Autors: Ivanova, T. I., Terzieva V.
Title: Ontology Learning in Educational Systems
Keywords: e-learning, intelligent e-learning environment, ontology learning, personalization

Abstract: E-learning content and participants in the learning process are usually annotated with metadata. Complicated metadata models are necessary for organizing personalized learning, so an ontological metadata representation is used. Since ontologies represent static knowledge, changes in e-learning systems and related description metadata require frequent changes to corresponding ontologies. Only a few professionals in the educational domain have some expertise in ontology development. So, maximal possible automation is of great importance for the development and maintenance of knowledge models, needed for intelligent e-learning environments. Ontology learning is an approach for automatic ontology development and evolution, affected significantly by recent advances in Artificial Intelligence and Language Models. The main objective of this study is to explore and analyze ontology learning approaches and techniques and the specifics of their use in an intelligent e-learning environment. It examines and summarizes recent scientific research to reveal the degree of development and the extent to which ontology learning is applied to support personalized tutoring. The paper outlines trends and challenges of ontology learning from textual e-learning content and comprehensively discusses ontology learning and its applications in intelligent e-learning. It also describes a use case concerning the implementation and practical usage of ontology learning.

References

  1. Zhu Z.T. Yu M.H. Riezebos P. A Research Framework of Smart Education Smart Learn. Environ. 2016 3 4 10.1186/s40561-016-0026-2
  2. Rico-Bautista D. Medina-Cardenas Y. Coronel-Rojas L.A. Cuesta-Quintero F. Maestre-Gongora G. Guerrero C.D. Smart University: Key Factors for an Artificial Intelligence Adoption Model Advances and Applications in Computer Science, Electronics and Industrial Engineering García M.V. Fernández-Peña F. Gordón-Gallegos C. AISC Springer Singapore 2021 Volume 1307 153 166 10.1007/978-981-33-4565-2_10
  3. Huang L.-S. Su J.-Y. Pao T.-L. A Context Aware Smart Classroom Architecture for Smart Campuses Appl. Sci. 2019 9 1837 10.3390/app9091837
  4. Iqbal H.M.N. Parra-Saldivar R. Zavala-Yoe R. Ramirez-Mendoza R.A. Smart Educational Tools and Learning Management Systems: Supportive Framework Int. J. Interact. Des. Manuf. 2020 14 1179 1193 10.1007/s12008-020-00695-4
  5. Ilić M. Mikić V. Kopanja L. Vesin B. Intelligent Techniques in E-Learning: A Literature Review Artif. Intell. Rev. 2023 56 14907 14953 10.1007/s10462-023-10508-1
  6. Popchev I.P. Orozova D.A. Towards Big Data Analytics in the E-Learning Space Cybern. Inf. Technol. 2019 19 16 24 10.2478/cait-2019-0023
  7. Terzieva V. Ilchev S. Todorova K. Andreev R. Towards a Design of an Intelligent Educational System IFAC-PapersOnLine 2021 54 363 368 10.1016/j.ifacol.2021.10.474
  8. Ilchev S. Alexandrov A. Ilcheva Z. Design of a Laser Projection System for Intelligent Learning Environments Proceedings of International Conference on Data Science and Applications Saraswat M. Roy S. Chowdhury C. Gandomi A.H. LNNS Springer Singapore 2022 Volume 288 89 103 10.1007/978-981-16-5120-5_8
