Research Article Open Access

Enhancing Semantic Web Retrieval Through Ontology-Driven Feature Extraction: A Novel Proposition

Meer Hazar Khan1, Muhammad Imran Sharif2, Mehwish Mehmood3, Fernaz Narin Nur4, Md Palash Uddin5, Zahid Akhtar6, Kamran Siddique7 and Sadia Waheed Awan8
  • 1 Department of Computer Science, Institute of Southern Punjab, Multan, Pakistan
  • 2 Department of Computer Science, Kansas State University, Manhattan, United States
  • 3 School of Electronics, Electrical Engineering and Computer Science, Queen’s University Belfast, Belfast, United Kingdom
  • 4 Department of Computer Science and Engineering, Notre Dame University Bangladesh, Dhaka, Bangladesh
  • 5 School of Information Technology, Deakin University, Geelon, Australia
  • 6 Department of Network and Computer Security, State University of New York Polytechnic Institute, Utica, United States
  • 7 Department of Computer Science and Engineering, University of Alaska Anchorage, Anchorage, United States
  • 8 Department of Computer Science, University of Wah, Wah Cantt, Pakistan


Web images represent unstructured data sets which often lead to challenges when users try to locate distinct images via text-based searches on the web. Such difficulties stem from different factors, e.g., redundant image storage, irrelevant metadata tags, and incorrect associations. To overcome this issue, we propose a semantic model based on the ontology language that enables users to find images that exactly match their queries. The proposed technique employs a simple procedure where users generate image captions by constructing an ontology for each image in the repository. In order to fit the existing ontology domains, the ontology generation relies on information gathered from the image's visual and textual elements, including low-level features like color, name, and shape. Next, constructing the ontology establishes accurate relationships with existing ontology concepts using the "an" and "is a part of" relationships. The resulting text with immersed ontology information yields accurate results, leading to easy retrieval using semantics keyword searches. Our framework relies on two main ontology concepts, i.e., animals and vehicles. In this study, we used a dataset of MAT files comprising images, content, and information to study the ontology of animals (e.g., wolves, foxes, and dogs) as well as the ontology of vehicles. The overall comparative evaluation of the proposed framework was performed under various conditions to obtain valuable insights.

Journal of Computer Science
Volume 20 No. 5, 2024, 487-494


Submitted On: 10 September 2023 Published On: 23 February 2024

How to Cite: Khan, M. H., Sharif, M. I., Mehmood, M., Nur, F. N., Uddin, M. P., Akhtar, Z., Siddique, K. & Awan, S. W. (2024). Enhancing Semantic Web Retrieval Through Ontology-Driven Feature Extraction: A Novel Proposition. Journal of Computer Science, 20(5), 487-494.

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  • Semantic
  • Metadata
  • Redundancy
  • Local and Global Features
  • Ontology
  • Owl
  • RDF Schema