A semi-automatic approach to construct Vietnamese ontology from online text
Open accessAbstract
An ontology is an effective formal representation of knowledge used commonly in artificial intelligence, semantic web, software engineering, and information retrieval. In open and distance learning, ontologies are used as knowledge bases for e-learning supplements, educational recommenders, and question answering systems that support students with much needed resources. In such systems, ontology construction is one of the most important phases. Since there are abundant documents on the Internet, useful learning materials can be acquired openly with the use of an ontology. However, due to the lack of system support for ontology construction, it is difficult to construct self-instructional materials for Vietnamese people. In general, the cost of manual acquisition of ontologies from domain documents and expert knowledge is too high. Therefore, we present a support system for Vietnamese ontology construction using pattern-based mechanisms to discover Vietnamese concepts and conceptual relations from Vietnamese text documents. In this system, we use the combination of statistics-based, data mining, and Vietnamese natural language processing methods to develop concept and conceptual relation extraction algorithms to discover knowledge from Vietnamese text documents. From the experiments, we show that our approach provides a feasible solution to build Vietnamese ontologies used for supporting systems in education.
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Based on Nguyen and Yang's suggestion, the aims of developing an AI-integrated system in education could be grouped into four types: classification (5 studies), matching (3 studies), recommendation (5 studies), and deep learning (10 studies).
“Based on the above and Nguyen and Yang's suggestion [28], the aims of developing an AI-integrated system in education could be grouped into four types: classification (5 studies), matching (3 studies), recommendation (5 studies), and deep learning (10 studies).”
From A Review of Artificial Intelligence (AI) in Education from 2010 to 2020 (2021) · cites this paper as [28]
The Conclusion and Future Research section (page unavailable) identifies text classification and recommendation systems as possible applications of the ontology, which supports two of the cited categories. It does not suggest the four-part grouping: matching and deep learning are not included. The study counts appear to be the citing authors’ own grouping, rather than figures attributed to Nguyen and Yang. (LLM, conf=0.83)
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Leveraging Artificial Intelligence for Enhanced Project Completion in EducationPreprint
Swargiary, K. (2023) · Research Square · doi:10.21203/rs.3.rs-3462413/v1
- Authors
- Nguyen, B.-A., & Yang, D.-L.
- Affiliations
- Tra Vinh University (VN)
- Feng Chia University (TW)
- Venue
- The International Review of Research in Open and Distributed Learning
- Publisher
- Athabasca University Press
- Published
- 2012-11-15
- Volume
- 13
- Issue
- 5
- Pages
- 148
- ISSN
- 1492-3831 (ISSN-L)
- OpenAlex
- W1580488490
- Cited by
- 9
- References
- 17
- Citations by year
- 2023: 1 · 2022: 1 · 2021: 3 · 2017: 1 · 2015: 2 · 2014: 1
- FWCI
- 0.94
- Type
- journal article
- Language
- en
- Open access
- diamond
- doi.org
- Licence
- cc-by
- Locations
- The International Review of Research in Open and Distributed Learning (publishedVersion, cc-by)
- DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
- Érudit (Université de Montréal) (submittedVersion, cc-by)
- Topics
- Physical Sciences › Computer Science › Artificial Intelligence › Semantic Web and Ontologies
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Biomedical Text Mining and Ontologies
- Physical Sciences › Computer Science › Artificial Intelligence › Natural Language Processing Techniques
- Keywords
- ontology construction, Vietnamese language, concept extraction, relation extraction, semi-automatic knowledge acquisition, online texts, online learning
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