  9. Peng H. Ma S. Spector J.M. Personalized Adaptive Learning: An Emerging Pedagogical Approach Enabled by a Smart Learning Environment Smart Learn. Environ. 2019 6 9 10.1186/s40561-019-0089-y
  10. Bontchev B. Antonova A. Dankov Y. Educational Video Game Design Using Personalized Learning Scenarios Computational Science and Its Applications—ICCSA 2020 Gervasi O. Murgante B. Misra S. Garau C. Blečić I. Taniar D. Apduhan B.O. Rocha A.M.A.C. Tarantino E. Torre C.M. et al. LNTCS Springer Cham, Switzerland 2020 Volume 12254 829 845 10.1007/978-3-030-58817-5_59
  11. Ivanova T. Terzieva V. Ivanova M. Intelligent Technologies in E-Learning: Personalization and Interoperability Proceedings of the International Conference on Computer Systems and Technologies ’21 Ruse, Bulgaria 18 June 2021 ACM New York, NY, USA 2021 176 181
  12. Blagoev I. Vassileva G. Monov V. A Model for E-Learning Based on the Knowledge of Learners Cybern. Inf. Technol. 2021 21 121 135 10.2478/cait-2021-0023
  13. Trichkova-Kashamova E. Paunova-Hubenova E. Boneva Y. Dimitrov S. Criteria and Approaches for Optimization of Innovative Methods for STEM Education Proceedings of the 22th IFAC Conference on Technology, Culture and International Stability (TECIS 2024) Sofia, Bulgaria 11–13 September 2024 IFAC Papers Online Elsevier Waterford, Ireland 2024 Volume 58 123 128 10.1016/j.ifacol.2024.07.137
  14. Villegas-Ch W. García-Ortiz J. Enhancing Learning Personalization in Educational Environments through Ontology-Based Knowledge Representation Computers 2023 12 199 10.3390/computers12100199
  15. Kaur P. Sharma P. Vohra N. An Ontology Based E-Learning System Int. J. Grid Distrib. Comput. 2015 8 273 278 10.14257/ijgdc.2015.8.5.27
  16. MaduraiMeenachi N. Sai Baba M. A Survey on Usage of Ontology in Different Domain Int. J. Appl. Inf. Syst. (IJAIS) 2012 4 46 55 10.5120/ijais12-450666
  17. Khadir A.C. Aliane H. Guessoum A. Ontology Learning: Grand Tour and Challenges Comput. Sci. Rev. 2021 39 100339 10.1016/j.cosrev.2020.100339
  18. Konys A. Knowledge Systematization for Ontology Learning Methods Procedia Comput. Sci. 2018 126 2194 2207 10.1016/j.procs.2018.07.229
  19. Rahayu N.W. Ferdiana R. Kusumawardani S.S. A Systematic Review of Ontology Use in E-Learning Recommender System Comput. Educ. Artif. Intell. 2022 3 100047 10.1016/j.caeai.2022.100047
  20. Asim M.N. Wasim M. Khan M.U.G. Mahmood W. Abbasi H.M. A Survey of Ontology Learning Techniques and Applications Database 2018 2018 bay101 10.1093/database/bay101
  21. Iyer V. Mohan L. Bhatia M. Reddy Y.R. A Survey on Ontology Enrichment from Text Proceedings of the 16th International Conference on Natural Language Processing Hyderabad, India 18–21 December 2019 NLP Association of India International Institute of Information Technology Hyderabad, India 2019 95 104
  22. Lande D.V. Dmytrenko O.O. Using Part-of-Speech Tagging for Building Networks of Terms in Legal Sphere Proceedings of the 5th International Conference on Computational Linguistics and Intelligent Systems (COLINS 2021) Kharkiv, Ukraine 22–23 April 2021 87 97
  23. Aparna K. Bhakta P. Vijaykumar S. A Review on Different Approaches of Pos Tagging in NLP Proceedings of the Information Technology & Bioinformatics: International Conference on Advance IT, Engineering and Management—SACAIM-2022 Ulaanbaatar, Mongolia 28–29 October 2022 Volume 1 47 51 10.25215/8119070682.09
