Hybrid Search Approach for Retrieving Medical and Health Science Knowledge from Quran

  • Abstract
  • Keywords
  • References
  • PDF
  • Abstract

    Keyword-based technique has low accuracy and always leads to wrong information retrieved. Therefore, many researchers implement semantic search to overcome the above problems. Many researchers have built different Quran ontology in various domains to facilitate the knowledge representation in the Quran. Nevertheless, there are many domain concepts mentioned in the Quran which are not yet covered, especially for the Medical and Health Science domain. Hence, this research presents the development of ontology for the Medical and Health Science domain in the Quran and implementation of ontology-based search method to answer related queries in the Quran. The development of ontology adopts the ontology 101 approach which later evaluated by Quran experts. Furthermore, a hybrid search tool was developed that encompassed semantic-based and keyword based technique to answer a user query. The search tool was evaluated using the Recall and Precision measurements, which shows high accuracy in retrieving the Medical and Health Science knowledge in the Quran. For future work, this research can be used as a reference and basis to answer user queries, data integration with other applications or existing ontology can be further expanded.



  • Keywords

    Information Retrieval; Medical and Health Science; Quran Ontology.

  • References

      [1] Arbaoui, A., Alginahi, Y. M. & Menacer, M. (2013). Strategies for collecting electronic resources on the qur’anic researches. Int. J. Quranic Res., 3(4), 57–78.

      [2] Ullah Khan, H., Saqlain, S. M., Shoaib, M. & Sher, M. (2013). Ontology based semantic search in Holy Quran. Int. J. Futur. Comput. Commun., 2(6), 570–575.

      [3] Ta’a, A., Abed, Q. A., Ali, B. M. & Ahmad, M. (2016). Ontology-based approach for knowledge retrieval in Al-Quran Holy Book. Int. J. Comput. Eng. Res. Ontol., 6(3), 8–15.

      [4] Alqahtani, M. & Atwell, E. (2016). Arabic Quranic search tool based on ontology. Proceedings of the International Conference on Applications of Natural Language to Information Systems, pp. 478–485.

      [5] Yauri, A. R., Kadir, R. A., Azman, A. & Murad, M. A. A. (2013). Quranic verse extraction base on concepts using OWL-DL ontology. Res. J. Appl. Sci. Eng. Technol., 6, (23), 4492–4498.

      [6] Mangold, C. (2007). A survey and classification of semantic search approaches. Int. J. Metadata, Semant. Ontol., 2(1), 23.

      [7] Kalfoglou, Y. (2007). Using ontologies to support and critique decisions. Eng. Intell. Syst. Electr. Eng. Commun., 15(3), 159–166.

      [8] Hakkoum, A. & Raghay, S. (2016). Semantic Q&A system on the Qur’an. Arab. J. Sci. Eng., 41(12), 5205–5214.

      [9] Beseiso, M., Ahmad, A. R. & Ismail, R. (2010). A Survey of Arabic language Support in Semantic web. Int. J. Comput. Appl., 9(1), 35–40.

      [10] Ta’a, A., Abdullah, M. S., Ali, A. B. M. & Ahmad, M. (2014). Themes-based classification for Al-Quran knowledge ontology. Proceedings of the IEEE International Conference on Information and Communication Technology Convergence, pp. 89–94.

      [11] Shoaib, M., Yasin, M. N., Hikmat Ullah, K., Saeed, M. I. & Khiyal, M. S. H. (2009). Relational WordNet model for semantic search in Holy Quran. Proceedings of the Int. Conf. Emerg. Technol., pp. 29–34.

      [12] Atwell, E. et al. (2010). Understanding the Quran: A new grand challenge for computer science and artificial intelligence. Gd. Challenges Comput. Res. Br. Comput. Soc. Work., 1(11), 1829–1841.

      [13] Alqahtani, M. & Atwell, E. (2017). Evaluation criteria for computational Quran search. Int. J. Islam. Appl. Comput. Sci. Technol., 5(1), 12–22.

      [14] Sudeepthi, G., Anuradha, G. & Babu, M. (2012). A survey on semantic web search engine. Int. J. Comput. Sci., 9(2), 241–245.

      [15] Al-Jarrah, O., Al-Kiswany, S., Al-Gharaibeh, B., Fraiwan, M. & Khasawneh, H. (2006). A new algorithm for Arabic optical character recognition. Proceedings of the 5th WSEAS Int Conf on Signal Processing Robotics and Automation, pp. 211–224.

