Review of Semantic Importance and Role of using Ontologies in Web Information Retrieval Techniques


  • Ashraf Ali Faculty of Computer Studies, Arab Open University, Bahrain



Web Information Retrieval, Ontology, Semantics, Multimedia Information Retrieval


The Web contains an enormous amount of information, which is managed to accumulate, researched, and regularly used by many users. The nature of the Web is multilingual and growing very fast with its diverse nature of data including unstructured or semi-structured data such as Websites, texts, journals, and files. Obtaining critical relevant data from such vast data with its diverse nature has been a monotonous and challenging task. Simple key phrase data gathering systems rely heavily on statistics, resulting in a word incompatibility problem related to a specific word's inescapable semantic and situation variants. As a result, there is an urgent need to arrange such colossal data systematically to find out the relevant information that can be quickly analyzed and fulfill the users' needs in the relevant context. Over the years ontologies are widely used in the semantic Web to contain unorganized information systematic and structured manner. Still, they have also significantly enhanced the efficiency of various information recovery approaches. Ontological information gathering systems recover files focused on the semantic relation of the search request and the searchable information. This paper examines contemporary ontology-based information extraction techniques for texts, interactive media, and multilingual data types. Moreover, the study tried to compare and classify the most significant developments utilized in the search and retrieval techniques and their major disadvantages and benefits.


A. Ali, F. Alfaycz and H. Alquhayz, Semantic Similarity Measures Between Words: A Brief Survey. Sci. Int.(Lahore), 30(6), 907-914, 2018.

A. Ali and A. Alourani, An Investigation of Cloud Computing and E-Learning for Educational Advancement. International Journal of Computer Science and Network Security, 21(11), 216-222, 2021.

A. Ali, and I. Ahmad, Concept-based information retrieval approaches on the web: a brief survey. IJAIR, 3(6), 14-18, 2011.

A. Ali and I. Ahmad, A Novel Approach for Information Retrieval on the Web. International Journal of Advance and Innovative Research, 1 (6),20-26, 2012.

A. Ali, I. Ahmad, Information Retrieval Issues on the World Wide Web. International Journal of Computer Technology and Applications, 2(6), 1951-1955, 2011.

A. AlKhunzain, and R. Khan, The Use of M-Learning: A Perspective of Learners’ Perceptions on M-Blackboard Learn. International Journal of Interactive Mobile Technologies (iJIM), 15(2), 4–17, 2021

M. Bendersky, D. Metzler, and W. B. Croft, Effective query formulation with multiple information sources. Paper presented at the Proceedings of the fifth ACM international conference on Web search and data mining, 2012.

T. H. Cao, V. M. Ngo, D.T. Hong, and T. T. Quan, A Named-Entity-Based Multi-Vector Space Model for Semantic Document Clustering. In Proc. of the 1st Pacific-Asia Workshop on Web Mining and Web-Based Application (WMWA'2008, May 20, Osaka, Japan), 2008.

M. A. Casteleiro, M. J. F. Prieto, G. Demetriou, N. Maroto, W. J. Read, D. Maseda-Fernandez, J. J. Des Diz, G. Nenadic, J. A. Keane, and R. Stevens, Ontology Learning with Deep Learning: a Case Study on Patient Safety Using PubMed. Paper presented at the SWAT4LS, 2016.

B. Charron, Y. Hirate, D. Purcell, M. Rezk, , Extracting semantic information for e-commerce. Paper presented at the International Semantic Web Conference, 2016.

D. Chicco, P. Sadowski, and P. Baldi, Deep autoencoder neural networks for gene ontology annotation predictions. Paper presented at the Proceedings of the 5th ACM conference on bioinformatics, computational biology, and health informatics, 2014.

F. Corcoglioniti, M. Dragoni, M. Rospocher, A. P. Aprosio, Knowledge extraction for information retrieval. Paper presented at the European Semantic Web Conference, 2016.

