Domain Ontology Extraction from a Glossary: Case of the Phosphate Industry
Domain Ontology Extraction from a Glossary: Case of the Phosphate Industry |
||
 |
 |
|
| © 2025 by IJETT Journal | ||
| Volume-73 Issue-1 |
||
| Year of Publication : 2025 | ||
| Author : Oussama Chabih, Sara Sbai, Mohammed Reda Chbihi Louhdi, Hicham Behja |
||
| DOI : 10.14445/22315381/IJETT-V73I1P106 | ||
How to Cite?
Oussama Chabih, Sara Sbai, Mohammed Reda Chbihi Louhdi, Hicham Behja, "Domain Ontology Extraction from a Glossary: Case of the Phosphate Industry," International Journal of Engineering Trends and Technology, vol. 73, no. 1, pp. 77-85, 2025. Crossref, https://doi.org/10.14445/22315381/IJETT-V73I1P106
Abstract
Ontologies play a crucial role in structuring domain-specific knowledge, enabling more efficient search, discovery, and data interoperability across different systems. In this context, an innovative approach to transform domain-specific glossaries into ontologies, with a focus on the phosphate industry, is proposed in this paper. Unlike traditional methods that depend solely on transformation rules, the proposed approach combines empirical and algorithmic techniques to detect relationships between glossary terms, resulting in a more accurate and comprehensive ontology. The proposed method was applied to the OCP Group’s internal glossary, successfully generating an OWL2 ontology that significantly improves search and discovery within the organization’s knowledge management systems. The experiment’s results demonstrate that the proposed method outperforms existing techniques in terms of accuracy and relevance, providing a robust framework for knowledge representation in specialized industrial contexts.
Keywords
OWL2 Ontology, Ontology extraction, Transformation rules, Jaccard similarity, Glossary vocabulary.
References
[1] Benamar Bouougada et al., “Mapping Relational Database to Owl Ontology Based on MDE Settings,” Artificial Intelligence Review, vol. 35, pp. 217-222, 2021.
[CrossRef] [Google Scholar] [Publisher Link]
[2] Batool Lakzaei, and Mehrnoush Shamsfard, “Ontology Learning from Relational Databases,” Information Sciences, vol. 577 pp. 280-297, 2021.
[CrossRef] [Google Scholar] [Publisher Link]
[3] Bilal Ben Mahria, Ilham Chaker, and Azeddine Zahi, “A Novel Approach for Learning Ontology from Relational Database: from The Construction to the Evaluation,” Journal of Big Data, vol. 8, 2021.
[CrossRef] [Google Scholar] [Publisher Link]
[4] Len Yabloko, The OntoBase-Protégé, 2023. [Online]. Available: https://protegewiki.stanford.edu/wiki/OntoBase
[5] Olivier Curé, Myriam Lamolle, and Chan Le Duc, “Ontology Based Data Integration Over Document and Column Family Oriented NOSQL,” Arxiv, pp. 1-16, 2013.
[CrossRef] [Google Scholar] [Publisher Link]
[6] V.K. Kiran, and R. Vijayakumar, “Ontology Based Data Integration of NoSQL Datastores,” 2014 9th International Conference on Industrial and Information Systems (ICIIS), Gwalior, India, pp. 1‑6, 2014.
[CrossRef] [Google Scholar] [Publisher Link]
[7] Hanen Abbes, Soumaya Boukettaya, and Faiez Gargouri, “Learning Ontology from Big Data through MongoDB Database,” 2015 IEEE/ACS 12th International Conference of Computer Systems and Applications (AICCSA), Marrakech, Morocco, pp. 1‑7, 2015.
[CrossRef] [Google Scholar] [Publisher Link]
[8] Simin Jabbari, and Kilian Stoffel, “Ontology Extraction from MongoDB using Formal Concept Analysis,” 2017 2nd International Conference on Knowledge Engineering and Applications (ICKEA), London, UK, pp. 178‑182, 2017.
[CrossRef] [Google Scholar] [Publisher Link]
[9] Bernhard Ganter, and Rudolf Wille, Formal Concept Analysis: Mathematical Foundations, Berlin Heidelberg: Springer-Verlag, 1st ed., pp. 1-370, 1999.
