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An SQL Domain Ontology Learning for Analyzing Hierarchies of Structures in Pre-Learning Assessment Agents

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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 \(<{{\varvec{D}}}>\), PrerequisiteConcept \(<{{\varvec{C}}}>\) and LeafNodes \(<{{\varvec{N}}}>\) 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.

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Authors and Affiliations

  1. Department of Computer Science, Wenzhou-Kean University, Wenzhou, China

    Kennedy E. Ehimwenma

  2. Department of Computer Science, International College, Hunan University of Arts and Science, Hunan, China

    Kennedy E. Ehimwenma

  3. Department of Computing, Sheffield Hallam University, Sheffield, UK

    Paul Crowther & Martin Beer

  4. Department of Information Technology, University of Technology and Applied Sciences, Muscat, Oman

    Safiya Al-Sharji

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  1. Kennedy E. Ehimwenma
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  2. Paul Crowther
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  4. Safiya Al-Sharji
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Correspondence to Kennedy E. Ehimwenma.

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Ehimwenma, K.E., Crowther, P., Beer, M. et al. An SQL Domain Ontology Learning for Analyzing Hierarchies of Structures in Pre-Learning Assessment Agents. SN COMPUT. SCI. 1, 335 (2020). https://doi.org/10.1007/s42979-020-00338-1

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