Google scholar arxiv informatics ads IJAIS publications are indexed with Google Scholar, NASA ADS, Informatics et. al.

Call for Paper


March Edition 2023

International Journal of Applied Information Systems solicits high quality original research papers for the March 2023 Edition of the journal. The last date of research paper submission is February 15, 2023.

A Review of Ontology-based Information Retrieval Techniques on Generic Domains

Ishaq Oyebisi Oyefolahan, Enesi Femi Aminu, Muhammad Bashir Abdullahi, Muhammadu Tajudeen Salaudeen in Information Sciences

International Journal of Applied Information Systems
Year of Publication: 2018
Publisher: Foundation of Computer Science (FCS), NY, USA
Authors:Ishaq Oyebisi Oyefolahan, Enesi Femi Aminu, Muhammad Bashir Abdullahi, Muhammadu Tajudeen Salaudeen
Download full text
  1. Ishaq Oyebisi Oyefolahan, Enesi Femi Aminu, Muhammad Bashir Abdullahi and Muhammadu Tajudeen Salaudeen. A Review of Ontology-based Information Retrieval Techniques on Generic Domains. International Journal of Applied Information Systems 12(13):8-21, May 2018. URL, DOI BibTeX

    	author = "Ishaq Oyebisi Oyefolahan and Enesi Femi Aminu and Muhammad Bashir Abdullahi and Muhammadu Tajudeen Salaudeen",
    	title = "A Review of Ontology-based Information Retrieval Techniques on Generic Domains",
    	journal = "International Journal of Applied Information Systems",
    	issue_date = "May 2018",
    	volume = 12,
    	number = 13,
    	month = "May",
    	year = 2018,
    	issn = "2249-0868",
    	pages = "8-21",
    	url = "",
    	doi = "10.5120/ijais2018451750",
    	publisher = "Foundation of Computer Science (FCS), NY, USA",
    	address = "New York, USA"


A promising evolution of the existing web where machine and people are in cooperation is the Semantic Web. That is, a machine’s represented and understandable web. This is against the existing web which is syntactic in nature - where meaning of query search and its expected results on the web is mostly understood and interpreted by user not machine. However, the technologies drive behind this goal of semantic web is on one hand ontologies and on the other hand information retrieval techniques. Ontology is a data modeling technique for structured data repository premised on collection of concepts with their semantic relationships and constraints on a chosen area of knowledge. While on the other hand information retrieval technique is a mechanism of retrieving relevant information based on the query search. There are existing techniques for information retrieval processes, which includes that of ontological process. Therefore, this paper aimed to present a review on these existing techniques based on different classifications processes. Also, the analysis and comparison of the review are carried out based on some fundamental criteria which include various ontology’s domains, ontological tools, information retrieval techniques along with the weights computation algorithms and different evaluation techniques. Thus, a review of ontology based information retrieval techniques had been carried out and this paper has disambiguates the categorization processes of the techniques and serves as a developer’s guide for chosen a technique for any domain.


