Please use this identifier to cite or link to this item: https://hdl.handle.net/20.500.12540/447
Title: An SQL domain ontology learning for analyzing hierarchies of structures in pre‑Learning assessment agents
Authors: Ehimwenma, Kennedy E. 
Crowther, Paul 
Beer, Martin 
Al‑Sharji, Safiya 
Issue Date: 2020
Publisher: Springer Nature
Source: Ehimwenma, K. E., Crowther, P., Beer, M., & Al-Sharji, S. (2020). An SQL domain ontology learning for analyzing hierarchies of structures in pre-learning assessment agents. SN Computer Science, 1(6), 1-19.
Journal: SN Computer Science 
Abstract: This paper presents the use of description logics (DL) in the definition and development of a Structured Query Language (SQL) domain ontology for a multi-agent based pre-assessment system. Description logics is a knowledge representation language for defining terms or classes, the relationships between classes, their instances, including individuals and literals. In a formal school curriculum, modules of learning are inter-dependent. So, teaching and learning follows an ordered sequence of learning from lower-level module(s) to higher-level ones. This process enables students to gain mastery of lower-level materials before moving up the ladder to higher-level learning. To describe an SQL ontology and its representation for a multi-agent based system application, this paper uses a description logic language to present the organization of learning modules into DesiredConcept <DD>, PrerequisiteConcept <CC> and LeafNodes <NN> as well as their associated relationships, namely, hasPrerequisite and hasKB between the learning modules. The paper thus presents a TBox and an Abox of a DL ontology and further transformation into a first-order predicate for a multi-agent based system that was implemented in Jason.
URI: https://hdl.handle.net/20.500.12540/447
DOI: 10.1007/s42979-020-00338-1
Appears in Collections:Scholarly Publications

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