2692-4048ISSN (Online)
2770-0070ISSN (Print)
Volume 15 , Issue 2 , PP: 121-131, 2024 | Cite this article as | XML | Html | PDF | Full Length Article
Duc Truong 1 , Hung Nguyen 2 * , Nha P. Tran 3 , Sang Vu 4 , Hien D. Nguyen 5
Doi: https://doi.org/10.54216/FPA.150211
The knowledge of courses can be represented by using ontology to create intelligent educational systems. This study proposes the Onto-Linking model as a knowledge framework that expresses the knowledge of the inputted schema to investigate the schema linking problem of the Text-to-SQL model. It combines the ontology with the structure of the schema. The proposed ontology is utilized to encapsulate the semantics of the intellectual elements of the schema, such as the table names, column names, foreign/primary key restrictions, and information about the probing schema connection. Therefore, the model makes it easier to accurately translate natural language questions into SQL queries. It improves query creation, helps with error handling, and supports query validation by helping the model better grasp the query's intent. The outcomes of the pedagogically oriented model aimed at guiding learners to comprehend the process of reasoning to attain the respective solution.
Ontology , T5 , Text-to-SQL , Schema linking , E-learning.
[1] L. Wu, P. J. Hsieh, & S. M. Wu, Developing effective e-learning environments through e-learning use mediating technology affordance and constructivist learning aspects for performance impacts: Moderator of learner involvement. The Internet and Higher Education, 2022, vol. 55, 100871.
[2] A. N. Saleem, N. M. Noori, & F. Ozdamli, Gamification applications in E-learning: A literature review. Technology, Knowledge and Learning, 2022, vol. 27, no. 1, 139-159.
[3] H. Nguyen, N. Do, & V. Pham, A methodology for designing knowledge-based systems and applications. In Applications of Computational Intelligence in Multi-Disciplinary Research, 2022,159-185. Academic Press, Elsevier.
[4] H. D. Nguyen, D. A. Tran, H. P. Do, & V. T. Pham, Design an intelligent system to automatically tutor the method for solving problems. International journal of integrated engineering, 2020, vol. 12, no. 7, 211-223.
[5] I. A. Mastan, D. I. Sensuse, R. R. Suryono, & K. Kautsarina, Evaluation of distance learning system (e-learning): a systematic literature review. Jurnal Teknoinfo, 2022, vol. 16, no. 1, 132-137.
[6] T. T. Mai, H. D. Nguyen, T. T. Le, & V. T. Pham, An Intelligent Support System for the Knowledge evaluation in high-school mathematics by Multiple choices testing. In 2018 5th NAFOSTED Conference on Information and Computer Science (NICS) (pp. 282-287). IEEE, 2018.
[7] D. M. Truong, H. D. Nguyen, S. Vu, et al., Construct an intelligent querying system in education based on ontology integration. In 2022 IEEE International Conference on Computing (ICOCO), 340-345, Malaysia, 2022.
[8] B. Svendsen, & S. Kadry, A dataset for recognition of Norwegian sign language. International Journal of Mathematics, Statistics, and Computer Science, 2024, vol. 2.
[9] F. Kedwan, NLQ into SQL translation using computational linguistics. Journal of King Saud University-Computer and Information Sciences, 2022, vol. 34, no. 9, 6564-6582.
[10] Mahmoud Ismail, Naif El-Rashidy, Nabil M. Abdel-aziz, Mobile Cloud Database Security: Problems and Solutions, Journal of Fusion: Practice and Applications, Vol. 7 , No. 1 , (2022) : 15-29 (Doi : https://doi.org/10.54216/FPA.070102)
[11] G. Katsogiannis-Meimarakis, & G. Koutrika, A survey on deep learning approaches for Text-to-SQL. The VLDB Journal, 2023, vol. 32, 905 - 936.
[12] A.T. Nguyen, M.H. Dao, D. Nguyen, A Pilot Study of Text-to-SQL Semantic Parsing for Vietnamese. In Findings of the Association for Computational Linguistics: EMNLP 2020, 4079–4085, Online. Association for Computational Linguistics
[13] L. Wang, B Qin, B Hui, et al., Proton: Probing Schema Linking Information from Pre-trained Language Models for Text-to-SQL Parsing, Proceedings of the 28th ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD 2020), 1889 – 1898, 2022.
[14] A. Vaswani, N. Shazeer, N. Parmar, et al., Attention is all you need. Advances in neural information processing systems, 2017, vol. 30.
[15] K. Nassiri, & M. Akhloufi, Transformer models used for text-based question answering systems. Applied Intelligence, 2023, vol. 53, no. 9, 10602-10635.
[16] S. Grossberg, Recurrent neural networks. Scholarpedia, 2013, vol. 8, no. 2, 1888.