S. Dill, N. Eiron, D. Gibson, D. Gruhl, R. Guha, A. Jhingran, T. Kanungo, S. Rajagopalan, A. Tomkins, and J. A. Tomlin, SemTag and Seeker: Bootstrapping the semantic web via automated semantic annotation. Paper presented at the Proceedings of the 12th international conference on World Wide Web, 2003.

A. Dingli, F. Ciravegna, and Y. Wilks, Automatic semantic annotation using unsupervised information extraction and integration, 2003.

O. Egozi, S. Markovitch, and E. Gabrilovich, Concept-based information retrieval using explicit semantic analysis. ACM Transactions on Information Systems (TOIS), 29(2), 1-34, 2011.

M. K. Elhadad, K. M. Badran, and G. I. Salama, A novel approach for ontology-based feature vector generation for web text document classification. International Journal of Software Innovation (IJSI), 6(1), 1-10, 2018.

F. Ensan, and E. Bagheri, Document retrieval model through semantic linking. Paper presented at the Proceedings of the tenth ACM international conference on web search and data mining, 2017.

H. Ezzikouri, Y. Madani, M. Erritali, and M. Oukessou, A new approach for calculating semantic similarity between words using WordNet and set theory. Procedia Computer Science, 151, 1261-1265, 2019.

S. Gupta, and D. Garg, Comparison of semantic and syntactic information retrieval system on the basis of precision and recall. Int J Data Eng, 2(3), 93-101, 2011.

W. Hersh, Information retrieval Biomedical Informatics. Springer, 755-794, 2021.

P. Hohenecker, and T. Lukasiewicz, Deep learning for ontology reasoning., 2017 arXiv preprint arXiv:1705.10342.

V. Jain, and M. Singh, Ontology based information retrieval in semantic web: A survey. International Journal of Information Technology and Computer Science (IJITCS), 5(10), 62, 2013.

B. Johnston, and S. Webber, As we may think: Information literacy as a discipline for the information age. Research strategies, 20(3), 108-121, 2005.

A. I. Kaloub, Automatic ontology-based document annotation for Arabic information retrieval, 2013.

R. M. I. Khan, A. Ali, A. Alourani, T. Kumar, and M. Shahbaz, M. , An Investigation of the Educational Challenges During COVID-19: A Case Study of Saudi Students' Experience. An Investigation of the Educational Challenges During COVID-19: A Case Study of Saudi Students' Experience, 11(1), 353-363, 2022.

R. M. I. Khan, N. R. M. Radzuan, S. Farooqi, and M.S. Khan, M. S., Learners' Perceptions on WhatsApp Integration as a Learning Tool to Develop EFL Vocabulary for Speaking Skill. International Journal of Language Education, 5(2), 1-14, 2021.

R. M. I. Khan, N.R.M. Radzuan, M. Shahbaz, and A. H. Ibrahim, EFL Instructors’ Perceptions on the Integration and Implementation of MALL in EFL Classes. International Journal of Language Education and Applied Linguistics, 39-50, 2018.

T. Kohonen, T. , Essentials of the self-organizing map. Neural networks, 37, 52-65, 2013.

K. Krishnan, R. Krishnan, and A. Muthumari, A semantic-based ontology mapping–information retrieval for mobile learning resources. International Journal of Computers and Applications, 39(3), 169-178, 2017.

X. Lin, Map displays for information retrieval. Journal of the American Society for information Science, 48(1), 40-54, 1997.

Y. Liu, S. Albanie, A. Nagrani, and A. Zisserman, Use what you have: Video retrieval using representations from collaborative experts. arXiv preprint arXiv:1907.13487, 2019.

Y. Liu, Y. Huang, S. Zhang, D. Zhang, and N. Ling, Integrating object ontology and region semantic template for crime scene investigation image retrieval. Paper presented at the 2017 12th IEEE Conference on Industrial Electronics and Applications (ICIEA), 2017.