      [16] Shawar, B. A. (2011). A chatbot as a natural web interface to Arabic web QA. Int. J. Emerg. Technol. Learn., 6(1), 37–43.

      [17] Raza, S. A., Rehan, M., Farooq, A., Ahsan, S. M. & Khan, M. S. (2014). An essential framework for concept based evolutionary Quranic search engine. Science International. 26(1), 181–184.

      [18] Yauri, A. R., Kadir, R. A. Azman, A. & Murad, M. A. A. (2013). Ontology semantic approach to extraction of knowledge from Holy Quran. Proceedings of the 5th International Conference on Computer Science and Information Technology, pp. 19–23.

      [19] Yunus, M. A., Zainuddin, R. & Abdullah, N. (2010). Semantic query for Quran documents results. Proceedings of the IEEE Conference on Open Systems, pp. 1–5.

      [20] Yahya, Z., Abdullah, M. T., Azman, A. & Abdul Kadir, R. (2013). Query translation using concepts similarity based on Quran ontology for cross-language information retrieval. J. Comput. Sci., 9(7), 889–897.

      [21] Saad, S., Salim, N. & Zainal, H. (2009). Pattern extraction for islamic concept. Proceedings of the Int. Conf. Electr. Eng. Informatics, pp. 333–337.

      [22] Saad, S., Salim, N. & Zainal, H. (2010). Towards context-sensitive domain of Islamic knowledge ontology extraction. Int. J. Infonomics, 3(1), 197–206.

      [23] Al-Yahya, M. & Al-Khalifa, H. (2010). An ontological model for representing semantic lexicons: An application on time nouns in the Holy Quran. Arab. J. Sci. Eng., (352), 21–35.

      [24] Al-Khalifa, H. S., Al-Yahya, M. M., Bahanshal, A. & Al-Odah, I. (2009). SemQ: A proposed framework for representing semantic opposition in the Holy Quran using semantic web technologies. Proceedings of the Int. Conf. Curr. Trends Inf. Technol., pp. 44–47.

      [25] Ali, B. & Ahmad, M. (2013). Al-Quran themes classification using ontology. Icoci.Cms.Net.My, 74, 383–389.

      [26] Yauri, A. R., Kadir, R. A., Azman, A. & Azmi Murad, M. A. (2012). Quranic-based concepts: Verse relations extraction using Manchester OWL syntax. Proceedings of the Int. Conf. Inf. Retr. Knowl. Manag., pp. 317–321.

      [27] Muhammad, A. (2012). Annotation of conceptual co-reference and text mining the Qur’an. PhD thesis, University of Leeds.

      [28] Sadi, A. B. M. S., Anam, T., Abdirazak, M., Adnan, A. H., Khan, S. Z., Rahman, M. M., & Samara, G. (2016). Applying ontological modeling on quranic ‘nature’ domain. Proceedings of the 7th International Conference on Information and Communication Systems, pp. 151–155.

      [29] Tashtoush, Y. M., Al-Soud, M. R., AbuJazoh, R. M. & Al-Frehat, M. (2017). The noble quran Arabic ontology: Domain ontological model and evaluation of human and social relations. Proceedings of the 8th International Conference on Information and Communication Systems, pp. 40–45.

      [30] Periamalai, N. S. H. A. R., Mustapha, A. & Alqurneh, A. (2016). An ontology for Juz’ Amma based on expert knowledge. Proceedings of the 7th International Conference on Computer Science and Information Technology, pp. 1–5.

      [31] Ou, S., Pekar, V., Orasan, C., Spurk, C. & Negri, M. (2008). Development and alignment of a domain-specific ontology for question answering. Proceedings of the 6th Ed. Lang. Resour. Eval. Conf., pp. 2221–2228.

      [32] Noy, N. F. & McGuinness, D. L. (2001). Ontology development 101: A guide to creating your first ontology. Stanford Knowl. Syst. Lab., 25, 2001.

      [33] Auer, S., Bizer, C., Kobilarov, Lehmann, G., Cyganiak, J. R., & Ives, Z. (2007). DBpedia: A nucleus for a Web of open data. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 4825, 722–735.

      [34] Aleksovski, Z., Ten Kate, W., & Van Harmelen, F. (2008). Using multiple ontologies as background knowledge in ontology matching. Proceedings of the CISWEB Workshop: ESWC Workshop on Collective Semantics, pp. 35–49.




Article ID: 21374
DOI: 10.14419/ijet.v7i4.15.21374

Copyright © 2012-2015 Science Publishing Corporation Inc. All rights reserved.