  24. Blandón Andrade J.C. Zapata Jaramillo C.M. Gate-Based Rules for Extracting Attribute Values Comput. Sist. 2021 25 851 862 10.13053/cys-25-4-3493
  25. OpenNLP—Apache OpenNLP Library (accessed on 22 December 2025) Available online: https://opennlp.apache.org
  26. Stanford CoreNLP API (accessed on 22 December 2025) Available online: https://stanfordnlp.github.io/CoreNLP/api.html
  27. WordNet-Based Java Library (accessed on 22 December 2025) Available online: https://github.com/extjwnl/extjwnl
  28. Braga M. Milanese G.C. Pasi G. Investigating Large Language Models’ Linguistic Abilities for Text Preprocessing arXiv 2025 10.48550/arXiv.2510.11482
  29. Sen S. Tao J. Deokar A.V. On the Role of Ontologies in Information Extraction Reshaping Society Through Analytics, Collaboration, and Decision Support Iyer L.S. Power D.J. Springer International Publishing Cham, Switzerland 2015 Volume 18 115 133 10.1007/978-3-319-11575-7_8
  30. Kang S. Patil L. Rangarajan A. Moitra A. Jia T. Robinson D. Ameri F. Dutta D. Extraction of Formal Manufacturing Rules from Unstructured English Text Comput.-Aided Des. 2021 134 102990 10.1016/j.cad.2021.102990
  31. Byeon H. Chunduri V. Narang G. Alghayadh F.Y. Soni M. Ramesh J.V.N. Deep Learning Model for Recommendation System Using Web of Things Based Knowledge Graph Mining Serv. Oriented Comput. Appl. 2025 19 57 76 10.1007/s11761-024-00409-8
  32. Unified Medical Language System Available online: https://www.nlm.nih.gov/research/umls/index.html (accessed on 22 December 2025)
  33. Jiang X. Tan A. CRCTOL: A Semantic-based Domain Ontology Learning System J. Am. Soc. Inf. Sci. 2010 61 150 168 10.1002/asi.21231
  34. Zepeda-Mendoza M.L. Resendis-Antonio O. Hierarchical Agglomerative Clustering Encyclopedia of Systems Biology Springer Berlin/Heidelberg, Germany 2013 Volume 43 886 887
  35. Ismail R. Abu Bakar Z. Abd Rahman N. Extracting knowledge from English Translated Quran using NLP Pattern J. Teknol. 2015 77 67 73 10.11113/jt.v77.6515
  36. Panchenko A. Faralli S. Ruppert E. Remus S. Naets H. Fairon C. Ponzetto S.P. Biemann C. TAXI at SemEval-2016 Task 13: A Taxonomy Induction Method Based on Lexico-Syntactic Patterns, Substrings and Focused Crawling Proceedings of the 10th International Workshop on Semantic Evaluation (SemEval-2016) San Diego, CA, USA 16–17 June 2016 Association for Computational Linguistics Stroudsburg, PA, USA 2016 1320 1327
  37. Mukanova A. Milosz M. Dauletkaliyeva A. Nazyrova A. Yelibayeva G. Kuzin D. Kussepova L. LLM-Powered Natural Language Text Processing for Ontology Enrichment Appl. Sci. 2024 14 5860 10.3390/app14135860
  38. Zhu Y. Wang X. Chen J. Qiao S. Ou Y. Yao Y. Deng S. Chen H. Zhang N. LLMs for Knowledge Graph Construction and Reasoning: Recent Capabilities and Future Opportunities World Wide Web 2024 27 58 10.1007/s11280-024-01297-w
  39. Babaei Giglou H. D’Souza J. Auer S. LLMs4OL: Large Language Models for Ontology Learning The Semantic Web—ISWC 2023 Payne T.R. Presutti V. Qi G. Poveda-Villalón M. Stoilos G. Hollink L. Kaoudi Z. Cheng G. Li J. Springer Nature Cham, Switzerland 2023 Volume 14265 408 427 10.1007/978-3-031-47240-4_22
  40. Ma C. Molnár B. Ontology Learning from Relational Database: Opportunities for Semantic Information Integration Vietnam J. Comp. Sci. 2022 9 31 57 10.1142/S219688882150024X