  1. Jiewen W., Ihab, I., and Grant, W. 2011. A Study of Ontology-based Query Expansion Technical Report CS-2011-04
  2. Grigoris, A. and Frank-van, H. 2008. A Semantic Web Primer. The MIT Press Cambridge, Massachusetts London, England.
  3. David, S. David, I. and Miquel, M. 2011. Content annotation for the semantic web: an automatic web-based approach. Knowl Inf Syst (2011) 27:393-418
  4. Wache, H., Vogele, T., Visser, U., Stuckenschmidt, H., Schuster, G., Neumann, H. and Hubner, S. 2001 Ontology-based integration of information—a survey of existing approaches. In IJCAI-01 Workshop: Ontologies and Information Sharing, Seattle, WA, pp. 108–117.
  5. Lutz, M. and Klien, E. 2006. Ontology-based retrieval of geographic information. International Journal of Geographical Information Science Vol. 20, No. 3, March 2006, 233–260
  6. Miguel, A. R-G, Rafael, V-G, Francisco, G-S,and Javier J. S-Z. 2014. Ontology-based annotation and retrieval of services in the cloud. Knowledge-Based Systems 56 (2014) 15–25
  7. Gruber, T. R. 1993. A Translation Approach to Portable Ontology Specifications. Knowledge Acquisition, 5(2): 199-220.
  8. Haav, H., and Lubi, T. 2001. A survey of concept-based information retrieval tools on the web. In: 5th East-European Conference, ADBIS 2001. Vilnius, Lithuania.
  9. Chih-Ping W., Paul J-H. H., Chia-Hung, T., Chun-Neng, H., and Chin-Sheng, Y. 2007. Managing Word Mismatch Problems in Information Retrieval: A Topic-Based Query Expansion Approach. Journal of Management Information Systems /Winter 2007-8, Vol. 24, No. 3, pp. 269-295.
  10. Manning, C.D., Raghavan, P., Schutze, H. 2008. Introduction to information retrieval. Cambridge University Press.
  11. Sylvie R., Benjamin, D., Mohameth-Francois, S., Jacky, M., Patrick, A. and Vincent, R. 2013. How ontology based information retrieval systems may benefit from lexical text analysis. New Trends of Research in Ontologies and Lexical Resources, Springer, pp.209-230
  12. Rashmi, C., Rayan, G., Robin, S. and Atul, C. 2013. Domain ontology based Semantic Search for Efficient Information Retrieval through Automatic Query Expansion. 2013 International Conference on intelligent Systems and Signal processing (ISSP)
  13. Suriati, A., Li-Hsing, S., and Rafael, B. 2014. Ontology-based similarity for product information retrieval. Computers in Industry 65 (2014) 91–107
  14. Rayner, A., Kim, O. C., Patricia, A., Phang, W. S., Tan, L. I., Leow, C. L. and Gan, K. S. (2014). Ontology Based Query Expansion for Supporting information Retrieval in Agriculture. The 8th International Conference on Knowledge Management in organizations, Springer proceedings in Complexity
  15. Rodrigo, B., Olga, F. N. & Ivo, P. J. 2016. Ontology models of the impacts of agriculture and climate changes on water resources: Scenarios on interoperability and information recovery. Future Generation Computer Systems.
  16. Amir, Z. and Mourad, A. 2013. A Generalized Framework for Ontology – Based Information Retrieval. 2013 International Conference on Advanced Logistics and Transport. 29 – 31, May.
  17. Songhua, M. and Ling, T. 2013. Ontology-based semantic retrieval for mechanical design knowledge. International Journal of Computer Integrated Manufacturing, 28:2, 226-238
  18. Xutang, Z., Xin, H., Xiaofeng, C., and Ting, Z. 2013. Ontology-based semantic retrieval for engineering domain knowledge. Neurocomputing 116 (2013) 382–391
  19. Liu, X., Zhang, X., and Li, Z. (2012). A Domain Ontology-based Information Retrieval Approach for Technique Preparation. Physics Procedia 25 1582 – 1588
  20. Soner, K., Ozgur, A., Orkunt, S., Samet, A., Nihan, K. C. and Ferda, N. A. 2012. Ontology-Based Retrieval System using Semantic Indexing. Information Systems 37, 294–305
  21. Zhanjun L., Victor R. and Karthik, R. 2007. A Methodology of Engineering Ontology Development for Information Retrieval. International Conference on Engineering Design, Iced’07 28 - 31, Paris, France
  22. Godspower, O. E. and Esingbemi, P. E. (2016). Ontology for Alleviating Poverty among Farmers in Nigeria. INFOS '16, May 09-11, 2016, Giza, Egypt
  23. Ruban, S., Kedar, T., Austin, P. R., and Niriksha, S. 2014.An Ontology-Based Information Retrieval Model for Domesticated Plants. International Journal of Innovative Research in Computer and Communication Engineering Vol.2, Special Issue 5
