• Journal of the Korea Academia-Industrial cooperation Society
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• v.10 no.9
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• pp.2415-2423
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• 2009

We consider organizational knowledge combination process. Previous literature investigated the issue from either managerial or social aspects, emphasizing on a part of the whole process and limiting to qualitative analyses. Here we propose an integrative and quantitative approach which considers knowledge combination process from engineering perspective. We employ a queueing network model and techniques to capture the process of interactions of entities in the knowledge combination environment. By doing so, we are able to understand the performance of the knowledge combination process. The performance measures derived can provide valuable implications for managerial decisions such as planning and controlling the knowledge combination process.

• International Journal of Quality Innovation
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• v.9 no.2
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• pp.99-117
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• 2008

High-tech industry has been the principal economic source for Taiwan in recent years. The characteristics of high-tech industries in Taiwan are changeable product markets, short product life cycles and high company attrition rate. In the globalization trend, the high-tech industry has gradually increased corporate competitiveness and reached the goal of sustainable operations through knowledge management, knowledge sharing and new product research and development. Firms have aggressively strengthened and integrated their internal and external resources and enhanced knowledge sharing to increase industry operational performance. Effectively strengthening the knowledge management operation and performance evaluation of knowledge sharing in Taiwan's high-tech industry has become a critical issue. In the selection of knowledge sharing Key Performance Indicators (KPI), this research divided the knowledge sharing indicators into representative strategic indicators such as organizational knowledge learning, organizational knowledge resources, organizational information capacity and organizational knowledge performance through screening using Factor Analysis. The characteristics of the constructs were interdependent. This research calculated and adjusted the correlation among the key performance knowledge sharing indicators using ANP and determined the relative weight of knowledge sharing.

• Journal of Korean Library and Information Science Society
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• v.53 no.1
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• pp.191-210
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• 2022

Niklas Luhmann is a sociologist who has had a strong influence on other disciplines. Therefore, it is necessary to examine what Luhmann's theory has influenced on his subsequent researchers. This study analyzed the knowledge network of studies on Niklas Luhmann's theory by follow-up researchers. Bibliographic coupling and co-citation were used as the analysis method of knowledge network. The main results are as follows. First, the language clusters were divided into Latin American / Spanish-speaking regions, Western Europe / Anglo-American regions, Eastern / Northern Europe and other language regions through bibliographic coupling analysis. Second, from the node analysis of bibliographic coupling, It was divided into 2 main cases: where Luhmann's major works were cited; where Luhmann's minor works were cited. Third, it was found that there are the core work groups that are repeatedly cited among Luhmann's works. Fourth, 12 core works were derived from the node analysis of the co-citation network, and appeared in four groups according to themes.

• Proceedings of the Korean Society for Bioinformatics Conference
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• 2005.09a
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• pp.366-370
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• 2005

Tissue microarry is one of the high throughput technologies in the post-genomic era. Using tissue microarray, the researchers are able to investigate large amount of gene expressions at the level of DNA, RNA, and protein The important aspect of tissue microarry is its ability to assess a lot of biomarkers which have been used in clinical practice. To manipulate the categorical data of tissue microarray, we applied Bayesian network classifier algorithm. We identified that Bayesian network classifier algorithm could analyze tissue microarray data and integrating prior knowledge about gastric cancer could achieve better performance result. The results showed that relevant integration of prior knowledge promote the prediction accuracy of survival status of the immunohistochemical tissue microarray data of 18 tumor suppressor genes. In conclusion, the application of Bayesian network classifier seemed appropriate for the analysis of the tissue microarray data with clinical information.

• Journal of Intelligence and Information Systems
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• v.1 no.1
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• pp.91-109
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• 1995

This paper compared four knowledge acquisition methods (namely, neural network, case-based reasoning, discriminant analysis, and covariance structure modeling) for allergic rhinitis. The data were collected from 444 patients with suspected allergic rhinitis who visited the Otorlaryngology Deduring 1991-1993. Among four knowledge acquisition methods, the discriminant model had the best overall diagnostic capability (78%) and the neural network had slightly lower rate(76%). This may be explained by the fact that neural network is essentially non-linear discriminant model. The discriminant model was also most accurate in predicting allergic rhinitis (88%). On the other hand, the CSM had the lowest overall accuracy rate (44%) perhaps due to smaller input data set. However, it was most accuate in predicting non-allergic rhinitis (82%).