A. Meštrović, Collaboration networks analysis: Combining structural and keyword-based approaches. Paper presented at the Semanitic Keyword-based Search on Structured Data Sources, 2017.

V. N. Michalke, and K. Hartig, Explanation Retrieval in Semantic Networks, 2016.

L. Moreno , and P. Martinez, Overlapping factors in search engine optimization and web accessibility. Online Information Review, 2013.

V. N. Murthy, S. Maji, and R. Manmatha, Automatic image annotation using deep learning representations. Paper presented at the Proceedings of the 5th ACM on International Conference on Multimedia Retrieval, 2015.

A. R. Pal, and D. Saha, Word sense disambiguation: A survey, 2015. arXiv preprint arXiv:1508.01346.

A. Panchenko, N. Loukachevitch, D. Ustalov, D. Paperno, C. Meyer, and N. Konstantinova, Russe: The first workshop on russian semantic similarity, 2018. arXiv preprint arXiv:1803.05820.

J. Paralic,and I. Kostial, Ontology-based information retrieval. In Proceedings of the 14th International Conference on Information and Intelligent systems (IIS 2003), Varazdin, Croatia , pp. 23-28, 2003.

G. Petrucci, C. Ghidini, and M. Rospocher, Ontology learning in the deep. Paper presented at the European Knowledge Acquisition Workshop, 2016.

K. Purcell, L. Rainie, and J. Brenner, Search engine use 2012.

F. Ramli, S. A. Noah, and T.B. Kurniawan, Ontology-based information retrieval for historical documents. Paper presented at the 2016 Third International Conference on Information Retrieval and Knowledge Management (CAMP), 2016.

E. M. Sanfilippo, F. Belkadi, and A. Bernard, Ontology-based knowledge representation for additive manufacturing. Computers in Industry, 109, 182-194, 2019.

B. Selvalakshmi, and M. Subramaniam, Intelligent ontology based semantic information retrieval using feature selection and classification. Cluster Computing, 22(5), 12871-12881, 2019.

M. Shahbaz, and R. M. I. Khan, Use of mobile immersion in foreign language teaching to enhance target language vocabulary learning. MIER Journal of Educational Studies Trends and Practices, 66-82, 2017.

V. Vijayarajan, M. Dinakaran, P. Tejaswin, and M. Lohani, A generic framework for ontology-based information retrieval and image retrieval in web data. Human-centric Computing and Information Sciences, 6(1), 1-30, 2016.

Y. Yang, Semi-structured semantic overlay for information retrieval in self-organizing networks. Paper presented at the Proceedings of the 21st International Conference on World Wide Web, 2012.

J. Ye, S. Dasiopoulou, G. Stevenson, G. Meditskos, E. Kontopoulos, I. Kompatsiaris, and S Dobson, Semantic web technologies in pervasive computing: A survey and research roadmap. Pervasive and Mobile Computing, 23, 1-25, 2015.

X. Ye, H. Shen, X. Ma, R. Bunescu, and C. Liu, From word embeddings to document similarities for improved information retrieval in software engineering. Paper presented at the Proceedings of the 38th international conference on software engineering, 2016.

H. Yu, T. Mine, and M. Amamiya, An architecture for personal semantic web information retrieval system. Paper presented at the Special interest tracks and posters of the 14th international conference on World Wide Web, 2005.

N. Zhang, Y.-F. Pu, and P. Wang, An ontology-based approach for chinese legal information retrieval. Paper presented at the Proc. CENet, 2015.

D. Zomahoun, Collaborative Semantic Annotation of Images: Ontology-Based Model. Paper presented at the Signal & Image Processing: An International Journal (SIPIJ), 2013.




How to Cite

Ali, A. (2022). Review of Semantic Importance and Role of using Ontologies in Web Information Retrieval Techniques. International Journal of Computer and Information Technology(2279-0764), 11(1).