  24. Suresh, P., Mohamed, A. S., and Jens, L. 2014. Ontology Based Data Access and Integration for Improving the Effectiveness of Farming in Nepal. International Joint Conference on Web Intelligence (WI) and Intelligent Agent Technologies (IAI) – Vol. 02 Pages 319 – 326
  25. Antonio, J-Y., Rafael, B-L., and Dietrich, R-S. 2010. Ontology refinement for improved information retrieval. Information Processing and Management 46 (2010) 426 – 435
  26. Uthayan, K. R. and Mala, G. S. A. 2015. Hybrid Ontology for Semantic Information Retrieval Model Using Keyword Matching indexing System. The Scientific World Journal, Volume 2015
  27. Vishal, J. and Mayank, S. 2013. Ontology Based information Retrieval in Semantic Web: A Survey. I.J. Information Technology and Computer Science, 2013, 10, 62-69
  28. Bhogal, J., Macfarlane, A. and Smith, P. 2006. A review of ontology based query expansion. Information Processing and Management 43 (2007) 866–886
  29. Francesco, C., Massimo D. S., Luca, G., and Paolo, N. 2014. Weighted Word Pairs for query expansion. Information Processing and Management (2014).
  30. Hang, C., Ji-Rong, W., Jian-Yun, N., and Wei-Ying, M. 2002. Probabilistic Query Expansion Using Query Logs. ACM 1-58113-449-5/02/0005
  31. Carpineto, C. and Romano, G. 2012. A survey of automatic query expansion in information retrieval. ACM Comput. Surv. 44, 1
  32. Maaike, de B., Klamer, S., and Wessel, K. 2016. Knowledge based query expansion in complex multimedia event detection. Multimed Tools Appl (2016) 75:9025–9043
  33. Maleerat, S., Pilapan, P., and Nalinpat, P. 2013. An Ontology-Based Query Expansion for an Agricultural Expert Retrieval System. iiWAS2013, 2-4 December, 2013, Vienna, Austria. ACM 978-1-4503-2113-6/13/12
  34. Olga, V. and Murat, K. 2007. Query expansion with terms selected using lexical cohesion analysis of documents. Information Processing and Management 43, 849-865.
  35. Alejandra, S. N., Salvador-Sanchez, Elena G-B, and Manuel, P. 2011. An empirical analysis of ontology-based query expansion for learning resource searches using merlot and the gene ontology. Knowledge-Based Systems 24, 15.
  36. Jinxi, X. and Croft, W. B. 2000. Improving the Effectiveness of Information Retrieval with Local Context Analysis. ACM Transactions on Information Systems, Vol. 18, No. 1, Pages 79–112.
  37. Phonarin, P., S. N., and Haruechaiyasak, C. 2012. Agrix: An ontology based agricultural expertise retrieval framework. Advanced Materials Research 403-408.
  38. Jagdev, B. and Andrew, M. 2013. Ontology Based Query Expansion with a Probabilistic Retrieval Model. 6th Information Retrieval Facility Conference, IRFC.
  39. Kallipolitis, L., Karpis, V., and Karali, I. (2007). World News Finder: How we Cope without the Semantic Web. In: Devedžic, V. (ed.) Proceedings of AIA 2007, pp. 549–221
  40. Aree, T., Asanee, K., Supamard, P. and Uamporn, V. 2009. Ontology Development: A Case Study for Thai Rice. Kasetsart J. (Nat. Sci.) 43 : 594 - 604
  41. Devi, M. U. and Gandhi, G. M. 2015. Wordnet and Ontology Based Query Expansion for Semantic Information Retrieval in Sports Domain. Journal of Computer Science, 2015
  42. Meili L., Xiaobing, S., Shaowei, W., David, L., Yucong, D. 2015. Query Expansion via Wordnet for Effective Code Search. SANER 2015, Montréal, Canada, 978-1-4799-8469-5/15/ 2015 IEEE
  43. Walid, M. and Gareth, J. F. J. 2011. A Study on Query Expansion Methods for Patent Retrieval. PaIR’11, October 24, 2011, Glasgow, ACM 978-1-4503-0955-4/11/10
  44. Dipasree, P., Mandar, M., and Kalyankumar, D. 2014. Improving Query Expansion Using WordNet. Journal of the Association for Information Science and Technology
  45. Rila, M, Tokunaga, T. and Tanaka, H. 1998. The use of wordNet in information retrieval. Workshop on Usage of WordNet in Natural Language Processing Systems
  46. Anna, W., Grzegorz, P., Robert, B., and Teresa, P-M. 2013. Association between Text and Ontologies. Intell. Tools for Building a Scientific Information SCI 467, pp. 305-321.
  47. Davide, B. Paolo, R., Emilio, S. A. 2005. A WordNet-based Query Expansion method for Geographical Information Retrieval.
