• Journal of the Korean Society for information Management
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• v.32 no.4
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• pp.205-221
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• 2015

The impact of a journal is commonly used as the impact of an individual paper within that journal. It is problematic to interpret a journal's impact as a single paper's impact of the journal, so there are several researches to measure a single paper's impact with its own citation counts. This study applied 8 impact indicators to Korean Citation Index database and examined discipline bias of each indicator. Analyzed indicators are simple citation counts, PageRank, f-value, CCI, c-index, single publication h-index, single publication hs-index, and cl-index. PageRank has the least discipline bias at highly ranked papers and journal bias in a discipline. On the contrary, simple citation counts showed strongly biased results toward a certain discipline or a journal. KCI database provides only simple citation counts. It needs to show PageRank (global indicator) to discover influential papers in diverse areas. Furthermore it needs to consider to provide the best of local indicators. Local indicators can be calculated only with papers in users' search results because they uses citation counts of citing papers and the number of references. They are more efficient than global indicators which explore the whole database. KCI should also consider to provide Cl-index (local indicator).

• The KIPS Transactions:PartA
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• v.12A no.6 s.96
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• pp.539-546
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• 2005

Recently, as the number of Internet users are growing explosively, e-learning has been applied spread, as well as remote evaluation of intellectual capacity However, only the multiple choice and/or the objective tests have been applied to the e-learning, because of difficulty of natural language processing. For the intelligent marking of short-essay typed answer papers with rapidness and fairness, this work utilize heterogenous linguistic knowledges. Firstly, we construct the semantic kernel from un tagged corpus. Then the answer papers of students and instructors are transformed into the vector form. Finally, we evaluate the similarity between the papers by using the semantic kernel and decide whether the answer paper is correct or not, based on the similarity values. For the construction of the semantic kernel, we used latent semantic analysis based on the vector space model. Further we try to reduce the problem of information shortage, by integrating Korean Word Net. For the construction of the semantic kernel we collected 38,727 newspaper articles and extracted 75,175 indexed terms. In the experiment, about 0.894 correlation coefficient value, between the marking results from this system and the human instructors, was acquired.

• The Journal of the Korea Contents Association
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• v.21 no.2
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• pp.85-99
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• 2021

Graphene, called the "dream material" is drawing attention as a groundbreaking new material that will lead the era of the 4th Industrial Revolution. Graphene has high strength, excellent electrical and thermal conductivity, excellent optical permeability, and excellent gas barrier properties. In this paper, as the South Korean government recently announced Green New Deal and Digital New Deal policy, we analyze graphene technology, which is also attracting attention for its application to Corona 19 biosensor, to understand its national R&D trend and knowledge structure, and to explore the possibility of its application. Firstly, 4,054 cases of national R&D project information for the last 10 years are collected from the National Science & Technology Information Service(NTIS) to analyze the trend of graphene-related R&D. Besides, projects classified as green technology are analyzed concerning the government's Green New Deal policy. Secondly, text mining analysis is conducted by collecting 500 recent graphene-related articles from e-newspapers. According to the analysis, the field with the largest number of projects was found to be high-efficiency secondary battery technology, and the proportion of total research funds was also the highest. It is expected that South Korea will lead the development of graphene technology in the future to become a world leader in diverse industries including electric vehicles, cellular phone batteries, next-generation semiconductors, 5G, and biosensors.

• Journal of the Korean Society for information Management
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• v.38 no.4
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• pp.113-128
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• 2021

In this study, we aimed to understand the public opinion on COVID-19 vaccine. To achieve the goal, we analyzed COVID-19 vaccine-related Twitter posts. 45,413 tweets posted from March 16, 2020 to March 15, 2021 including COVID-19 vaccine names as keywords were collected. The 12 vaccine names used for data collection included 'Pfizer', 'AstraZeneca', 'Modena', 'Jansen', 'NovaVax', 'Sinopharm', 'SinoVac', 'Sputnik V', 'Bharat', 'KhanSino', 'Chumakov', and 'VECTOR' in the order of the number of collected posts. The collected posts were analyzed manually and automatedly through keyword analysis, sentiment analysis, and topic modeling to understand the opinions for the investigated vaccines. According to the results, there were generally more negative posts about vaccines than positive posts. Anxiety about the aftereffects of vaccination and distrust in the efficacy of vaccines were identified as major negative factors for vaccines. On the contrary, the anticipation for the suppression of the spread of coronavirus following vaccination was identified as a positive social factor for vaccines. Different from previous studies that investigated opinions about COVID-19 vaccines through mass media data such as news articles, this study explores opinions of social media users using keyword analysis, sentiment analysis, and topic modeling. In addition, the results of this study can be used by governmental institutions for making policies to promote vaccination reflecting the social atmosphere.

