• DocumentCode
    3715208
  • Title

    A hybrid approach for word segmentation

  • Author

    Ammar Mohammed;Mohamed Karam;Hesham Hefny

  • Author_Institution
    Department of Computer Science, Arab East Colleges, Riyadh, KSA, Department of Computer Science, ISSR, Cairo University, Egypt
  • fYear
    2015
  • Firstpage
    232
  • Lastpage
    238
  • Abstract
    Automatic word segmentation is the process of finding the most likely sequence of words from a sequence of characters without spaces. The central issues of the word segmentation process are the complexity and accuracy. This paper proposes a hybrid method for automatic word segmentation depending on a dictionary based approach, word-statistics and the length of the word. In comparison to the word segmentation using Maximum Length Descending Frequency and Entropy Rate method, the paper shows that the proposed method gives a better accuracy.
  • Keywords
    "Complexity theory","Dictionaries","Probability","Heuristic algorithms","Computer science","Entropy","Intelligent systems"
  • Publisher
    ieee
  • Conference_Titel
    SAI Intelligent Systems Conference (IntelliSys), 2015
  • Type

    conf

  • DOI
    10.1109/IntelliSys.2015.7361148
  • Filename
    7361148