• Journal of Korean Elementary Science Education
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• v.38 no.4
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• pp.484-495
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• 2019

This study divided pre-service elementary school teachers' knowledge conversion into four types, socialization, externalization, combination and internalization, based on their inquiry activities on the life cycle of cabbage butterfly. As research subjects, this study collected results from 24 pre-service elementary school teachers who carried out inquires on the life cycle of cabbage butterfly for about 2 months. The type of socialization indicates the conversion of tacit knowledge into tacit knowledge, and this study found out that pre-service elementary school teachers acquired and accumulated tacit knowledge from their fellow pre-service teachers, professors and even acquaintances inside and outside the lab. However, there appeared no process that they shared their tacit knowledge with other pre-service teachers or delivered it to them. The type of externalization indicates the conversion of tacit knowledge into explicit knowledge, and this study discovered some cases that pre-service elementary school teachers expressed their inner tacit knowledge into explicit knowledge. However, there was no case found that they converted the verbally-unexpressed tacit knowledge of their fellow teachers or experts into well-defined explicit knowledge. The type of combination indicates the conversion of explicit knowledge into explicit knowledge, and this study discovered some cases that they collected explicit knowledge and converted it into new explicit knowledge for the acquisition, integration and delivery or distribution of explicit knowledge. However, there were few cases that they creatively devised new explicit knowledge by acquiring new knowledge through direct observation and supplementing the existing explicit knowledge. The type of internalization indicates the conversion of explicit knowledge into tacit knowledge, and this study discovered both explicit knowledge embodied through personal experiences and explicit knowledge embodied through simulations and experiments that formed tacit knowledge in process of examining the existing explicit knowledge.

• Asia pacific journal of information systems
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• v.30 no.2
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• pp.228-251
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• 2020

This study attempts to examine the importance of social capital in customer service organizations and clarifies how translates into organizational performance through knowledge management activities. A survey was conducted with the customer service employees, and 256 questionnaires were used for an empirical analysis with smart partial least squares (PLS). The analysis found that relational capital had a positive effect on both the knowledge management components of knowledge sharing and knowledge conversion, while structural capital significantly influenced knowledge sharing. In addition, human capital positively affected knowledge conversion. Both knowledge sharing and knowledge conversion significantly influenced organizational performance. This study proposed a conceptual framework of social capital that influences organizational performance mediated by an organization's knowledge management activities. Based on the results, we suggest practical guidelines for managing social capital and recommend areas of improvement for customer organization's managers and employees.

• Information Systems Review
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• v.3 no.2
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• pp.261-276
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• 2001

The purpose of this research is to review how Korean KM companies are applying information technology to their operations from the four perspectives of knowledge conversion (KC) and to suggest ideas for introducing appropriate knowledge management implementation methodology through the case studies of Korean KM companies that have adopted knowledge management strategy using information technology. This research was conducted focusing on the cases of companies that are carrying out knowledge management by applying information technology and the result shows that Korean KM companies place high value on the application of information technology in introducing knowledge management. However, the use of information technology is not common to all kind of companies in four kinds of knowledge conversion.

• Proceedings of the Korea Society of Design Studies Conference
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• 2001.10a
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• pp.11.2-11
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• 2001

• Journal of the Korean Institute of Intelligent Systems
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• v.17 no.1
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• pp.123-129
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• 2007

On the Semantic Web, the content of the documents must be explicitly represented through metadata in order to enable contents-based inference. In this study, we propose a mechanism to convert the Conceptual Graph (CG) into Resource Description Framework (RDF). Quite a large number or representation languages for representing knowledge on the Web have been established over the last decade. Most of these researches are focused on design of independent knowledge description. On the Semantic Web, however, a knowledge conversion mechanism will be needed to exchange the knowledge used in independent devices. In this study, the CG could give an entire conceptual view of knowledge and RDF can represent that knowledge on the Semantic Web. Then the CG-based object oriented PROLOG could support the natural inference based on that knowledge. Therefore, our proposed knowledge conversion mechanism will be used in the designing of Semantic Web-based knowledge representation and inference systems.

