• Asia-pacific Journal of Multimedia Services Convergent with Art, Humanities, and Sociology
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• v.6 no.1
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• pp.39-48
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• 2016

The tacit knowledge transfer cultivate the value and mount of tacit knowledge. The tacit knowledge transfer plays the most important role for improving the competitiveness of the organization. Despite the tacit knowledge transfer is very important, the research related with tacit knowledge transfer has not been actively carried out. The barriers to tacit knowledge transfer interfere with the tacit knowledge transfer. The barriers to tacit knowledge transfer are lack of understanding knowledge experts, heavy over-work, insufficient compensation, trust shortage and knowledge stickiness. In order to overcome the barrier of the tacit knowledge transfer, it is necessary to promote knowledge broker. The knowledge broker is the foundation for the tacit knowledge transfer and the critical success factor for efficient tacit knowledge transfer. However, most research related on the knowledge broker had focused on the degree, centrality and density of the knowledge network. The framework is needed to performance indicator for diagnosing the tacit knowledge transfer. Therefore, we suggest the knowledge broker framework based on the social network analysis.

• The Journal of the Korea Contents Association
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• v.16 no.5
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• pp.205-216
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• 2016

This study aimed to discover the most influential player in the network of Soccer game and how individual players contribute within the team with quantitative capabilities they possess. It also examined whether or not the network of relationship between players and the coach's tactics were in harmony. The results showed high level of correlation between the network between offenders and defenders according to tactics of the coach during the first half. It can be said that each players fulfilled their role and formed a network within them to lead the game and form a virtuous network structure. On the other hand, the overall network of the team was focused on a specific player during the second half. But the coach's appropriate use of substitutes and change in tactics stabilized the network balance between the players.

• 정보화사회
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• s.121
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• pp.31-35
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• 1998

21세기를 눈앞에 둔 지금, 세계는 국가의 경제적 이익을 최우선으로 하는 경제전쟁의 시대에 있으며, 특히 선진 각국은 정보통신의 급격한 발전에 의해 도래하는 정보화 사회에서 주도적 입지를 굳히기 위해 바삐 움직이고 있다. 이러한 국제적.사회적 환경의 급격한 변화에 따라 국민들은 정부에 대한 행정의 수요 및 기대를 다양하게 표출하고 있으며, 정부도 국민에 대한 반응성이 높아지는 반면, 관료제의 영향력은 점차 감소되고 있다. 이러한 국민의 요구에 적극적으로 부응할 수 있는 수요중심의 행정을 펼치기 위해서는 정보통신기술을 전체 행정과정에 적극 도입.활용하는 행정정보화를 통해 정부의 생산성을 획기적으로 제고시키고, 공통의 정보통신기반 위에 하나로 연결된 각종 정부정보 및 서비스를 언제, 어디서나, 어떤 방법으로든, 신속히 제공할 수 있는 행정관리체계를 구축해야 한다. 이와 동시에, 정부의 업무와 조직의 혁신 등 제도적 개선이 병행될 때 비로소 경쟁력 있는 "작고 효율적인 정부"가 구현될 것이다. 본고에서는 현재 우리 나라의 행정정보 공동활용현황과 행정부문 정보화의 주무기관인 "정부전산정보관리소"에서 추진하고 있는 "정부고속망 사업"에 관해 논하고자 한다.

• The Journal of Korean Association of Computer Education
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• v.17 no.4
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• pp.69-78
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• 2014

This study aims to investigate better predictors, among learner participation and interaction, for collective self-efficacy and achievement in a web-based collaborative learning environment. Interaction requires communication among two or more learners, while participation does not. In this study, interaction was measured by in-degree centrality and out-degree centrality based on the social network analysis perspective. Multiple regression analysis results from 53 college students who performed team project via online showed that in-degree centrality predicted collective self-efficacy and out-degree centrality predicted achievement, while participation was not a significant predictor.

• Journal of Intelligence and Information Systems
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• v.27 no.1
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• pp.23-46
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• 2021

Collaborative filtering, which is often used in personalization recommendations, is recognized as a very useful technique to find similar customers and recommend products to them based on their purchase history. However, the traditional collaborative filtering technique has raised the question of having difficulty calculating the similarity for new customers or products due to the method of calculating similaritiesbased on direct connections and common features among customers. For this reason, a hybrid technique was designed to use content-based filtering techniques together. On the one hand, efforts have been made to solve these problems by applying the structural characteristics of social networks. This applies a method of indirectly calculating similarities through their similar customers placed between them. This means creating a customer's network based on purchasing data and calculating the similarity between the two based on the features of the network that indirectly connects the two customers within this network. Such similarity can be used as a measure to predict whether the target customer accepts recommendations. The centrality metrics of networks can be utilized for the calculation of these similarities. Different centrality metrics have important implications in that they may have different effects on recommended performance. In this study, furthermore, the effect of these centrality metrics on the performance of recommendation may vary depending on recommender algorithms. In addition, recommendation techniques using network analysis can be expected to contribute to increasing recommendation performance even if they apply not only to new customers or products but also to entire customers or products. By considering a customer's purchase of an item as a link generated between the customer and the item on the network, the prediction of user acceptance of recommendation is solved as a prediction of whether a new link will be created between them. As the classification models fit the purpose of solving the binary problem of whether the link is engaged or not, decision tree, k-nearest neighbors (KNN), logistic regression, artificial neural network, and support vector machine (SVM) are selected in the research. The data for performance evaluation used order data collected from an online shopping mall over four years and two months. Among them, the previous three years and eight months constitute social networks composed of and the experiment was conducted by organizing the data collected into the social network. The next four months' records were used to train and evaluate recommender models. Experiments with the centrality metrics applied to each model show that the recommendation acceptance rates of the centrality metrics are different for each algorithm at a meaningful level. In this work, we analyzed only four commonly used centrality metrics: degree centrality, betweenness centrality, closeness centrality, and eigenvector centrality. Eigenvector centrality records the lowest performance in all models except support vector machines. Closeness centrality and betweenness centrality show similar performance across all models. Degree centrality ranking moderate across overall models while betweenness centrality always ranking higher than degree centrality. Finally, closeness centrality is characterized by distinct differences in performance according to the model. It ranks first in logistic regression, artificial neural network, and decision tree withnumerically high performance. However, it only records very low rankings in support vector machine and K-neighborhood with low-performance levels. As the experiment results reveal, in a classification model, network centrality metrics over a subnetwork that connects the two nodes can effectively predict the connectivity between two nodes in a social network. Furthermore, each metric has a different performance depending on the classification model type. This result implies that choosing appropriate metrics for each algorithm can lead to achieving higher recommendation performance. In general, betweenness centrality can guarantee a high level of performance in any model. It would be possible to consider the introduction of proximity centrality to obtain higher performance for certain models.

