Processing Of “Hadith Isnad” Based On Hidden Markov Model

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Author(s) Moath Mustafa Ahmad Najeeb
Pages 50-55
Volume 6
Issue 2
Date February, 2016
Keywords Hadith, Hidden Markov Model, Isnad, Narrator, Sahih Muslim, Natural Language Processing.

Abstract

Hadith is the sayings and actions of Prophet Mohammad (Peace Be upon Him), it is the second legalization source in Islam after the Holy Quran. Hadith consists of two parts: Isnad and Matn, Isnad is the sequence chain of narrators who narrate Hadith while Matn is the words or actions of the prophet. In this paper, we introduce a novel approach that recognizes the “Parts of Isnad” based on Hidden Markov Model (HMM), this approach contains three phases: preparation, training and testing. Our approach classifies the words and phrases of Isnad to its main categories such as: narrator name, prefix of narrator name, received method, prefix of received method, title, replacement and prophet name.

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