Al-Hadith Text Classifier

作者：Mohammed Naji Al Kabi; Ghassan Kanaan; Riyad Al Shalabi; Saja I Al Sinjilawi

来源：Journal of Applied Sciences, 2005.

• statistical analysis
• Arabic Text categorization
• hadith (prophet sayings) text classifier
• Arabic text classification
• Arabic text mining
• data-mining
• classification

This study explore the implementation of a text classification method to classify the prophet Mohammed (PBUH) hadiths (sayings) using Sahih Al-Bukhari classification. The sayings explain the Holy Qur`an, which considered by Muslims to be the direct word of Allah. Present method adopts TF/IDF (Term Frequency-Inverse Document Frequency) which is used usually for text search. TF/IDF was used for term weighting, in which document weights for the selected terms are computed, to classify non-vocalized sayings, after their terms (keywords have been transformed to the corresponding canonical form (i.e., roots), to one of eight Books (classes), according to Al-Bukhari classification. A term would have a higher weight if it were a good descriptor for a particular book, i.e., it appears frequently in the book but is infrequent in the entire corpus.

• 出版日期2005