Ecological and confined domain ontology construction scheme using concept clustering for knowledge management

Mahmood, Khalid and Rahmah, M. and Raza, Muhammad Ahsan and Noraziah, Ahmad and Alkazemi, Basem Y. (2023) Ecological and confined domain ontology construction scheme using concept clustering for knowledge management. Applied Sciences, 13 (1). pp. 1-20. ISSN 2076-3417. (Published)

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Abstract

Knowledge management in a structured system is a complicated task that requires common, standardized methods that are acceptable to all actors in a system. Ontology, in this regard, is a primary element and plays a central role in knowledge management, interoperability between various departments, and better decision making. The ontology construction for structured systems comprises logical and structural complications. Researchers have already proposed a variety of domain ontology construction schemes. However, these schemes do not involve some important phases of ontology construction that make ontologies more collaborative. Furthermore, these schemes do not provide details of the activities and methods involved in the construction of an ontology, which may cause difficulty in implementing the ontology. The major objectives of this research were to provide a comparison between some existing ontology construction schemes and to propose an enhanced ecological and confined domain ontology construction (EC-DOC) scheme for structured knowledge management. The proposed scheme introduces five important phases to construct an ontology, with a major focus on the conceptualizing and clustering of domain concepts. In the conceptualization phase, a glossary of domain-related concepts and their properties is maintained, and a Fuzzy C-Mean soft clustering mechanism is used to form the clusters of these concepts. In addition, the localization of concepts is instantly performed after the conceptualization phase, and a translation file of localized concepts is created. The EC-DOC scheme can provide accurate concepts regarding the terms for a specific domain, and these concepts can be made available in a preferred local language.

Item Type: Article
Additional Information: Indexed by Scopus and WOS
Uncontrolled Keywords: Concept clustering; Domain ontology; Knowledge mining; Ontology construction; Ontology localization; Structured knowledge management; Computational intelligence
Subjects: Q Science > QA Mathematics > QA75 Electronic computers. Computer science
Faculty/Division: Institute of Postgraduate Studies
Faculty of Computing
Depositing User: Dr. Rahmah Mokhtar
Date Deposited: 01 Feb 2023 02:36
Last Modified: 01 Feb 2023 02:36
URI: http://umpir.ump.edu.my/id/eprint/36035
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