Multi-Relational Latent Syntax-Semantic “SYNTAXLSEM” Analysis Model for Extracting Qura’nic Concept a New Innovative for Sustainable Society

Abstract

A flexible model that can represent Qur’anic concept is required for people to understand the content of the Quran. In this research, we propose a Multi-Relational Latent Syntax-Semantic Analysis Model (SYNTAXLSEM) based on a combination of Arabic Semantic and six multiple relations between words, which are synonym, antonym, hypernym, hyponym, holonym and meronym, to precisely extract Qur’anic concept. The existing literatures focus only on very limited relationships between words which could not extract the in-depth concept of Qur’anic without considering the importance Arabic Semantic. Therefore, the objectives of this research are: (1) to analyse and categorize Quranic words according to Arabic Semantic patterns, (2) to propose a new model for extracting Quranic concept using SYNTAXLSEM, (3) to investigate semantic relationships between Qura’nic words, and (4) to validate the proposed model with Arabic linguistic, and Qura’nic experts. This research will be conducted qualitatively through content analysis approach a new innovative technological technique. It is expected that the model will come out with a precise analysis for extracting Qur’anic concept. This will be very significant in enhancing the overall Quran’s understanding among the society in Malaysia and Muslim’s world for sustainable society.