• DocumentCode
    145639
  • Title

    Analogy-Based Machine Translation Using Secability

  • Author

    Kimura, Tomohiro ; Matsuoka, Junichi ; Nishikawa, Yoshihiro ; Lepage, Yves

  • Author_Institution
    Grad. Sch. of Inf., Production & Syst., Waseda Univ., Tokyo, Japan
  • Volume
    2
  • fYear
    2014
  • fDate
    10-13 March 2014
  • Firstpage
    297
  • Lastpage
    298
  • Abstract
    The problem of reordering remains the main problem in machine translation. Computing structures of sentences and the alignment of substructures is a way that has been proposed to solve this problem. We use secability to compute structures and show its effectiveness in an example-based machine translation.
  • Keywords
    language translation; natural language processing; analogy-based machine translation; example-based machine translation; reordering problem; secability; sentence structure; substructure alignment; Computational intelligence; Computational linguistics; Educational institutions; Grammar; Indexes; Production; Scientific computing; Example-based machine translation; alignment; proportional analogy; secability; translation table;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Computational Science and Computational Intelligence (CSCI), 2014 International Conference on
  • Conference_Location
    Las Vegas, NV
  • Type

    conf

  • DOI
    10.1109/CSCI.2014.142
  • Filename
    6822353
    • Link To Document
    https://search.isc.ac/dl/search/defaultta.aspx?DTC=49&DC=145639