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Cited 52 time in webofscience Cited 75 time in scopus
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Process-centered knowledge model and enterprise ontology for the development of knowledge management system

Authors
Han, Kwan HeePark, Jun Woo
Issue Date
May-2009
Publisher
PERGAMON-ELSEVIER SCIENCE LTD
Keywords
Knowledge management system (KMS); Enterprise ontology; Knowledge retrieval; Business process; Business performance
Citation
EXPERT SYSTEMS WITH APPLICATIONS, v.36, no.4, pp 7441 - 7447
Pages
7
Indexed
SCIE
SCOPUS
Journal Title
EXPERT SYSTEMS WITH APPLICATIONS
Volume
36
Number
4
Start Page
7441
End Page
7447
URI
https://scholarworks.gnu.ac.kr/handle/sw.gnu/26317
DOI
10.1016/j.eswa.2008.09.031
ISSN
0957-4174
1873-6793
Abstract
Among many enterprise assets, knowledge is treated as a critical driving force for attaining enterprise performance goals. This is because knowledge facilitates the better business decision makings in a timely fashion. However, since knowledge is created and utilized during the execution of business processes, if knowledge is separated from the business process context, it does not lead to the ability to take the right action for target performance. This paper proposes the framework for process-centered knowledge model and enterprise ontology for the context-rich and networked knowledge storage and retrieval required during task execution. The enterprise knowledge object for a process-centered knowledge model is classified into two types: process knowledge and task Support knowledge. In the proposed enterprise ontology, which represents major enterprise concepts, and the relationships between them, all domain concepts are related to the "process" concept, both directly and indirectly. As a result, networked and sophisticated knowledge, rather than single-level knowledge. is provided to the participant of unit activity. In order to show the applicability of the proposed framework, a process-centered KMS (knowledge management system) was also developed, which is classified into 3 parts: (1) project management sub-system based on process knowledge. (2) Knowledge management sub-system for maintaining task support knowledge. (3) Infrastructure sub-system which supports the above two sub-systems. (C) 2008 Elsevier Ltd. All rights reserved.
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공과대학 > Department of Industrial and Systems Engineering > Journal Articles

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