• International Journal of CAD/CAM
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• v.5 no.1
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• pp.99-109
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• 2005

This paper introduces an approach to an ontology-based multi-level knowledge framework for a knowledge management system for discrete-product development. Participants in a product life cycle want to share comprehensive product knowledge without any ambiguity and heterogeneity. However, previous knowledge management approaches are limited in providing those aspects: therefore, we suggest an ontology-based multi-level knowledge framework (OBMKF). The bottom level, the axiom, specifies the semantics of concepts and relations of knowledge so ambiguity can be alleviated. The middle level is a product development knowledge map; it defines the concepts and the relations of the product domain knowledge and guides the engineer to process their engineering decisions. The middle level is then classified further into more detailed levels, such as generic product level, specific product level, product version level, and manufactured item level, according to the various viewpoints. The top level is specialized knowledge for a specific domain that gives the solution of a specific task or problem. It is classified into three knowledge types: expert knowledge, engineering function knowledge, and data-analysis-based knowledge. This proposed framework is based on ontology to accommodate a comprehensive range of knowledge and is represented with first-order logic to maintain a uniform representation.

• International journal of advanced smart convergence
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• v.12 no.2
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• pp.34-46
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• 2023

A growing number of large scale knowledge graphs raises several issues how knowledge graph data can be organized, discovered, and integrated efficiently. We present a novel semantic-based mashup platform for contents convergence which consists of acquisition, RDF storage, ontology learning, and mashup subsystems. This platform servers a basis for developing other more sophisticated applications required in the area of knowledge big data. Moreover, this paper proposes an entity matching method using graph convolutional network techniques as a preliminary work for automatic classification and discovery on knowledge big data. Using real DBP15K and SRPRS datasets, the performance of our method is compared with some existing entity matching methods. The experimental results show that the proposed method outperforms existing methods due to its ability to increase accuracy and reduce training time.

• Journal of the Korean Society of Safety
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• v.38 no.5
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• pp.15-26
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• 2023

The relationship between the knowledge, attitude, and practice of the person in charge of designating a Class III facility was analyzed to improve its practice. As a field of knowledge, system knowledge and technical knowledge were considered, and attitudes were divided into cognitive, affective, and behavioral attitudes. A knowledge, attitude, and practice (KAP) survey was conducted, and the relationship among them was analyzed through correlation and regression analyses. The factors affecting the level of practice in designating the Class III facility were technical knowledge in the field of knowledge and cognitive and behavioral attitudes in the field of attitudes. Cognitive and behavioral attitudes were the two factors that most influenced the practice of designating a Class III facility. It is thought that the higher the level of cognitive and behavioral attitudes, the greater the ability to practice designating the Class III facility. The general characteristics of respondents influencing cognitive and behavioral attitudes were analyzed by safety inspection.

• Proceedings of the Korean Institute of Building Construction Conference
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• 2005.05a
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• pp.157-160
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• 2005

The purpose of this paper is to develop a framework for strategic construction knowledge management. The variables of proposed framework includes knowledge types, strategic business functions, and engineering data types. The Proposed framework and knowledge action Plan for the construction company will contribute to develop knowledge management system related to engineering capabilities of strategic business functions

• Korean Journal of Computational Design and Engineering
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• v.5 no.3
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• pp.232-241
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• 2000

Even though we have greater chances to accomplish successful collaborative design by utilizing recent proliferation of networks, current practices do not fully take advantage of the information infrastructure. There are so much data over the networks, but not enough knowledge about the data is available to users. The main objectives of the product data interface system proposed in this paper are to capture more knowledge on managing product data and to provide users effective search capability. We define the metadata model for product data defined in STEP AP 203 and manage the metadata from product data in a repository system. Because we utilize the standard formats such as STEP for product data and RDF for metadata, the proposed approach can be applied to various fields of industries independently on commercial products.

• Journal of Smart Tourism
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• v.4 no.1
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• pp.19-29
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• 2024

The objective of this article is to create a model of integrated management from the framework modeling of a digital collaborative network supported by knowledge engineering to make heritage site in the Brazil more effective. It is an exploratory and qualitative research with thematic analysis as technique of data analysis from the collaborative network, digital platform, world heritage, and tourism themes. The snowballing approach was chosen, and the mapping and classification of relevant studies was developed with the use of the spreadsheet tool and the Mendeley® software. The results show that the collaborative network model oriented towards strategic objectives should be supported by a digital platform that provides a technological environment that adds functionalities and digital platform services with the integration of knowledge engineering techniques and tools, enabling the discovery and sharing of knowledge in the collaborative network.

• Journal of the Korean Society for Precision Engineering
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• v.23 no.3 s.180
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• pp.22-31
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• 2006

This paper introduces an approach to an ontology-based knowledge framework for product life cycle management (PLM). Participants in a product life cycle want to share comprehensive product knowledge without any ambiguity and heterogeneity. However, previous knowledge management approaches are limited in providing those aspects. Therefore, we suggest an ontology-based knowledge framework including knowledge maps, axioms and specific knowledge far domain. The bottom level, the axiom, specifies the semantics of concepts and relations of knowledge so that ambiguity of the semantics can be alleviated. The middle level is a product development knowledge map; it defines the concepts and the relations of the product domain common knowledge and guides engineers to process their engineering decisions. The middle level is then classified further into more detailed levels, such as generic product level, specific product level, product version level, and product item level for PLM. The top level is specialized knowledge fer a specific domain that gives the solution of a specific task or problem. It is classified into three knowledge types: expert knowledge, engineering function knowledge, and data-analysis-based knowledge. This proposed framework is based on ontology to accommodate a comprehensive range of unambiguous knowledge for PLM and is represented with first-order logic to maintain a uniform representation.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2006.05a
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• pp.613-614
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• 2006

Design data, information, and knowledge have complex associations with each other. Systems related with the management of the data, information, and knowledge are various, and the representations are numerous. Therefore it is difficult to construct a knowledge based design system with a full association knowledge for supporting the design tasks. In this research, OWL based ontology model for an excavator design is developed for the representation of the relationships. Also an ontology model is used to develop the knowledge based excavator design system.

• Journal of Korean Society for Quality Management
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• v.38 no.3
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• pp.294-312
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• 2010

Data Technology (DT) is a new technology which deals with data collection, data analysis, information generation from data, knowledge generation from modelling and future prediction. DT is a newly emerged interdisciplinary science & technology in this 21st century knowledge society. Even though the main body of DT is applied statistics, it also contains management information system (MIS), quality management, process system analysis and so on. Therefore, it is an interdisciplinary science and technology of statistics, management science, industrial engineering, computer science and social science. In this paper, first of all, the definition of DT is given, and then the effects and the basic properties of DT, the differences between IT and DT, the 6 step process for DT application, and a DT example are provided. Finally, the relationship among DT, e-Statistics and Data Mining is explained, and the direction of DT development is proposed.

• International Journal of Computer Science & Network Security
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• v.21 no.4
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• pp.209-213
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• 2021

Data mining is the application of specific algorithms for extracting patterns from data and KDD is the automated or convenient extraction of patterns representing knowledge implicitly stored or captured in large databases, data warehouses, the Web, other massive information repositories or data streams. Data mining can be used for decision making in educational system. But educational institution does not use any knowledge discovery process approach on these data; this knowledge can be used to increase the quality of education. The problem was happening in the educational management system, but to make education system more flexible and discover knowledge from it huge data, we will use data mining techniques to solve problem.