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Ontology COKB for Knowledge Representation and Reasoning in Designing Knowledge-Based Systems

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Intelligent Software Methodologies, Tools and Techniques (SoMeT 2014)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 513))

Abstract

Knowledge Representation and Reasoning is at the heart of the great challenge of Artificial Intelligence, especially knowledge-based systems, expert systems and intelligent problem solvers. The models for knowledge such as logics, semantic networks, conceptual graphs, frames and classes are useful tools to design the above systems. However, they are not suitable to represent knowledge in the domains of reality applications. Designing of the knowledge bases and the inference engines of those systems in practice requires representations in the form of ontologies. For applications such as the intelligent problem solver in plane geometry, the knowledge contains a complicated system of concepts, relations, operators, functions, and rules. This situation motivates an ontology-based solution with such components. In this article, an ontology called Ontology of Computational Object Knowledge Base (COKB), will be presented in details. We also present a model for representing problems together reasoning algorithms for solving them, and design methods to construct applications. The above methodology has been used in designing many applications such as systems for solving analytic geometry problems, solving problems in plane geometry, and the expert system for diabetic micro vascular complication diagnosis.

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Authors and Affiliations

  1. University of Information Technology, National University Ho Chi Minh City, Ho Chi Minh City, Vietnam

    Nhon V. Do

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  1. Nhon V. Do
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Correspondence to Nhon V. Do .

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Editors and Affiliations

  1. Iwate Prefectural University, Takizawa, Japan

    Hamido Fujita

  2. Universiti Teknologi Malaysia, Johor Baharu, Malaysia

    Ali Selamat

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Do, N.V. (2015). Ontology COKB for Knowledge Representation and Reasoning in Designing Knowledge-Based Systems. In: Fujita, H., Selamat, A. (eds) Intelligent Software Methodologies, Tools and Techniques. SoMeT 2014. Communications in Computer and Information Science, vol 513. Springer, Cham. https://doi.org/10.1007/978-3-319-17530-0_8

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  • DOI: https://doi.org/10.1007/978-3-319-17530-0_8

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  • Publisher Name: Springer, Cham

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  • Online ISBN: 978-3-319-17530-0

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