• Journal of the Korean Society for information Management
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• v.33 no.2
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• pp.61-76
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• 2016

This study aims at proposing three prestige indices-closeness prestige, input domain, and proximity prestige- as useful measures for the impact of a particular node in citation networks. It compares these prestige indices with other impact indices as it is still unknown what dimensions of impact these indices actually measure. The prestige indices enable us to distinguish the most prominent actors in a directed network, similar to the centrality indices in undirected networks. Correlation analysis and principal component analysis were conducted on the author citation network to identify the differentiated implications of the three prestige indices from the existing impact indices. We selected simple citation counting, h-index, PageRank, and the three kinds of centrality indices which assume undirected networks as the existing impact measures for comparison with the three prestige indices. The results indicate that these prestige indices demonstrate distinct impact dimension from the other impact indices. The prestige indices reflect indirect impact while the others direct impact.

• The Korean Journal of Health Service Management
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• v.13 no.4
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• pp.1-8
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• 2019

Objectives: This study is prepared to understand the past of the KJHSM (Korean Journal of Health Service Management), to analyze the papers in the KJHSM, to identify the research trends during 2007~2018, and to help the future development of research. Methods: The data for the objectives was collected major KCI index and key words of the articles in KCI web site. Results: The KJHSM has good performaces that KCI IF(2 year) is 0.98, Centrality Index(3 Year) is 1.188, Immediacy index is 0.19, and Self Citation Rate(2 Year) is 25.81. Conclusions: In order to improve the academic quantity and quality in the KSHSM, we will need the vision to corporate and participate through more good research results and performance with desirable ethic value.

• International Journal of Contents
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• v.11 no.1
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• pp.52-61
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• 2015

In the past decade, East Asian Research has received attention from researchers as well as in South Korea society-at-large. The broad category of East Asian Research includes various disciplinary fields, such as "history, economics, and politics; however, few studies have used quantitative analysis to explore its development. In this paper, we used network analysis to identify the disciplines and active research areas, focusing on productivity, collaboration patterns, and citation networks of East Asian Research in South Korea. For this study, 6,646 journal publications related with East Asian Research and indexed by KCI (Korean Citation Index) during the 10-year period of 2004-2013 were considered. Results show that East Asian Research was led during this period by sole-researchers, rather than interdisciplinary studies. Moreover, a co-institution network represents active institutions with a high degree and collaborative centrality. In terms of journal-journal citation networks, journals belonging to both "history" and "Korean literature" disciplines were dominant.

• Journal of Information Management
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• v.41 no.2
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• pp.161-181
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• 2010

The purpose of this study is to investigate citation behavior in internet news to research papers of 10 domestic economic institutes and to suggest institutes' impact quantitatively with h-index and various modified indices. Content analysis of 878 news articles that collected from NAVER news site was performed. First, as citing behavior, cited numbers of research papers, preferred news media, speed, source entry accuracy, centrality, subject section, and length by the institutes were examined. Next, impact indices for institutes were calculated by cited numbers using h-index, g-index, $h_s$-index, and $g_s$-index, and the ranking of 10 research institutes were determined by each impact indices. As a result, institutes belonged to upper ranks showed little variation among the different indices. On the other hand, institutes belonged to middle and lower ranks showed variations in impact indices and experts' survey.

• Journal of the Korean Institute of Rural Architecture
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• v.19 no.3
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• pp.25-32
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• 2017

This study aims to explore the direction of readjustment of rural areas, considering the community. Therefore, it classified the types of 37 Myeon units from 4 communities with higher aging index among rural communities in Jeonnam according to the degree of central functions and population and examined the residents' awareness of community space. As a result, The space used as a social activity for each type is as follows. First of all, the type of decline in the decline of the central index, which reduces transportation conditions, is welfare center (culture center). Second, the central index is high, but there is a low degree of access to the center of the middle and low levels of the population, and the local autonomous center and marketplace, respectively. Third, the low level of access to the central index and the higher center is Nonghyup. Fourth, the decline type with low center index and low accessibility to superior center and low population was the elderly community. Additionally, the types with higher center index on the awareness of community included solidarity and neighbor relationship, and those with lower center index were influenced by cooperation and community awareness for community activation.

