• Journal of Korea Society of Industrial Information Systems
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• v.19 no.6
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• pp.97-106
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• 2014

A company regards knowledge shared and used within a corporate organization as intellectual capital linked to corporate competences. A great deal of research has been conducted in the past to identify knowledge sharing among knowledge workers. Some papers focus on information technology for automated, efficient, and explicit knowledge sharing. Other papers emphasize the role of social networks to identify the flow of tacit knowledge. Though the role of CoP(Community of Practice) is emphasized to facilitate knowledge management among workers, it is not an easy task to identify the potential members of CoP without voluntary participation of the workers. In this study we adopt a social network approach to analyze knowledge propagation and to identify the potential members of CoP. We suggest a framework for classifying knowledge workers and the result of feasibility study.

• Proceedings of the Technology Innovation Conference
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• 1999.12a
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• pp.197-215
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• 1999

With the advent of knowledge-based economy and information society, information and telecommunications(IT) industry is reckoned as the crucial sector for the creation and diffusion of technological knowledge. In this study, we analyze the process of 'industrialization of IT'and 'informatization of industries' based on the technology linkage structure, or technological knowledge network. The former is defined as the process whereby IT industry absorbs technological knowledge from other industries to grow as an independent industrial sector. The latter is defined as the process whereby other industries adopt IT technology to enhance productivity and upgrade industrial structure, We employ the R&D stock as a proxy for technological knowledge of respective industries and measure the flow of technological knowledge between industries in terms of I/O relationship. By applying the network analysis, we examine the changing pattern of technology linkage structure of the Korean industry throughout the years from 1983 to 1997. Some policy implications are presented based on the findings from the analysis.

• Journal of Intelligence and Information Systems
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• v.2 no.2
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• pp.69-83
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• 1996

The objective of this research is to develop a knowledge acquisition and refinement method for a multi-objective and multi-decision FMS scheduling problem. A competitive neural network and an inductive learning algorithm are integrated to extract and refine necessary scheduling knowledge from simulation outputs. The obtained scheduling knowledge can assist the FMS operator in real-time to decide multiple decisions simultaneously, while maximally meeting multiple objective desired by the FMS operator. The acquired scheduling knowledge for an FMS scheduling problem is tested by comparing the desired and the simulated values of the multiple objectives. The result show that the knowledge acquisition and refinement method is effective for the multi-objective and multi-decision FMS scheduling problems.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.17 no.11
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• pp.2903-2923
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• 2023

Knowledge recommendation is a type of recommendation system that recommends knowledge content to users in order to satisfy their needs. Although using graph neural networks to extract data features is an effective method for solving the recommendation problem, there is information loss when modeling real-world problems because an edge in a graph structure can only be associated with two nodes. Because one super-edge in the hypergraph structure can be connected with several nodes and the effectiveness of knowledge graph for knowledge expression, a dual-channel hypergraph convolutional neural network model (DCHC) based on hypergraph structure and knowledge graph is proposed. The model divides user data and knowledge data into user subhypergraph and knowledge subhypergraph, respectively, and extracts user data features by dual-channel hypergraph convolution and knowledge data features by combining with knowledge graph technology, and finally generates recommendation results based on the obtained user embedding and knowledge embedding. The performance of DCHC model is higher than the comparative model under AUC and F1 evaluation indicators, comparative experiments with the baseline also demonstrate the validity of DCHC model.

• Korean Management Science Review
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• v.12 no.3
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• pp.135-161
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• 1995

This paper is concerned with a conceptual design of a knowledge-based modeler for network analysis. The "knowledge-based modeler" approach is suggested as a method for incorporating the user's qualitative knowledge and subjective decison in the course of the mathematical modeling and the subsequent solution procedure. The submodules of the proposed modeler such as database, model/algorithm base and functional knowledge bases are identified and the flows of information between the submodules are sequentially defined. A prototype system is implemented for experimental purpose by using the application software GURU.ware GURU.

