heart University, Fairfield, CT (United States)
  • Mann, R.C.
  • Protopopescu, V.A. Computer and Mathematics Division, Oak Ridge National Laboratory, Oak Ridge, TN (United States)

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Description

Analysis and classification of free text documents encompass decision-making processes that rely on several clues derived from text and other contextual information. When using multiple clues, it is generally not known a priori how these should be integrated into a decision. An algorithmic sensor based on Latent Semantic Indexing (LSI) (a recent successful method for text retrieval rather than classification) is the primary sensor used in our work, but its utility is limited by the {ital reference}{ital library} of documents. Thus, there is an important need to complement or at least supplement this sensor. We have developed a system that uses a neural network to integrate the LSI-based sensor with other clues derived from the text. This approach allows for systematic fusion of several information sources in order to determine a combined best decision about the category to which a document belongs.

Physical Description

8 p.

Notes

OSTI as DE96013781

Source

  • Foundations of decision/information fusion workshop on applications to engineering problems, Washington, DC (United States), 7-9 Aug 1996

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  • Other: DE96013781
  • Report No.: CONF-9608120--1
  • Grant Number: AC05-96OR22464
  • Office of Scientific & Technical Information Report Number: 378178
  • Archival Resource Key: ark:/67531/metadc686892

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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

  • August 1, 1996

Added to The UNT Digital Library

  • July 25, 2015, 2:20 a.m.

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  • Jan. 22, 2016, 11:41 a.m.

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Dasigi, V.; Mann, R.C. & Protopopescu, V.A. Information fusion for automatic text classification, article, August 1, 1996; Tennessee. (digital.library.unt.edu/ark:/67531/metadc686892/: accessed November 19, 2017), University of North Texas Libraries, Digital Library, digital.library.unt.edu; crediting UNT Libraries Government Documents Department.