Innovation in Language Learning

Al Quran is a divine text which represents the purest and most authentic form of the classical Arabic language. In order to understand the meaning of each verse, a deep knowledge of Arabic linguistic is essential. Therefore, our scholars have made their efforts by engaging themselves in the works of explaining al Quran’s words, interpreting its meanings into Arabic and other languages. Currently, more people are interested in knowing the content of al-Quran, especially for non-Muslim, after 9/11 tragedy. Thus, 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 Lexicology –Semantic Analysis Model (LEXICOLSEM) 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 LEXICOLSEM,(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.

Keywords: Multi-Relational, Latent, Lexicology-Semantic, Model Extracting, Qura’ni;

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