• Journal of the Economic Geographical Society of Korea
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• v.8 no.1
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• pp.31-50
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• 2005

The purpose of this study is to analyse the role of the inter-regional knowledge network in the knowledge based economic development of regions, using regional data collected over the IMF financial crisis between 1996 and 2001. In particular, the major questions about the inter-regional knowledge network in terms of regional innovation are as follows. First, how can be distinguished the inter-regional knowledge networks among the regions? Secondly, what is the relationship between the real object economy and the inter-regional knowledge network? To answer rho questions listed above, the social network analysis is used to examine the association between the intra-regional knowledge linkage structure and the change of the real object economy. For the empirical analyses, regional labour data for 16 Metropolitan Areas(Si) and Provinces(Do) from 1996 to 2001 are used. The findings of the study suggest that there is a significant positive relationship between the concentration of the inter-regional knowledge linkage and a rate of economic growth of the real object economy and that there is a negative correlation between the density and the standard deviation of the inter-regional knowledge linkage and the rate.

• Journal of Korea Society of Digital Industry and Information Management
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• v.10 no.1
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• pp.157-167
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• 2014

Increasing productivity of knowledge workers is a significant issue in the 21st century referred as knowledge-based society. The core key word is behavior of knowledge transfer among members of an organization. The objective of this study is to investigate a model based on Triandis theory and Social Capital theory. This explored the antecedent factors of knowledge Transfer in ITO(Information Technology Outsourcing) Organization. Data were derived from 42 respondents working IT Cooperation in Seoul, Korea. In this paper, we introduce the research model for the knowledge transfer. In order to validate the proposed research model, social network analysis tool, UCINET, a structural equation modeling tool, SmartPLS, was utilized. The empirical result showed that, all antecedent factors (intention of knowledge sharing, anticipated reciprocal relationships, subjective norm, closeness network centrality) of knowledge transfer behavior were significant. In conclusion, findings and implications were discussed and limitations of the study and future research directions were suggested.

• Knowledge Management Research
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• v.14 no.2
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• pp.71-88
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• 2013

The aim of this study was to investigate why people voluntarily contribute knowledge to others, primarily strangers, in the electronic network of practice for job examination expected potential competing. This paper is organized as follows. First, we introduce the electronic network of practice which is the knowledge sharing community for job examination, and discuss the key issues for understanding knowledge sharing in these networks on the basis of individual motivations, relational capital, sense of community, and sense of rivalry to develop a research model for this study. To test the proposed research model, we adopted the survey method for data collection, and examined our hypotheses by applying the multiple regression analysis method to the collected data. Our unit of analysis was the individual. The findings of this study show that the intention of knowledge sharing is influenced by the reputation and the enjoy helping as the factors of individual motivations, by the reciprocity as the factor of relational capital, and by a sense of rivalry as a psychological factor. Lastly, contributions of this study and future research opportunities are also discussed.

• Informatization Policy
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• v.17 no.2
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• pp.25-44
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• 2010

In order to improve organizational performance, organizations should make a knowledge management system to share, distribute, and create related knowledge effectively in the operational process. It is not too much to say that organizational performance depends on the level of network and networking for the use of knowledge among the agents. Theoretically, a web portal is known as a useful instrument not only to link among the actors who have a specific interest and purpose but also to promote social networking which creates new knowledge relevant to user's environment. In the context, this article explored policy implications of building and operating government portals by analysing the efficacy of the "Innovative Portal", which the Korean government had opened to diffuse its innovation activities and to improve organizational innovation capacities in 2005, in innovation process from the knowledge management perspective. In particular, this study tried to identify how did the "Innovation Portal"influence network and networking of innovation knowledge using hyperlink network analysis method.

• Journal of Korean Academy of Nursing
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• v.41 no.5
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• pp.623-632
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• 2011

Purpose: This study was done to explore the knowledge structure of Korean Nursing Science. Methods: The main variables were key words from the research papers that were presented in the Journal of Korean Academy of Nursing and journals of the seven branches of the Korean Academy of Nursing. English titles and abstracts of the papers (n=5,936) published from 1995 through 2009 were included. Noun phrases were extracted from the corpora using an in-house program (BiKE Text Analyzer), and their co-occurrence networks were generated via a cosine similarity measure, and then the networks were analyzed and visualized using Pajek, a Social Network Analysis program. Results: With the hub and authority measures, the most important research topics in Korean Nursing Science were identified. Newly emerging topics by three-year period units were observed as research trends. Conclusion: This study provides a systematic overview on the knowledge structure of Korean Nursing Science. The Social Network Analysis for this study will be useful for identifying the knowledge structure in Nursing Science.