Using Word Based Features for Word Clustering

  • Authors

    • Farhan Nashwan
    • Mohsen Rashwan
    • Sherif Abdou
    • Hassanin Al-Barhamtoshy
    2019-03-01
    https://doi.org/10.14419/ijet.v8i1.11.28085
  • holistic technique, clustering, optical character recognition, lexicon reduction

  • Abstract

    In the holistic technique (HT) the whole information of the Arabic word is calculated using many possible features. In this paper, this approach is used to test the possible uses of the HT in the Arabic OCR systems. The HT is used to reduce the possible candidates for each word. We succeeded to reduce the candidates to around 115 with accuracy over 99%, given a single font and a single size from a large lexicon of more than 356K words. This vocabulary size has a good coverage for the Arabic Language. This means that the problem facing the OCR classifier is tremendously reduced, and much higher accuracy can be expected for the OCR systems.

     

     

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  • How to Cite

    Nashwan, F., Rashwan, M., Abdou, S., & Al-Barhamtoshy, H. (2019). Using Word Based Features for Word Clustering. International Journal of Engineering & Technology, 8(1.11), 25-32. https://doi.org/10.14419/ijet.v8i1.11.28085

    Received date: 2019-03-01

    Accepted date: 2019-03-01

    Published date: 2019-03-01