• DocumentCode
    1681437
  • Title

    Acronym Expansion Via Hidden Markov Models

  • Author

    Taghva, Kazem ; Vyas, Lakshmi

  • Author_Institution
    Sch. of Comput. Sci., Univ. of Nevada, Las Vegas, NV, USA
  • fYear
    2011
  • Firstpage
    120
  • Lastpage
    125
  • Abstract
    In this paper, we report on design and implementation of a Hidden Markov Model (HMM) to extract acronyms and their expansions. We also report on the training of this HMM with Maximum Likelihood Estimation (MLE) algorithm using a set of examples. Finally, we report on our testing using standard recall and precision. The HMM achieves a recall and precision of 98% and 92% respectively.
  • Keywords
    hidden Markov models; maximum likelihood estimation; acronym expansion; hidden Markov models; maximum likelihood estimation algorithm; Data mining; Databases; Hidden Markov models; Maximum likelihood estimation; Meteorology; Organic light emitting diodes; Terminology; Acronyms; HMM; Hidden Markov Models; MLE; Maximum Likelihood Estimation; supervised learning;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Systems Engineering (ICSEng), 2011 21st International Conference on
  • Conference_Location
    Las Vegas, NV
  • Print_ISBN
    978-1-4577-1078-0
  • Type

    conf

  • DOI
    10.1109/ICSEng.2011.29
  • Filename
    6041807
    • Link To Document
    https://search.isc.ac/dl/search/defaultta.aspx?DTC=49&DC=1681437