  41. Lakzaei B. Shamsfard M. Ontology Learning from Relational Databases Inf. Sci. 2021 577 280 297 10.1016/j.ins.2021.06.074
  42. Lin L. Xu Z. Ding Y. OWL Ontology Extraction from Relational Databases via Database Reverse Engineering J. Softw. 2013 8 2749 2760 10.4304/jsw.8.11.2749-2760
  43. Xu Z. Ni Y. He W. Lin L. Yan Q. Automatic Extraction of OWL Ontologies from UML Class Diagrams: A Semantics-Preserving Approach World Wide Web 2012 15 517 545 10.1007/s11280-011-0147-z
  44. Papasalouros A. Retalis S. Papaspyrou N. Semantic Description of Educational Adaptive Hypermedia Based on a Conceptual Model J. Educ. Technol. Soc. 2004 7 129 142
  45. Brunzel M. The XTREEM Methods for Ontology Learning from Web Documents Proceedings of the 2008 Conference on Ontology Learning and Population: Bridging the Gap Between Text and Knowledge Patras, Greece 21–22 September 2008 IOS Press Amsterdam, The Netherlands 2008 3 26
  46. Kawakami T. Morita T. Yamaguchi T. Building up Ontologies from the EnglishWikipedia and Comparing with YAGO Trans. Jpn. Soc. Artif. Intell. 2020 35 C-J32_1-14 10.1527/tjsai.C-J32
  47. Gorodetsky V. Tushkanova O. Learning an Ontology of Text Data Advances in Fuzzy Systems and Soft Computing: Selected Contributions to the 10th International Conference “Integrated Models and Soft Computing in Artificial Intelligence” (IMSC-2021), Kolomna, Russia, 17–20 May 2021 CEUR Workshop Proceedings CEUR-WS Aachen, Germany 2021 1 8
  48. Chen J. Gu J. ADOL: A Novel Framework for Automatic Domain Ontology Learning J. Supercomput. 2021 77 152 169 10.1007/s11227-020-03261-7
  49. Navarro-Almanza R. Juárez-Ramírez R. Licea G. Castro J.R. Automated Ontology Extraction from Unstructured Texts Using Deep Learning Intuitionistic and Type-2 Fuzzy Logic Enhancements in Neural and Optimization Algorithms: Theory and Applications Castillo O. Melin P. Kacprzyk J. Springer International Publishing Cham, Switzerland 2020 Volume 862 727 755 10.1007/978-3-030-35445-9_50
  50. Tramontana E. Verga G. Ontology Enrichment with Text Extracted from Wikipedia Proceedings of the 2022 5th International Conference on Software Engineering and Information Management (ICSIM) Yokohama, Japan 14–16 January 2022 ACM New York, NY, USA 2022 113 117 10.1145/3520084.3520102
  51. Bhatt B. Unsupervised Multilingual Ontology Learning Proceedings of the 2019 14th International Joint Symposium on Artificial Intelligence and Natural Language Processing (iSAI-NLP) Macau, China 20–22 November 2019 IEEE Chiang Mai, Thailand 2019 1 7 10.1109/iSAI-NLP48611.2019.9045197
  52. Lau R.Y.K. Song D. Li Y. Cheung T.C.H. Hao J.-X. Toward a Fuzzy Domain Ontology Extraction Method for Adaptive E-Learning IEEE Trans. Knowl. Data Eng. 2009 21 800 813 10.1109/TKDE.2008.137
  53. Capuano N. Dell’Angelo L. Orciuoli F. Miranda S. Zurolo F. Ontology Extraction from Existing Educational Content to Improve Personalized E-Learning Experiences Proceedings of International Conference on Semantic Computing IEEE Piscataway, NJ, USA 2009 577 582 10.1109/ICSC.2009.69
  54. Atapattu T. Falkner K. Falkner N. A Comprehensive Text Analysis of Lecture Slides to Generate Concept Maps Comput. Educ. 2017 115 96 113 10.1016/j.compedu.2017.08.001
  55. Ivanova T. Adaptive Open Corpus E-Learning and Authoring, Using Collaborative Ontology Learning Proceedings of the 9th International Conference on Emerging eLearning Technologies and Applications (ICETA) Starý Smokovec, Slovakia 27–28 October 2011 IEEE Piscataway, NJ, USA 2011 83 87 10.1109/ICETA.2011.6112591
