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

  • Authors

    • Asma Abdul Rahman
    • Ahmad Abdul Rahman
    • Mohd Fadhil Md Din
    2018-12-09
    https://doi.org/10.14419/ijet.v7i4.33.26032
  • Multi-Relational, Latent, Syntax-Semantic, Model Extracting, Qura’ni, Sustainable Society.
  • 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.

     

     

  • References

    1. [1] Mousa, A. E. D., Schlüter, R., & Ney, H. (2012). Investigations on the use of morpheme level features in language models for Arabic LVCSR. Proceedings of the IEEE International Conference on Acoustics, Speech and Signal Processing, 2012 pp. 5021-5024.

      [2] Asma Abdul Rahman, (2003-2007), Linguistics Studies. Publishing Section USIM.

      [3] Asma Abdul Rahman, (2007-2017), A’liyat Tahlil Al-Nass Al-Qurani Al-Lughawwy: Dirasah Lughawiyyah Dalaliyyah (Formula Book). Publishing Section USIM.

      [4] Asma Abdul Rahman, (2018), Modern Linguistics Studies. Publishing Section USIM.

      [5] Azman Ta’a, Abidin, S. Z., Abdullah, M. S., Ali, B. B. M., & Ahmad, M. (2013). Al-Quran Themes Classification Using Ontology. Proceedings of the 4th International Conference on Computing and Informatics, pp. 383-389.

      [6] Chang, K. W., Yih, W. T., & Meek, C. (2013). Multi-relational latent semantic analysis. Proceedings of the Conference on Empirical Methods in Natural Language Processing, pp. 1602-1612.

      [7] Cosma, G., & Joy, M. (2012). An approach to source-code plagiarism detection and investigation using latent semantic analysis. IEEE transactions on computers, 61(3), 379-394.

      [8] Desouki, S. G. (2011). An Application Oriented Arabic Phonological Analyzer, 27, 7-19.

      [9] Khan, H. U., Saqlain, S. M., Shoaib, M., & Sher, M. (2013). Ontology based semantic search in Holy Quran. International Journal of Future Computer and Communication, 2(6), 570-575.

      [10] Al-Yahya, M., Al-Khalifa, H., Bahanshal, A., Al-Odah, I., & Al-Helwah, N. (2010). An ontological model for representing semantic lexicons: an application on time nouns in the holy Quran. Arabian Journal for Science and Engineering, 35(2), 21-35.

      [11] Ozcan, R., & Aslangdogan, Y. A. (2004). Concept based information access using ontologies and latent semantic analysis. Technical Report CSE-2004-8, pp. 1-16.

      [12] Steinberger, J., & Ježek, K. (2004). Using Latent Semantic Analysis in Text Summarization. Proceedings of the ISIM, pp. 93-100.

      [13] Zhao, L., & Callan, J. (2010). Term necessity prediction. Proceedings of the 19th ACM International Conference on Information and Knowledge Management, pp. 259-268.

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  • How to Cite

    Abdul Rahman, A., Abdul Rahman, A., & Fadhil Md Din, M. (2018). Multi-Relational Latent Syntax-Semantic “SYNTAXLSEM” Analysis Model for Extracting Qura’nic Concept a New Innovative for Sustainable Society. International Journal of Engineering & Technology, 7(4.33), 254-258. https://doi.org/10.14419/ijet.v7i4.33.26032