• Journal of Gifted/Talented Education
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• v.25 no.1
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• pp.21-36
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• 2015

The purpose of this study is to examine social influence of the counselors on the network for a career counseling on gifted students of science and general students. This study collected data from 151 gifted students of science and 212 general students. The collected data was analyzed by the social network analysis. The results are as follows: First, we found that mother had the highest centrality indicators and teacher had the lowest centrality indicators on the career counseling network in both groups. And the max-flow indicators from mothers to teachers were the lowest on the career counseling network, on other hand; general students had lower centrality indicators than gifted students of science. Second, father was the most obvious counselor to cover for mother, on the hand, teacher was the worst counselor to cover for mother on the career counseling network. The gifted students group of science had less difficulty to cover for mother than the general students group. While teacher had the highest limits to information exchange on the career counseling network in both groups, mother had the lowest limits. As the result, we can conclude that mother played a key role on the career counseling network in gifted students of science and general students, while teachers was excluded from the career counseling network of students. Therefore, it is necessary to connect systematically parents with teachers for leading effectively students to their career; also government needs to build a career counseling system for this.

• The Journal of Bigdata
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• v.4 no.1
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• pp.99-118
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• 2019

This study used network analysis and clustering techniques to analyze studies on social media participation. As a result of the main path analysis, 37 major studies were extracted and divided into two networks: community-related networks and new media-related. Network analysis and clustering result in four clusters. This study has the academic significance of using academic data to grasp research trends at a macro level and using network analysis and machine learning as a methodology.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2009.10a
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• pp.686-689
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• 2009

NGN은 기존의 회선교환망이 가지는 높은 신뢰성과 IP 망의 유연성을 양립시킨다는 기본 이념을 바탕으로 IP 기술을 활용한 통신망이다. 상호접속은 서로 다른 통신망의 가입자간 통신을 가능하도록 통신설비를 물리적으로 연결하여 사업자간 경쟁환경을 조성하고 사회 후생을 극대화를 위한 중요한 정책수단이다. NGN에서는 사용대역차이와 QoS의 유무 및 수준 등 성격이나 품질이 다양한 서비스가 종합적으로 제공되는 네트워크로 기존 상호접속체계에 비해 복잡할 수 밖에 없다. 일본에서는 NGN 기반 서비스가 상용화 됨에 따라 구체적으로 상호접속체계를 정립하였다. 본 논문에서 NGN 상호접속체계를 정립하기 위한 NGN 서비스 및 설비 기능 세분화, 설비 비용 산정방법, 서비스 비용 산정기준에 관하여 살펴보고 상호접속체계 검토시 고려사항을 제시하고자 한다.

• Journal of the Korea Convergence Society
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• v.11 no.7
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• pp.251-257
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• 2020

This study comparatively analyzed the differences in the talented human resources perceived by enterprises and job seekers in terms of recruitment trends of companies related to the 4th Industrial Revolution, focusing on 16 factors. The analysis data was collected from enterprises and job seekers related to the 4th Industrial Revolution, and the analysis method was applied to a convergence research methodology that mixes social network analysis and variance analysis using big data type. As a result, several things were verified. First, large enterprises emphasized communication, and small enterprises emphasized competency and confidence. Second, in the manufacturing industry, enterprises emphasized confidence and competence, and job seekers emphasized spec and passion. Third, in the service industry, enterprises emphasized personality and competence, and job seekers emphasized spec and global. Fourth, there was a big difference in talented human resources between enterprises and job seekers according to manufacturing and service industries. Based on these results, we discussed the opening of employment information for enterprises to reduce the recognition mismatch in the talented human resources.

• Journal of Information Management
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• v.40 no.2
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• pp.1-24
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• 2009

This study explored the scientific web spaces of Korea and Japan by applying webmetric and social network analysis techniques with the aim of ascertaining international scholarly communication characteristics between the two countries. In general, more links were generated from the Korean scientific web sites to the Japanese sites than those from the opposite direction, thus implying a higher usage of Japanese scientific information on the web in Korean sites. In addition, university sites in the two countries were highly linked on the web revealing the most active institutions in scholarly communication were the universities. Based on the link analysis, the study also indicated which country was more dependent on the other in scholarly communication in specific scientific fields.