Design an ontology-based model for intelligent querying system in mathematics education

Nguyen, Hien D.; Huynh, Hoa; Mai, Thanh T.; Tran, Dung A.; Nguyen, Diem; Nguyen-Le, Van-Thanh

doi:10.47974/JIM-1674

Open Access Research Article

Design an ontology-based model for intelligent querying system in mathematics education

Hien D. Nguyenhiennd@uit.edu.vnAffiliation 1University of Information TechnologyHo Chi Minh city, VietnamAffiliation 2Vietnam National UniversityHo Chi Minh city, VietnamView full profile → , Hoa Huynhhqhoa99@gmail.comIndustrial University of Ho Chi Minh city (IUH)Ho Chi Minh city, VietnamView full profile → , Thanh T. Maithanhmt@hiu.vnHong Bang International UniversityHo Chi Minh city, VietnamView full profile → , ^*Dung A. TranCorresponding authordungta@uit.edu.vnAffiliation 1University of Information TechnologyHo Chi Minh city, VietnamAffiliation 2Vietnam National UniversityHo Chi Minh city, VietnamView full profile → , Diem Nguyendiemntn@uit.edu.vnAffiliation 1University of Information TechnologyHo Chi Minh city, VietnamAffiliation 2Vietnam National UniversityHo Chi Minh city, VietnamView full profile → , Van-Thanh Nguyen-Lethanhnlv@hcmute.edu.vnHCMC University of Technology and EducationHo Chi Minh city, VietnamView full profile →

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pp. 449–473Vol. 26Issue 3April 2023DOI: 10.47974/JIM-1674XML

Published Online:: 01 Apr 2023
Article type:: Research Article
Language:: EN
Article no.:: JIM-1674
Pages:: 449–473

Abstract

Distance learning can be facilitated through e-learning, and students can enhance their understanding of course materials through the use of an intelligent querying system that enables self-learning. In this paper, an ontology-based method for organizing the knowledge of mathematics in high-school is presented. Ontology Rela-Ops model, which is a knowledge model for representing the knowledge of relations and operators, is combined with the knowledge component of functions. Based on the combining model, a structure of knowledge graph is proposed to represent relations of intellectual contents. An intelligent querying system is designed for the domain of high-school mathematics using these structures. This searching system can query contents of the course and extracts other knowledge related to querying results. The experimental results show that the proposed method is useful and effective to apply in the practice.

Keywords

Ontology Knowledge graph Intelligent searching system High-school mathematics Education Knowledge engineering

Subject Classifications

00A05 (Mathematics in general)03B70 (Logic in computer science)