  48. Jianwei, L., Li, L. and Xiaoyan, L. 2015. An Integrated, Ontology-Based Agricultural Information System. Information Development, Vol. 31(2) 150–163
  49. Tulasi, R. L., Meda, S. R., Ankita, K. and Hgoudar, R. 2017. Ontology Based Automatic Annotation: An Approach for Efficient Retrieval of Semantic Results of Web Documents. Proceedings of the First International Conference on Computational Intelligence and informatics, Advances in Intelligent Systems and Computing 507
  50. Krisztian, B., Jeffrey, D. Antoine, D. and Yusra, I. 2016. Report on the Eighth Workshop on Exploiting Semantic Annotations in Information Retrieval (ESAIR ’15). ACM SIGIR Forum, Vol. 50 No. 1 June 2016
  51. Eyal, O., Knud, H. M., Simon, S., Siegfried, H. and Michael S. 2005. What are Semantic Annotations?
  52. Lawrence, R. and Hyoil, H. 2005. Survey of Semantic Annotation Platforms. 2005 ACM Symposium on Applied Computing.
  53. Mohamed A. H. T., Mohamed, B. A. and Abdelmajid, B. H. 2013. A new semantic relatedness measurement usingWordNet Features. Knowl Inf Syst DOI 10.1007/s10115- 013-0672-4
  54. Sascha, S., Michael, K., Manuel, M., Saikat, M., Alexander, C., Martin, H., and Dorin, C. 2010. Semantic Annotation of Medical Images. Proc. of SPIE Vol. 7628 762808-1
  55. Anne-Marie, T., Stephane, H., and Jean-Yves, A. 2012. Semantic hierarchies for image annotation: A survey. Pattern Recognition 45 (2012) 333-345
  56. Guido, B., Luigi, D. C., Alice, R. and Livio, R. 2014. Learning from syntax generalizations for automatic semantic. J Intell Inf Syst
  57. Thangaraj, M., and Sujatha, G. 2014. An architectural design for effective information retrieval in semantic web. Experts Systems with Applications 41 (2014) 8225 – 8233
  58. Celso, A. F., Maria, C. C. and Ana, M. M. 2013. An Ontology Based Reasoning Approach for Document Annotation. 2013 IEEE Seventh international Conference on Semantic Computing
  59. Hong, Q., Liangliang, Z., and Ying, G. 2010. Semantic Retrieval System Based on Corn Ontology. 2010 Fifth international Conference on Frontier of Computer Science and Technology
  60. Dengsheng, Z., Md, M. I. and Guojun, L. 2012. A review on automatic image annotation technique. Pattern Recognition 45 (2012) 346-362
  61. Vijayarajan, V., Dinakaran, M. Priyam, T., and Mayank, L. 2016. A generic framework for ontology based information retrieval and image retrieval in web data. Human-centric Computing and Information Sciences 6:18
  62. Bechhofer, S. 2009. OWL: Web Ontology Language. Encyclopedia of Database Systems, pp 2008 – 2009
  63. Jeen B., Michel K., Stefan D., Dieter F., Frankvan H., and Ian H. (2002). Enabling knowledge representation on the Web by extending RDF Schema. Computer Networks 39 609–634
  64. Ian, H. (2002). DAML+OIL: A Reason-able Web Ontology Language. International Conference on Extensible Database Technology, EDBT.
  65. Enesi, F. A. and Adewale, O. S. 2015. A Mechanism for Detecting Dead URLs in XTM-Based Ontology Repository International Journal of Computer Applications (0975 – 8887) Volume 111 – No 12.
  66. John, H. G., Mark, A. M., Ray, W. F., Williams, E. G., Monica, C., Henrik, E., Natalya, F. N. and Samson W. T. 2003. The evolution of Protégé: an environment for knowledge-based systems development. International Journal of Human-Computer Studies, Vol. 58, Issue 1, Pages 89 – 123.
  67. Panita, Y., Dussadee, T., Thanapat, S., Asanee, K., Sachit, R., Margherita, S., and Johannes, K. 2008. The AGROVOC Concept Server Workbench: A Collaborative Tool for Managing Multilingual Knowledge. World Conference on Agriculture Information and IT.
  68. Alatrish, E. S. (2013). Comparison Some of Ontology. Journal of Management Information Systems.
  69. Ellen, M. V. and Donna, K. H. 2005. TREC: Experiment and Evaluation in Information Retrieval Computational Linguistic, Volume 32 Number 4.
  70. Miriam, F., Ivan, C., Vanesa, L., David, V., Pablo, C. and Enrico, M. 2011. Semantically enhanced Information Retrieval: an ontology-based approach. Web Semantics: Science, Services and Agents on the World Wide Web. Vol. 9, Issue 4, 434 – 452.


Semantic Web; Ontology; Information Retrieval; Query Expansion; Semantic Annotation; Weights Algorithms