[17] A. Mastropaolo, S. Scalabrino, N. Cooper, et al., Studying the usage of text-to-text transfer transformer to support code-related tasks. In Proceedings of 43rd International Conference on Software Engineering (ICSE 2021), pp. 336-347. IEEE, 2021.
[18] M. H. Hwang, J. Shin, H. Seo, et al., Ensemble-NQG-T5: Ensemble Neural Question Generation Model Based on Text-to-Text Transfer Transformer. Applied Sciences, 2023, vol. 13, no. 2, 903.
[19] V. Zhong, C. Xiong, & R. Socher, Seq2sql: Generating structured queries from natural language using reinforcement learning. Proc. of 6th International Conference of Learning Representation (ICLR 2018), Canada, 2018.
[20] Spider: https://yale-lily.github.io/spider (Access on 31 July 2023)
[21] T. Yu, R. Zhang, K. Yang, et al. Spider: A Large-Scale Human-Labeled Dataset for Complex and Cross-Domain Semantic Parsing and Text-to-SQL Task. Proceedings of the 2018 Conference on Empirical Methods in Natural Language Processing (EMNLP 2018), pages 3911–3921, Brussels, Belgium, 2018.
[22] SYN dataset: https://github.com/ygan/Spider-Syn (Access on 31 July 2023)
[23] H. Nguyen, D. Truong, S. Vu, et al. Knowledge Management for Information Querying System in Education via the Combination of Rela-Ops Model and Knowledge Graph. J. Cases on Inf. Tech. (JCIT), 2023, vol. 25, no. 1, 13.
[24] M. Pham, K. Nguyen, V. T. Nguyen-Le, & H. Nguyen, An intelligent searching system for academic courses of programming based on Ontology Query-Onto. International Journal of Intelligent Systems Design and Computing (IJISDC). 2022, In press.
[25] B. Wang, R. Shin, X. Liu, O. Polozov, & M. Richardson, Rat-sql: Relation-aware schema encoding and linking for Text-to-SQL parsers. Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics (ACL 2020), pp. 7567–7578, 2020.
[26] N. V. Do, H. D. Nguyen, & A. Selamat, Knowledge-based model of expert systems using rela-model. International Journal of Software Engineering and Knowledge Engineering, 2018, vol. 28, no. 08, 1047-1090.
[27] T. Kudo, J. Richardson, SentencePiece: A simple and language independent subword tokenizer and detokenizer for Neural Text Processing. In Proceedings of the 2018 Conference on Empirical Methods in Natural Language Processing: System Demonstrations (EMNLP 2018), pp. 66–71, Brussels, Belgium, 2018.
[28] H.D. Nguyen, H. Huynh, T. Mai, et al., Design an Ontology-based model for Intelligent Querying system in Mathematics Education, Journal of Interdisciplinary Mathematics, 2023, vol. 26, no. 3, 449 – 473,
[29] D. Rothman, Transformers for Natural Language Processing: Build innovative deep neural network architectures for NLP with Python, PyTorch, TensorFlow, BERT, RoBERTa, and more. Packt Publishing Ltd., 2021.
[30] D. Almeida, C. Winter, J. Tang, & W. Zaremba, A generalizable approach to learning optimizers. CoRR abs/2106.00958, 2021.
[31] 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. Proc. 15th International Conference on Evaluation of Novel Approaches to Software Engineering (ENASE 2020), pp. 339-346, 2020.
[32] H. Nguyen, V. Tran, T. Pham, A. T. Huynh, & N. V. Do, Ontology-based Integration of Knowledge Base for Building an Intelligent Searching Chatbot. Sensors & Materials, 2021, vol. 33, no. 9, 3101 – 3121.
[33] H. D. Nguyen, N. V. Do, N. P. Tran, & X. H. Pham, Criteria of a knowledge model for an intelligent problems solver in education. In Proceedings of 10th International Conference on Knowledge and Systems Engineering (KSE 2018), pp. 288-293, Ho Chi Minh, Vietnam, 2018.
[34] M. L. Gillenson, Fundamentals of database management systems. John Wiley & Sons, 2023.
[35] M. S. Baig, A., Imran, A. U. Yasin, et al., Natural language to SQL queries: A review. International Journal of Innovations in Science Technology, 2022, vol. 4, 147-162.
[36] Q. N. Naveed, M. R. N. Qureshi, N. Tairan, et al., Evaluating critical success factors in implementing E-learning system using multi-criteria decision-making. Plos one, 2020, vol. 15, no 5, e0231465.
[37] H. D. Nguyen, T. V. Tran, X. T. Pham, A. T. Huynh, V. T. Pham, & D. Nguyen, Design intelligent educational chatbot for information retrieval based on integrated knowledge bases. IAENG International Journal of Computer Science, 2022, vol. 49, no. 2, 531-541.