[CrossRef] [Google Scholar] [Publisher Link]
[10] Yuangang Yao et al., “An Automatic Semantic Extraction Method for Web Data Interchange,” 2014 6th International Conference on Computer Science and Information Technology (CSIT), Amman, Jordan, pp. 148‑152, 2014.
[CrossRef] [Google Scholar] [Publisher Link]
[11] Thomas Lampoltshammer, and Thomas Heistracher, “Ontology Evaluation with Protégé using OWLET,” Infocommunications Journal, vol. 6, no. 2, pp. 12-17, 2014.
[Google Scholar] [Publisher Link]
[12] Gui-hyun Baek, Su-kyoung Kim, and Ki-hong Ahn, “Framework for Automatically Construct Ontology Knowledge Base From Semi Structured Datasets,” 2015 10th International Conference for Internet Technology and Secured Transactions (ICITST), London, UK, pp. 152‑157, 2015.
[CrossRef] [Google Scholar] [Publisher Link]
[13] Martin Seidel et al., “KESeDa: Knowledge Extraction from Heterogeneous Semi-Structured Data Sources,” Proceedings of the 12th International Conference on Semantic Systems, New York, USA, pp. 129‑136, 2016.
[CrossRef] [Google Scholar] [Publisher Link]
[14] Roberto Navigli, and Paola Velardi, “From Glossaries to Ontologies: Extracting Semantic Structure from Textual Definitions,” Proceedings of the 2008 Conference on Ontology Learning and Population: Bridging the Gap between Text and Knowledge, pp. 71-87, 2008.
[Google Scholar] [Publisher Link]
[15] Katarina Grolinger, Kevin P. Brown, and Miriam A.M. Capretz, “From Glossaries to Ontologies: Disaster Management Domain,” SEKE 2011 - Proceedings of the 23rd International Conference on Software Engineering and Knowledge Engineering, pp. 402-407, 2011.
[Google Scholar] [Publisher Link]
[16] Guntis Arnicans, Dainis Romans, and Uldis Straujums, “Semi-automatic Generation of a Software Testing Lightweight Ontology from a Glossary Based on the ONTO6 Methodology,” Frontiers in Artificial Intelligence and Applications, vol. 249 pp. 263-276, 2013.
[CrossRef] [Google Scholar] [Publisher Link]
[17] José R. Hilera et al., “An Evolutive Process to Convert Glossaries into Ontologies,” Information Technology and Libraries, vol. 29, pp. 195 204, 2010.
[CrossRef] [Google Scholar] [Publisher Link]
[18] Karin Koogan Breitman, and Julio Cesar Sampaio do Prado Leite, “Lexicon Based Ontology Construction,” Lecture Notes in Computer Science, Software Engineering for Multi-Agent Systems II Springer Berlin Heidelberg, vol. 2940, pp. 19-34, 2004.
[CrossRef] [Google Scholar] [Publisher Link]
[19] Loris Bozzato, Mauro Ferrari, and Alberto Trombetta, “Building A Domain Ontology from Glossaries: A General Methodology,” CEUR Workshop Proceedings, Rome, Italy, vol. 426, pp. 1-10, 2008.
[Google Scholar] [Publisher Link]
[20] Guntis Arnicans, and Uldis Straujums, “Transformation of the Software Testing Glossary into A Browsable Concept Map,” Lecture Notes in Electrical Engineering, Innovations and Advances in Computing, Informatics, Systems Sciences, Networking and Engineering, vol. 313, pp. 349-356, 2015.
[CrossRef] [Google Scholar] [Publisher Link]
[21] Xianming Tang et al., “Construction and Application of an Ontology-Based Domain-Specific Knowledge Graph for Petroleum Exploration and Development,” Geoscience Frontiers, vol. 14, no. 5, pp. 1-11, 2023.
[CrossRef] [Google Scholar] [Publisher Link]
[22] Tom Gruber, Ontology, Encyclopedia of Database Systems, Springer-Verlag, 2009. [Online]. Available: https://tomgruber.org/writing/definition-of-ontology/
[23] Bill Swartout et al., “Towards Distributed Use of Large-Scale Ontologies,” Association for the Advancement of Artificial Intelligence Spring Symposium Series on Ontological Engineering, Stanford University, CA, pp. 138-148, 1997.
[Google Scholar] [Publisher Link]