• Journal of Korean Home Economics Education Association
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• v.26 no.3
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• pp.17-34
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• 2014

This study aimed to examine the research trends and to suggest future research directions in teaching-learning methods for Home Economics education, by analyzing articles published in three major academic journals in the field. From each of the research studies, the teaching-learning method, the related content area, and the learning effect measures were quantitatively codified. The data were analyzed using frequency analysis and cross-tabulations. According to the results, the number of teaching-learning method studies steadily increased since 1998 and peaked in 2010 and 2011. The most frequently studied content areas were combinations of more than two content areas, and the most frequently studied teaching-learning method was the Content-Based methods, followed by Practical Thinking/Problem Solving, and IT-Based methods. The most frequently used measures of learning effect were Knowledge/Understanding, Attitudes toward Home Economics subject, General Attitudes/Competencies, and the Attitudes toward the Instructional Method, in the order of frequencies. The results of this study are expected to contribute to the teaching-learning method research and also provide implications to the documentation of Home Economics curriculum for secondary education.

• (The)Study of the Eastern Classic
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• no.35
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• pp.359-385
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• 2009

The study aims to investige how Soupjin, military training has been changed in early Joseon Dynasty. The conclusions are following these. First, Jin means military marching or attacking the enemy and Jinbeop means how to make Jin or traning but now Jinbeop indicates textbook of Jinbeop rather than practing it. Second, publishing Owijinbeop is completed as a result of continuous series of Jinbeop textbook and Owi systems are built up by military construction reorganization. Third, the total number of articles is 268 from Taejo to Seonjo in early Joseon Dynasty. They are divided into different parts according to kings. Forth, Taejo, Taejong, Munjong, Sejo, Yejong and Jungjong are the kings who take the lead of Jinbeop training directly. Among them Munjong and Sejo are highly considered that they edited and revised Sinjinbeop and tried to unify military organization. Besides Jungjong discussed Jinbeop textbooks which are published by prior kings and even make them be practiced. But after Imjinwaeran, Seonjo accepted the book Gihyosinseo by Cheokgyegwang in China and transformed our Jinbeop for protecting the country. Firth, We found that Hyangmyung and Jintoigyjak had been focused from Sejo to Jungjong. Because in this period Joseon had to find the way to protect the country from north Yeojin, But after Imjinwaeran Seonjo introduced Cheokgyegwang's Jeolgangjinbeop in China because of Japanese attacks.

• Journal of the Korean Society for Library and Information Science
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• v.45 no.1
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• pp.125-147
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• 2011

Recently, with a high demand for the construction and remodeling of libraries, and the rapid increase in the number of libraries during the last two years, the concern and need for library goods is also increasing sharply. The purpose of this study is to develop a new classification scheme of library goods by clarifying the terminology which could provide an accurate information on library goods and allow for their smooth circulation. In this study, library goods are defined as all kinds of products required for effectively collecting, organizing and providing services with library materials, and classified into library equipments and library supplies. The term, library equipment is principally used for those things that do not wear out within a certain time period, such as furniture and machinery. Library supplies refer to those things that are expendable. As the terminology is clarified, the classification scheme can be further refined. Library equipment, for example, can be classified as furniture, library system solutions, and computers and multi-media tools. Library supplies can be classified into library organization and repair supplies, sign systems, and miscellaneous articles. Finally, six major categories which include 117 different items are presented.

