Improving knowledge extraction of Hadith classifier using decision tree algorithm

@article{Aldhaln2012ImprovingKE,
  title={Improving knowledge extraction of Hadith classifier using decision tree algorithm},
  author={Kawther Aldhaln and Akram Zeki and Ahmed Zeki and Hamad Alreshidi},
  journal={2012 International Conference on Information Retrieval & Knowledge Management},
  year={2012},
  pages={148-152}
}
Decision tree algorithms have the ability to deal with missing values. While this ability is considered to be advantage, the extreme effort which is required to achieve it is considered a drawback. With the missing values the correct branch could be missed. Therefore, enhanced mechanisms must be employed to handle these values. Moreover, ignoring these null values may cause critical decision to user. Especially for the cases that belong to religion. The present study proposed Hadith classifier… CONTINUE READING

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Key Quantitative Results

  • The findings showed that the accurate rate of the naïvebyes classifier has been improved by the proposed approach with 46.54%.

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Citations

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Computational and natural language processing based studies of hadith literature: a survey

  • Artificial Intelligence Review
  • 2019
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CITES METHODS & BACKGROUND
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Hadith data mining and classification: a comparative analysis

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HIGHLY INFLUENCED

Frameworks for a Computational Isnad Authentication and Mechanism Development

  • 2016 6th International Conference on Information and Communication Technology for The Muslim World (ICT4M)
  • 2016
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CITES METHODS & BACKGROUND

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