Rapid Exploitation and Analysis of Documents

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Description

Analysts are overwhelmed with information. They have large archives of historical data, both structured and unstructured, and continuous streams of relevant messages and documents that they need to match to current tasks, digest, and incorporate into their analysis. The purpose of the READ project is to develop technologies to make it easier to catalog, classify, and locate relevant information. We approached this task from multiple angles. First, we tackle the issue of processing large quantities of information in reasonable time. Second, we provide mechanisms that allow users to customize their queries based on latent topics exposed from corpus statistics. Third, ... continued below

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PDF-file: 40 pages; size: 1.3 Mbytes

Creation Information

Buttler, D J; Andrzejewski, D; Stevens, K D; Anastasiu, D & Gao, B November 28, 2011.

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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. More information about this report can be viewed below.

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UNT Libraries Government Documents Department

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Description

Analysts are overwhelmed with information. They have large archives of historical data, both structured and unstructured, and continuous streams of relevant messages and documents that they need to match to current tasks, digest, and incorporate into their analysis. The purpose of the READ project is to develop technologies to make it easier to catalog, classify, and locate relevant information. We approached this task from multiple angles. First, we tackle the issue of processing large quantities of information in reasonable time. Second, we provide mechanisms that allow users to customize their queries based on latent topics exposed from corpus statistics. Third, we assist users in organizing query results, adding localized expert structure over results. Forth, we use word sense disambiguation techniques to increase the precision of matching user generated keyword lists with terms and concepts in the corpus. Fifth, we enhance co-occurrence statistics with latent topic attribution, to aid entity relationship discovery. Finally we quantitatively analyze the quality of three popular latent modeling techniques to examine under which circumstances each is useful.

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PDF-file: 40 pages; size: 1.3 Mbytes

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  • Report No.: LLNL-TR-517731
  • Grant Number: W-7405-ENG-48
  • DOI: 10.2172/1033748 | External Link
  • Office of Scientific & Technical Information Report Number: 1033748
  • Archival Resource Key: ark:/67531/metadc836047

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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

  • November 28, 2011

Added to The UNT Digital Library

  • May 19, 2016, 3:16 p.m.

Description Last Updated

  • Dec. 1, 2016, 1:23 p.m.

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Buttler, D J; Andrzejewski, D; Stevens, K D; Anastasiu, D & Gao, B. Rapid Exploitation and Analysis of Documents, report, November 28, 2011; Livermore, California. (digital.library.unt.edu/ark:/67531/metadc836047/: accessed May 27, 2018), University of North Texas Libraries, Digital Library, digital.library.unt.edu; crediting UNT Libraries Government Documents Department.