Multi-Relational Latent Syntax-Semantic â€œSYNTAXLSEMâ€ Analysis Model for Extracting Quraâ€™nic Concept a New Innovative for Sustainable Society
Keywords:Multi-Relational, Latent, Syntax-Semantic, Model Extracting, Quraâ€™ni, Sustainable Society.
A flexible model that can represent Qurâ€™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 Qurâ€™anic concept. The existing literatures focus only on very limited relationships between words which could not extract the in-depth concept of Qurâ€™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 Quraâ€™nic words, and (4) to validate the proposed model with Arabic linguistic, and Quraâ€™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 Qurâ€™anic concept. This will be very significant in enhancing the overall Quranâ€™s understanding among the society in Malaysia and Muslimâ€™s world for sustainable society.
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