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AcroDef: A Quality Measure for Discriminating Expansions of Ambiguous Acronyms

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Part of the Lecture Notes in Computer Science book series (LNAI,volume 4635)

Abstract

This paper presents a set of quality measures to determine the choice of the best expansion for an acronym not defined in the Web page. The method uses statistics computed on Web pages to determine the appropriate expansion. Measures are context-based and rely on the assumption that the most frequent words in the page are related semantically or lexically to the acronym expansion.

Keywords

  • Mutual Information
  • Quality Measure
  • Olympic Game
  • Error Ratio
  • Name Entity Recognition

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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Roche, M., Prince, V. (2007). AcroDef: A Quality Measure for Discriminating Expansions of Ambiguous Acronyms. In: Kokinov, B., Richardson, D.C., Roth-Berghofer, T.R., Vieu, L. (eds) Modeling and Using Context. CONTEXT 2007. Lecture Notes in Computer Science(), vol 4635. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-74255-5_31

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  • DOI: https://doi.org/10.1007/978-3-540-74255-5_31

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-74254-8

  • Online ISBN: 978-3-540-74255-5

  • eBook Packages: Computer ScienceComputer Science (R0)