• Research in Mathematical Education
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• v.14 no.4
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• pp.323-332
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• 2010

It is the development of a mathematics teachers' teaching knowledge that manifests a mathematics teacher's professional knowledge growth. It is becoming a direct and effective approach of conversion of mathematical knowledge into the knowledge of mathematics teaching. Through the investigation, the study revealed that the knowledge conversion process of mathematics teachers in middle school is restricted by three aspects including eight factors. From this point, the authors have structured the path and model on influencing factors of middle school Mathematics Teaching Knowledge Conversion (MPCK), and discuss the mechanism of the transformation process.

• Management & Information Systems Review
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• v.17
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• pp.161-189
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• 2005

As the importance of intellectual assets has been brought into relief, this study aims at positively verifying where the intellectual workers' overall level of their knowledge conversion preference and their job character has reached, and how much the knowledge conversion preference, the job character and the fitness of both factors affects the job effectiveness respectively. For this purpose 3 types of research hypotheses were set up and the result of the verification of the hypotheses is summarized as follows: First, the verification of the relation between the knowledge conversion preference and the job effectiveness revealed that the workers who have the higher synthetic ability in knowledge conversion preference show the higher job satisfaction and job product. Secondly, the verification of the relation between the MPS representing the job character by measured index and the job satisfaction revealed that the absolute value of relative coefficient between the 4 factors excluding the public welfare factor and the MPS is 4, interpreted as medium correlation. Thirdly, the analysis on the degree of relation between the job product measured by the quality of job result and the input effort and the MPS showed that the absolute value of person relative coefficient is 5, interpreted not only as medium correlation but also very meaningful. Accordingly, the main purpose of this study was to give a guideline which can be utilized as an indicator for educating, training and placing the workers. As results, the main effect that the variable of knowledge conversion preference and job character chosen as the independent variable influences on the dependent variable of job satisfaction and job product is very meaningful except the public welfare factor.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.11 no.1
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• pp.1-7
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• 2011

Most of expert systems use the text-oriented knowledge bases. However, knowledge management using the knowledge bases is considered as a huge burden to the knowledge workers because it includes some troublesome works. It includes chasing and/or checking activities on Consistency, Redundancy, Circulation, and Refinement of the knowledge. In those cases, we consider that they could reduce the burdens by using relational database management systems-based knowledge management infrastructure and convert the knowledge into one of easy forms human can understand. Furthermore they could concentrate on the knowledge itself with the support of the systems. To meet the expectations, in this study, we have tried to develop a general-purposed knowledge conversion tool for expert systems. Especially, this study is focused on the knowledge conversions among text-oriented knowledge base, relational database knowledge base, and decision tree.

• Knowledge Management Research
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• v.5 no.2
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• pp.25-51
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• 2004

The purpose of this study is to investigate the knowledge creating pattern of technology catching-up and pioneering phase in the new product development process. This paper first reviews the knowledge conversion, absorptive capability, learning orientation and the trigger of learning. The paper then presents the integrative model of knowledge creating. Based on the integrative model, in-depth case analysis was conducted on the new product development process in Phicom. As a result, the paper discuss that the pattern of absorptive capability building, knowledge conversion and knowledge transfer is different from technology catching-up and pioneering phase. Finally, the implications and limitations of the study are discussed.

• Journal of Korea Society of Digital Industry and Information Management
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• v.6 no.1
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• pp.91-103
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• 2010

This paper introduces efficient rule-based semantic search techniques to ontology-based knowledge commerce services. Primarily, the search techniques presented in this paper define rules of reasoning that are required for users to search using the concept of ontology, multiple characteristics, relations among concepts and data type. In addition, based on the defined rules, the rule-based reasoning techniques search ontology for knowledge commerce services. This paper explains the conversion rules of query which convert user's query language into semantic search words, and transitivity rules which enable users to search related tags, knowledge products and users. Rule-based sematic search techniques are also presented; these techniques comprise knowledge search modules that search ontology using validity examination of queries, query conversion modules for standardization and expansion of search words and rule-based reasoning. The techniques described in this paper can be applied to sematic knowledge search systems using tags, since transitivity reasoning, which uses tags, knowledge products, and relations among people, is possible. In addition, as related users can be searched using related tags, the techniques can also be employed to establish collaboration models or semantic communities.