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Integrated Approach to Detect Inconspicuous Contents

  • Rosina Weber
  • Ilya Waldstein
  • Amit Deshpande
  • Jason M. Proctor
Part of the Lecture Notes in Computer Science book series (LNCS, volume 3782)

Abstract

This paper describes an integrated approach for detecting inconspicuous contents in text. Inconspicuous contents can be an opinion or goal that may be disguised in some way to mislead automated methods but keeps a clear message for humans (e.g., terrorist sites). Our methodology hypothesizes that patterns that convey inconspicuous contents can be extracted, represented, generalized, and matched in unknown text. The proposed approach is meant to complement data-intensive methods (e.g. clustering). Data-intensive methods are fast but are susceptible to variations in frequency, do not discern meaning, and require a large corpus for training. Our approach relies on manual engineering for natural language interpretation and pattern extraction using no more than ten examples, but is sufficiently fast to complement a real-time application.

Keywords

True Positive Natural Language Processing Training Instance Training Corpus Cosmetic Procedure 
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 2005

Authors and Affiliations

  • Rosina Weber
    • 1
  • Ilya Waldstein
    • 1
  • Amit Deshpande
    • 1
  • Jason M. Proctor
    • 1
  1. 1.College of Information Science and TechnologyDrexel UniversityPhiladelphiaUSA

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