• The Journal of the Korea Contents Association
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• v.14 no.9
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• pp.582-588
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• 2014

The purpose of this study is to analyze how a joint research network between countries affects the diffusion of technology information and how much countries with high centrality on the network accept new technology and to seek their meaning. With this aim, the joint research network density between countries by year and the number of participating countries were measured using thesis information regarding the secondary battery field and the electric vehicle field, and a regression analysis of relevant variables was conducted. As a result of the analysis, the greater the joint research network density in the secondary battery field, the higher the number of participating countries in a linear relationship. Also, on the joint research network, countries with high degree centrality were discovered to have led development in the mid to large size secondary battery field. Meanwhile, for the electric vehicle field, although there appeared no increase in the network density value, the number of participating countries was found to have increased. This was analyzed that joint research between countries was not a necessary and sufficient condition although it played a crucial role in promoting technology diffusion. Such a result is meaningful in that it verified promoting factors for essential technology diffusion statistically; however, with this research, there exist limitations that the index of a central role on the network was measured only with degree centrality and that only the relationship between two players was measured for network density in interactions between players. Accordingly, it is necessary to carry out research into a method to measure interactions among multiple researchers in the future.

• Journal of Korean Library and Information Science Society
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• v.51 no.4
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• pp.59-81
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• 2020

The purpose of this study is to compare and analyze the trend of reading research in Korea's LIS Fields in the past 20 years, divided into the 2000s and 2010s, by establishing a keyword network. To achieve this purpose, keywords were extracted from 489 related articles in the four major journals in the LIS field sourced from the Korean Journal Citation Index (KCI) and then analyzed using NetMiner4. The results of the study were as follows: First, in the case of the 2000s, 'Public Library', 'Bibliotherapy', 'Reading Education', and 'School Library' showed high values of Frequency Analysis, Degree Centrality, and Betweenness Centrality. In the 2010s, 'Reading Education', 'School Library', 'Children', 'Adolescents', and 'Public Library' showed high values of the aforementioned measures. Second, in the 2000s, the establishment of library infrastructure for reading and reading education, the improvement of policies and systems, and reading research through the reading movement were actively conducted. In the 2010s, based on the work and research done in the 2000s, customized user reading studies and various detailed reading research were conducted. Third, to meet the demands of the times for the restoration of humanity with creativity and imagination in the Fourth Industrial Revolution, reading research and professional in-depth research should be conducted in various environments beyond public and school libraries and interdisciplinary research and active joint research between the field and academia are needed.

• Journal of Environmental Impact Assessment
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• v.21 no.3
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• pp.391-407
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• 2012

The loss of connectivity and fragmentation of forest landscapes are seriously hindering dispersal of many forest-dwelling species, which may be critical for their viability and conservation by decreasing habitat area and increasing distance among habitats. For understanding their environmental impacts, numerous spatial models exist to measure landscape connectivity. However, general relationships between functional connectivity and landscape structure are lacking, there is a need to develop landscape metrics that more accurately measure landscape connectivity in whole landscape and individual patches. We reviewed functional and structural definition of landscape connectivity, explained their mathematical connotations, and applied representative 13 indices in 3 districts of Seoul having fragmented forest patches with tits, the threshold distance was applied 500m by considering the dispersal of tits. Results of correlation and principal component analysis showed that connectivity indices could be divided by measurement methods whether they contain the area attribute with distance or not. Betweenness centrality(BC), a representative index measuring distance and distribution among patches, appreciated highly stepping stone forest patches, and difference of probability of connectivity(dPC), an index measuring including area information, estimated integrated connectivity of patches. Therefore, for evaluating landscape connectivity, it is need to consider not only general information of a region and species' characteristics but also various measuring methods of landscape connectivity.

