• DocumentCode
    244704
  • Title

    Sentence completion task using web-scale data

  • Author

    Kyusong Lee ; Lee, Gwo Giun

  • Author_Institution
    Dept. of Comput. Sci. & Eng., Pohang Univ. of Sci. & Technol., Pohang, South Korea
  • fYear
    2014
  • fDate
    15-17 Jan. 2014
  • Firstpage
    173
  • Lastpage
    176
  • Abstract
    We propose a method to automatically answer SAT-style sentence completion questions using web-scale data. Web-scale da-ta have been used in many language studies and have been found to be a very useful resource for improving accuracy in sentence completion task. Our method employs assorted N-gram probability information for each candidate word. We also proposed back-off strategy was used to remove zero probabilities. We found that the accuracy of our proposed method improved by 52-87% over the current state-of-the-art.
  • Keywords
    natural language processing; probability; SAT-style sentence completion questions; Web-scale data; assorted N-gram probability information; back-off strategy; sentence completion task; zero probability removal; Accuracy; Google; Mathematical model; Pain; Probability; Semantics; Smoothing methods; Lexical Disambiguation; N-gram; Web-cale Data; sentence completion;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Big Data and Smart Computing (BIGCOMP), 2014 International Conference on
  • Conference_Location
    Bangkok
  • Type

    conf

  • DOI
    10.1109/BIGCOMP.2014.6741431
  • Filename
    6741431