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

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, a...

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Main Authors: Mahmood, Khalid, Rahmah, M., Raza, Muhammad Ahsan, Noraziah, Ahmad, Alkazemi, Basem Y.
Format: Article
Language:English
Published: MDPI 2023
Subjects:
Online Access:http://umpir.ump.edu.my/id/eprint/36035/1/applsci-13-00032-v2.pdf
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author Mahmood, Khalid
Rahmah, M.
Raza, Muhammad Ahsan
Noraziah, Ahmad
Alkazemi, Basem Y.
author_facet Mahmood, Khalid
Rahmah, M.
Raza, Muhammad Ahsan
Noraziah, Ahmad
Alkazemi, Basem Y.
author_sort Mahmood, Khalid
collection UMP
description 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.
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spelling UMPir360352023-02-01T02:36:03Z http://umpir.ump.edu.my/id/eprint/36035/ Ecological and confined domain ontology construction scheme using concept clustering for knowledge management Mahmood, Khalid Rahmah, M. Raza, Muhammad Ahsan Noraziah, Ahmad Alkazemi, Basem Y. QA75 Electronic computers. Computer science 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. MDPI 2023 Article PeerReviewed pdf en cc_by_4 http://umpir.ump.edu.my/id/eprint/36035/1/applsci-13-00032-v2.pdf 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) https://doi.org/10.3390/ app13010032 https://doi.org/10.3390/app13010032
spellingShingle QA75 Electronic computers. Computer science
Mahmood, Khalid
Rahmah, M.
Raza, Muhammad Ahsan
Noraziah, Ahmad
Alkazemi, Basem Y.
Ecological and confined domain ontology construction scheme using concept clustering for knowledge management
title Ecological and confined domain ontology construction scheme using concept clustering for knowledge management
title_full Ecological and confined domain ontology construction scheme using concept clustering for knowledge management
title_fullStr Ecological and confined domain ontology construction scheme using concept clustering for knowledge management
title_full_unstemmed Ecological and confined domain ontology construction scheme using concept clustering for knowledge management
title_short Ecological and confined domain ontology construction scheme using concept clustering for knowledge management
title_sort ecological and confined domain ontology construction scheme using concept clustering for knowledge management
topic QA75 Electronic computers. Computer science
url http://umpir.ump.edu.my/id/eprint/36035/1/applsci-13-00032-v2.pdf
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