• The Journal of Information Systems
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• v.18 no.3
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• pp.135-154
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• 2009

As the knowledge is recognized as a core factor of organization's competitiveness and creation of value added, the importance of knowledge management is also increased. To achieve the successful knowledge management, it is important to establish strategy that consider essential purpose of knowledge management such as creating and sharing of knowledge resource, improving performance, and continuing organizational innovation within the organization and influence factor inside and outside of organization. Until now, however, the research for knowledge management strategy was mostly limited to the statistical analysis based on the unilinear causality model, and systematic access and analysis that consider interaction and feedback structure between factors. In this paper, we developed the novel decision-making framework for successful strategy establishment by applying the analytic network process(ANP). Specifically. we derive clusters and components to decide the interaction and feedback structure between the elements of knowledge management by literature studies. And we produced relative importance and preference of clusters, components and alternatives dealing with feedback structure through the survey of experts in the field or related one of knowledge management. In result of this study, we expect that it will help the knowledge officer to decide establishing knowledge management strategy.

• Journal of Korean Library and Information Science Society
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• v.42 no.4
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• pp.353-374
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• 2011

Analyzing research paper published from 2005 to 2010, this study aims for analysing the research paradigm on multi-culture and understanding the structural characteristics of the multicultural knowledge via scientometric. Co-word network constructed by keywords in documents and their co-occurrence relationships is a kind of mapping knowledge structure. A total of 4,521 and 1,373 papers published between 2005 and 2010 were retrieved from the KRF Registered Journals and Proposed Journals. This paper employs k-core analysis method in the field of mapping knowledge structure to analyze keyword co-occurrence network of multicultural research in Korea. And Netminer 3 is employed to visualize the networks in this paper.

• The Korea Journal of Herbology
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• v.34 no.6
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• pp.33-44
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• 2019

Objectives : This study aims to record and conserve oral traditional knowledge of medicinal animals from the indigenous people living in the local communities of Songnisan National Park, Korea. Methods : Data was collected by participatory observations and in-depth interviews with semi-structured questionnaires. Quantitative comparative analyses were accomplished through data received from the following three methods: informant consensus factor (ICF), fidelity level (FL), and network analysis. Results : The investigation reveals that the indigenous people have used 49 species of medicinal animals distributed within 45 genera, belonging to 39 families with 336 different usages. According to the distribution of recorded families, the most representative families were Scolpendridae and Phasianidae, which were utilized 36 times each (10.71 % each). The category with the highest degree of consensus from informants was disorders related to the nervous system (0.97). 16 species were classified with a fidelity level of 100 %. The network analysis revealed that a lack of vigor was related to 23 species, including Agkistrodon blomhoffii, Gallus domesticus, and Canis familiaris, among the total 49 species investigated. Conclusions : This documentation can help preserve the traditional knowledge and local health traditions of Korea that are disappearing due to rapid industrialization, urbanization, and death of the elderly with traditional knowledge. Additionally, the animals investigated in this study can be developed into medicinal food and drug for treating specific health conditions through further research.

• Knowledge Management Research
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• v.18 no.4
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• pp.287-306
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• 2017

This research focus on the effect of developers' participation structure in knowledge creation and knowledge sharing activities in open source software development projects. Based on preferential selection theory, hypotheses of relationship between a developers' concentration of knowledge creation/sharing activities and collaboration performance was derived. To verify the hypotheses, we use the Gini coefficient in the commit contribution of the developers (knowledge creation) and the centralization index in the repository issue network (knowledge sharing network). Using social network analysis, this paper calculates centralization index from developers in the issue boards in each repository based on data from 837 repositories in GitHub, a leading open source software development platform. As a result, instead of all developers creating and sharing knowledge equally, only a few of developers creating and sharing knowledge intensively further improve the performance of the open collaboration. In other words, a few developers predominantly providing commit and actively responding to issues raised from other developers enhance the project performance. The results of this study are expected to be used by developers who manage open source software project as a governance strategy, which could improve the performance of open collaboration.

• 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.