  56. Gaeta M. Orciuoli F. Paolozzi S. Salerno S. Ontology Extraction for Knowledge Reuse: The e-Learning Perspective IEEE Trans. Syst. Man Cybern.-Part A Syst. Hum. 2011 41 798 809 10.1109/TSMCA.2011.2132713
  57. Casali A. Deco C. Romano A. Tomé G. An Assistant for Loading Learning Object Metadata: An Ontology Based Approach Interdiscip. J. e-Ski. Lifelong Learn. 2013 9 077 087 10.28945/1789
  58. Ivanova T. A Semi-Automatic Ontology Learning Method for E-Learning Resources Terminology Extraction Proceedings of the International Conference on Interactive Collaborative Learning (ICL2010) Hasselt, Belgium 15–17 September 2010 1030 1034
  59. Louhdi M.R.C. Behja H. El Alaoui S.O. A Novel Method for Generating an E-Learning Ontology Int. J. Data Min. Knowl. Manag. Process 2013 3 151 10.5121/ijdkp.2013.3610
  60. Khoiruddin M. Kusumawardani S.S. Hidayah I. Fauziati S. A Review of Ontology Development in the E-Learning Domain: Methods, Roles, Evaluation Proceedings of the 2023 International Conference on Computer, Control, Informatics and Its Applications (IC3INA) Bandung, Indonesia 4 October 2023 262 267 10.1109/IC3INA60834.2023.10285789
  61. Lee C.-S. Wang M.-H. Kuan W.-K. Ciou Z.-H. Tsai Y.-L. Chang W.-S. Li L.-C. Kubota N. Huang T.-X. Sato-Shimokawara E. et al. A Study on AI-FML Robotic Agent for Student Learning Behavior Ontology Construction Proceedings of the 2020 International Symposium on Community-Centric Systems Tokyo, Japan 23–26 September 2020 1 6 10.1109/CcS49175.2020.9231339
  62. Li G. Tang C. Chen L. Deguchi D. Yamashita T. Shimada A. LLM-Driven Ontology Learning to Augment Student Performance Analysis in Higher Education Knowledge Science, Engineering and Management Springer Nature Singapore 2024 Volume 14886 57 68 10.1007/978-981-97-5498-4_5
  63. Li J. Garijo D. Poveda-Villalón M. Large Language Models for Ontology Engineering: A Systematic Literature Review 2025 (accessed on 22 December 2025) Available online: https://www.semantic-web-journal.net/system/files/swj3864.pdf
  64. Abu-Salih B. Alotaibi S. A systematic literature review of knowledge graph construction and application in education Heliyon 2024 10 e25383 10.1016/j.heliyon.2024.e25383
  65. Chang M. D’Aniello G. Gaeta M. Orciuoli F. Sampson D. Simonelli C. Building ontology-driven tutoring models for intelligent tutoring systems using data mining IEEE Access 2020 8 48151 48162 10.1109/ACCESS.2020.2979281
  66. Giglou H.B. D’Souza J. Mihindukulasooriya N. Auer S. Llms4ol 2025 overview: The 2nd large language models for ontology learning challenge Open Conf. Proc. 2025 6 1 17 10.52825/ocp.v6i.2913
  67. Yang T. Ren B. Gu C. He T. Ma B. Konomi S.I. Leveraging LLMs for Automated Extraction and Structuring of Educational Concepts and Relationships Mach. Learn. Knowl. Extr. 2025 7 103 10.3390/make7030103
  68. Doumanas D. Bouchouras G. Soularidis A. Kotis K. Vouros G. From human-to LLM-centered collaborative ontology engineering Appl. Ontol. 2024 19 334 367 10.1177/15705838241305067

Issue

Information (Switzerland), vol. 17, 2026, Albania, https://doi.org/10.3390/info17020147

Вид: статия в списание, публикация в издание с импакт фактор, публикация в реферирано издание, индексирана в Scopus