References

[1] N.W. Gleason, Higher education in the era of the fourth industrial revolution, Springer Nature, (2018).
[2] A. Meena, A. Vaish, S. Meena, et. al., A mathematical model for analysing the significance of Information Technology resources in school education during pandemic, Journal of Interdisciplinary Mathematics, 25(3), pp. 741-752, (2022).
[3] M. Littman, et. al., Gathering Strength, Gathering Storms: The One Hundred Year Study on Artificial Intelligence (AI100) 2021 Study Panel Report, Stanford University, Stanford, CA, Sept. 2021. http://ai100.stanford.edu/2021-report
[4] H. Nguyen, N. Do, N. Tran, X.H. Pham, V. Pham, Some criteria of the Knowledge Representation method for an Intelligent Problem Solver in STEM education. Applied Computational Intelligence and Soft Computing, Vol. 2020, Article ID 9834218, (2020).
[5] I. Hatzilygeroudis, J. Prentzas, Knowledge Representation in Intelligent Educational Systems, In: Z. Ma (Ed.), Web-Based Intelligent E-Learning Systems: Technologies and Applications, IGI Global, (2006).
[6] M. Tapia-Leon, A. Rivera, J. Chicaiza, S. Luján-Mora, Application of ontologies in higher education: A systematic mapping study, Proceedings of 2018 IEEE Global Engineering Education Conference (EDUCON 2018), pp. 1344-1353, (2018).
[7] N. Noy, D. McGuinness (Eds.), Final Report on the 2013 NSF Workshop on Research Challenges and Opportunities in Knowledge Representation, NSF Workshop Report, (2013).
[8] K. Giri, Role of ontology in semantic web. DESIDOC Journal of Library Information Technology, 31(2), 116-120, (2011).
[9] A.C. Khadir, H. Aliane, A. Guessoum, Ontology learning: Grand tour and challenges, Computer Science Review, 39, 100339, (2021).
[10] C. Grosan, A. Abraham, Intelligent Systems: A modern approach, Springer, Berlin, Heidelberg, (2011).
[11] N.V. Do, H.D. Nguyen, L.N. Hoang, Some Techniques for Intelligent Searching on Ontology-based Knowledge Domain in e-Learning, Proceedings of 12th International Conference on Knowledge Engineering and Ontology Development (KEOD 2020), pp. 313-320, Budapest, Hungary, (2020).
[12] A. Espen, Why you should choose math in high school, Ubiquity, 7(11), (2006). https://ubiquity.acm.org/article.cfm?id=1125361
[13] P.G.W. Adnyana, I.M. Suarsana, I.G.P Suharta, Multi-Representation Discourse Model and Math Problem Solving Skills of High School Students, Journal of Learning Improvement and Lesson Study, 1(1), 40-48, (2021).
[14] S.M. Stefanov, On some properties of linear functionals, Journal of Interdisciplinary Mathematics, 25(8), pp. 2491-2502, (2022).
[15] D.H. Nguyen, A.D. Tran, P.H. Do, et. al., Design an intelligent system to automatically tutor the method for solving problems, International Journal of Integrated Engineering, 12(7), pp. 211-223, (2020).
[16] E. Mousavinasab, N. Zarifsanaiey, R. Niakan, et. al., Intelligent tutoring systems: a systematic review of characteristics, applications, and evaluation methods, Interactive Learning Environments, 29(1), pp. 142-163, (2021).
[17] R.B. Kaliwal, S.L. Deshpande, Study on Intelligent Tutoring System for Learner Assessment Modeling Based on Bayesian Network. Proceedings of 5th International Joint Conference on Advances in Computational Intelligence (IJCACI 2021), pp. 389-397, Dhaka, Bangladesh, Oct. 2021, (2021).
[18] L.W. Somathilake, A mathematical model for control strategies of COVID-19, Journal of Interdisciplinary Mathematics, 25(8), pp. 2365-2386, (2022).
[19] N. Do, H. Nguyen, T. Mai, Intelligent Educational Software in Discrete Mathematics and Graph Theory, Proceedings of 17th International Conference on Intelligent Software Methodologies, Tools, and Techniques (SOMET 2018), pp. 925 - 938, Granada, Spain, (2018).
[20] H.D., Nguyen, N. Do, Intelligent Problems Solver in Education for Discrete Mathematics, Proceedings of 16th International Conference on Intelligent Software Methodologies, Tools, and Techniques (SOMET 2017), pp. 21-34, Kitakyushu, Japan, (2017).
[21] X.T. Pham, T.V. Tran, V.T. Nguyen-Le, V.T. Pham, H.D. Nguyen, Build a search engine for the knowledge of the course about Introduction to Programming based on ontology Rela-model, Proceedings of 2020 12th IEEE International Conference on Knowledge and Systems Engineering (KSE 2020), pp. 207 - 212, Can Tho, Vietnam, (2020).
[22] T. Le, et. al., Knowledge representation method for designing an Intelligent Tutoring System in Learning of courses about Algorithms. Proceedings of 25th Asia-Pacific Conference on Communications (APCC 2019), pp. 310-315, Ho Chi Minh city, Vietnam, (2019).
[23] H. Nguyen, et. al., A method for knowledge representation to design Intelligent Problems Solver in mathematics based on Rela-Ops model. IEEE Access 8, 76991-77012, (2020).
[24] M. Basaldella, E. Antolli, G. Serra, C. Tasso, Bidirectional LSTM Recurrent Neural Network for Keyphrase Extraction, Proc. Italian Research Conference on Digital Libraries (IRCDL 2018), pp. 180-187), Udine, Italy, (2018).
[25] H.D. Nguyen, V. Tran, T. Pham, A.T. Huynh, N. Do, Ontology-based Integration of Knowledge Base for Building an Intelligent Searching Chatbot, Sensors and Materials, Vol. 33, No. 9, pp. 3101-3121, (2021).
[26] Vietnam Ministry of Education and Training, Textbooks and workbooks of mathematics in high school, Publisher of Education, (2021).
[27] H. Nguyen, N. Do, T. Pham, A method for designing Knowledge-based Systems and Application. In: A. Elgnar et. al. (Eds.). Applications Computational Intelligence Multi-Disciplinary Research, Academic Press, Elsevier, (2022).
[28] H.D. Nguyen, T. Huynh, S.N. Hoang, V.T. Pham, I. Zelinka, Language-oriented Sentiment Analysis based on the grammar structure and improved Self-attention network, Proceedings of 15th International Conference on Evaluation of Novel Approaches to Software Engineering (ENASE 2020), pp. 339-346, Prague, Czech Public, May 2020.
[29] X. Chen, S. Jia, Y. Xiang, A review: Knowledge reasoning over knowledge graph, Expert Systems with Applications, 141, 112948, (2020).
[30] X. Wu, Y. Li, J. Wang, Q. Qian, Y. Guo, UBAR: User Behavior-Aware Recommendation with knowledge graph, Knowledge-Based Systems, Vol. 254, 109661, (2022).
[31] M. Gionfriddo, A remarkable connection between k-permutations and colourings of graphs, Journal of Interdisciplinary Mathematics, 14(1), pp. 95-104, (2011).
[32] T. Mai, et. al. An Intelligent Support System for the Knowledge evaluation in high-school mathematics by Multiple choices testing. Proceedings of 5th NAFOSTED Conference on Information and Computer Science (NICS 2018), pp. 282-287, Ho Chi Minh city, Vietnam, (2018).
[33] H. Chen, Personalized recommendation system of e-commerce based on big data analysis. Journal of Interdisciplinary Mathematics, 21(5), pp.1243-1247, (2018).
[34] Y. Zhou, C. Huang, Q. Hu, et. al., Personalized learning full-path recommendation model based on LSTM neural networks, Information Sciences, 444, pp.135-152, (2018).

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