• Journal of the Korea Convergence Society
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• v.12 no.6
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• pp.233-239
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• 2021

Recently, the COVID-19 virus has caused people to stay indoors longer without going out. As a result of this, people's activity decreased sharply, and their weight gained. So people became more interested in health. Home training can be an alternative method to solve this problem. Accordingly, To find out the trends of home training, we collected articles from December 1, 2019, to November 30, 2020, using the news provided by BIG KINDS, a news analysis system. We analyzed frequency analysis, relational analysis according to weighting, and related word analysis with the program using the algorithm developed by BIG KINDS. In conclusion, first, it was found that home training is led by technology and the emergence of artificial intelligence. Second, it can be assumed that people mainly do home training using content and video services related to mobile carriers. Third, people had a high preference for Pilates in the sports category. It can be seen that the number of patent applications increased as the demand for exercise products related to Pilates increased. In the next study, we expect that this study will be used as primary data for various big data studies by supplementing the research methodology and conducting various analyses.

• Journal of Korean Library and Information Science Society
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• v.52 no.1
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• pp.79-108
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• 2021

Information retrieval in the health field has several challenges. Health information terminology is difficult for consumers (laypeople) to understand. Formulating a query with professional terms is not easy for consumers because health-related terms are more familiar to health professionals. If health terms related to a query are automatically added, it would help consumers to find relevant information. The proposed query expansion (QE) models show how to expand a query using MeSH terms. The documents were represented by MeSH terms (i.e. Bag-of-MeSH), found in the full-text articles. And then the MeSH terms were used to generate LDA (Latent Dirichlet Analysis) topic models. A query and the top k retrieved documents were used to find MeSH terms as topic words related to the query. LDA topic words were filtered by threshold values of topic probability (TP) and word probability (WP). Threshold values were effective in an LDA model with a specific number of topics to increase IR performance in terms of infAP (inferred Average Precision) and infNDCG (inferred Normalized Discounted Cumulative Gain), which are common IR metrics for large data collections with incomplete judgments. The top k words were chosen by the word score based on (TP *WP) and retrieved document ranking in an LDA model with specific thresholds. The QE model with specific thresholds for TP and WP showed improved mean infAP and infNDCG scores in an LDA model, comparing with the baseline result.

• Journal of Distribution Science
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• v.9 no.4
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• pp.15-27
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• 2011

Although a huge number of academic researchers have paid considerable attention to exploring both the degree to which store image influences retailer brand customers and how to develop store personality, they have overlooked the contemporary retail context in which retailers have developed many different types of retailer brands, that is, price-oriented or quality-oriented retailer brands. Rather than focusing on the latter, much literature has looked at the former. Accordingly, even though there are many articles related to store image, a few authors have shown their interest in identifying the extent to which store personality affects customers purchasing retailer brands at lower prices. As a result, their efforts have been to illustrate the relationship between store image and consumer behaviours buying retailer brands. In that multiple retailers over the world such as E-Mart, Lotte-Mart, Tesco Korea and Tesco UK have actively introduced not only the quality-focused retailer brands that quality is better than, or equal to national brands, and prices are slightly higher than, or equal to them, but also price-focused retailer brands, academicians should make an effort to investigate how store image affects customers purchasing a quality-oriented retailer brand, comparing with previous research results. That is why the authors illustrate the extent to which store personality components influence retailer brand customers, including particularly quality-oriented retailer brand customers through an empirical research. By adopting a questionnaire method as a research technique to illuminate the relationship between store image components and retailer brand customers, research validity increases and further, data gathered through a field survey are analysed through a few statistic analysis methods, in order to minimise statistical deviations. Compared with the prior research concentrated on price-focused retailer brands, the authors have significantly shed light on customer behaviours purchasing retailer brand products with higher quality. When it comes to store personality components, the research suggests the following five items: merchandise attributes, services, physical facilities, promotions, and institutional image, considering the subcomponents mentioned by the previous research. Proposing the conceptual research model which those elements are differently hypothesised, according to retailer brand types: PR (Price-oriented Retailer brand) and QR (Quality-oriented Retailer brand), the research is proceeded. Through empirical research, the authors found that amongst the five items, only promotion influenced retailer brand customers in the Korean retailing marketplace, unlike other countries explored by many researchers, such as UK. Although much literature emphasises that those elements are closely related to retailer brand buying proneness, it is completely not fit to the Korean market. Also, research findings provide new insights into the degree of store image effects on retailer brand customers for academiciansand practitioners. Whether the retailer brand development program that a retailer has carried simultaneously both price-focused and quality-focused retailer brand types is practically profitable should be explored in the future.