• Journal of Intelligence and Information Systems
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• v.22 no.3
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• pp.113-127
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• 2016

Among the techniques for recommendation, collaborative filtering (CF) is commonly recognized to be the most effective for implementing recommender systems. Until now, CF has been popularly studied and adopted in both academic and real-world applications. The basic idea of CF is to create recommendation results by finding correlations between users of a recommendation system. CF system compares users based on how similar they are, and recommend products to users by using other like-minded people's results of evaluation for each product. Thus, it is very important to compute evaluation similarities among users in CF because the recommendation quality depends on it. Typical CF uses user's explicit numeric ratings of items (i.e. quantitative information) when computing the similarities among users in CF. In other words, user's numeric ratings have been a sole source of user preference information in traditional CF. However, user ratings are unable to fully reflect user's actual preferences from time to time. According to several studies, users may more actively accommodate recommendation of reliable others when purchasing goods. Thus, trust relationship can be regarded as the informative source for identifying user's preference with accuracy. Under this background, we propose a new hybrid recommender system that fuses CF and social network analysis (SNA). The proposed system adopts the recommendation algorithm that additionally reflect the result analyzed by SNA. In detail, our proposed system is based on conventional memory-based CF, but it is designed to use both user's numeric ratings and trust relationship information between users when calculating user similarities. For this, our system creates and uses not only user-item rating matrix, but also user-to-user trust network. As the methods for calculating user similarity between users, we proposed two alternatives - one is algorithm calculating the degree of similarity between users by utilizing in-degree and out-degree centrality, which are the indices representing the central location in the social network. We named these approaches as 'Trust CF - All' and 'Trust CF - Conditional'. The other alternative is the algorithm reflecting a neighbor's score higher when a target user trusts the neighbor directly or indirectly. The direct or indirect trust relationship can be identified by searching trust network of users. In this study, we call this approach 'Trust CF - Search'. To validate the applicability of the proposed system, we used experimental data provided by LibRec that crawled from the entire FilmTrust website. It consists of ratings of movies and trust relationship network indicating who to trust between users. The experimental system was implemented using Microsoft Visual Basic for Applications (VBA) and UCINET 6. To examine the effectiveness of the proposed system, we compared the performance of our proposed method with one of conventional CF system. The performances of recommender system were evaluated by using average MAE (mean absolute error). The analysis results confirmed that in case of applying without conditions the in-degree centrality index of trusted network of users(i.e. Trust CF - All), the accuracy (MAE = 0.565134) was lower than conventional CF (MAE = 0.564966). And, in case of applying the in-degree centrality index only to the users with the out-degree centrality above a certain threshold value(i.e. Trust CF - Conditional), the proposed system improved the accuracy a little (MAE = 0.564909) compared to traditional CF. However, the algorithm searching based on the trusted network of users (i.e. Trust CF - Search) was found to show the best performance (MAE = 0.564846). And the result from paired samples t-test presented that Trust CF - Search outperformed conventional CF with 10% statistical significance level. Our study sheds a light on the application of user's trust relationship network information for facilitating electronic commerce by recommending proper items to users.

• Journal of the Speleological Society of Korea
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• no.88
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• pp.38-44
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• 2008

This study aims to identify the efficiency by applying diverse index to the positions of vertex in the network among the network analysis methods in order to identify the relational location features of caves. The first consideration was about the relational location features according to the linking degree and centrality of cave. The second consideration was about the structural equivalence between caves or between caves and the surrounding tourists attractions. A variety of index examined in this study is very efficient for identifying the positions of caves in the network. Furthermore, the relational location features in consideration of surrounding tourists attractions identified the availability of more objective and quantitative expression. In particular, when there are other caves around a cave, it is also very useful to identify the structural equivalence or comparison with other caves.