Dr. Azizi

Senior Lecturer







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A New Multi-Relational Latent Semantic Analysis Model for Extracting Prophetic Hadith Concept

Hadith is the second source of Islamic teachings after the Quran. It is a collection of traditions containing sayings of the Prophet Muhammad and his daily practice. Understanding Hadith must not be taken lightly to peel the intended. Only expert scholars can interpret that particular verses using special rules and methodology. However, there is a need to simplify the meaning of Hadith, in order to preach about Islam and its rules, especially for ordinary Muslim or non-Muslims. Thus, a flexible model that can represent Prophetic concept is required for people to understand the content of the Hadith. In this research, we propose a Multi-Relational Latent Semantic Analysis Model (MRLSAM) based on a combination of six multiple relations between words, which are synonym, antonym, hypernym, hyponym, holonym and meronym, to precisely extract Prophetic. The existing literatures focus only on a very limited relationships between words which could not extract the in-depth concept of Hadith without considering the importance Arabic morphology and multi-relational Latent Semantic Analysis (LSA). It is expected that the model will come out with a precise analysis for extracting Prophetic Hadith concept.

Status Current
Lead Hishomudin Bin Ahmad
Members Norzulaili Mohd Ghazali, Robiatul Adawiyah Mohd, Norazizi Sayuti, Rosalina Abdul Salam, Zainal Abidin Hajib, Noor Azma Mohamad Khassim, Nik Farhan Mustapha
Funded By MOHE (FRGS)
Start Date 01/12/2014
End Date 01/12/2017

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