• Journal of Korean Library and Information Science Society
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• v.51 no.3
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• pp.197-221
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• 2020

This study aims to compare the statistical indicators of libraries of 57 Korean universities and 116 North American universities using Rinfo and ARL statistics respectively. The authors compared twelve similar statistical indicators and found that North American academic libraries were superior in 'volumes in library', 'electronic books', 'total staff', 'total library materials expenditures', 'total items borrowed', 'total items loaned', 'library presentations to groups', and 'participants in group presentations', compared to Korean academic libraries. Although Korean academic libraries showed higher numbers in 'annual gate count', 'reference transactions', 'initial circulations', and 'full-text article requests', there exist some differences in definitions and scopes of these indicators between Rinfo and ARL, needing cautious interpretation of results. The findings of the study imply the needs of expanding support for academic libraries that play pivotal roles in increasing competitiveness of teaching and research of universities. It was also found that systematic management and improvement for statistical indicators of Rinfo are necessary.

• Journal of the Korean Society for information Management
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• v.8 no.1
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• pp.78-99
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• 1991

So far, most of Korea's newspapers indexing have been done manually using tesaurus. In recent years, however, the need for automatic indexing system has grown stronger so as for indexers to save time, efforts and money. And some newspapers have started establishing their databases along with introducing electronic newspapers and CTS. This thesis is on establishing and automatic indexing system for the full-text of the Korea Economic Daily's articles, which have been accumulated in its database, KETEL. In my thesis, I suggest methods to create a keyword file, a stopword list, an auxiliary word list and an infected word list by applying linguistic analysis methods to Hangul, taking advantage of the language's morphological peculiarity. Through these studies, I was able to reach four conclusions as follows. First, we can obtain satisfactory keywords by automatic indexing methods that were made through morphological analysis. Second, an indexer can improve the efficiency of indexing work by controlling extracted vocabulary, as syntax analysis and semantic analysis is not complete in Hangul. Third, The keyword file in this system which is made of about 20,000 most-frequently-used newspaper terms can be used in the future in compiling a thesaurus. Finally, the suggested methods to prepare an auxiliary word list and an infected word list can be applicable to designing other automatic systems.

• Journal of the Korean BIBLIA Society for library and Information Science
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• v.22 no.3
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• pp.353-371
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• 2011

The purpose of this paper is to analyze the interrelation among research areas based on domestic journal papers, achievements of korea researchers. Generally, the content of papers is appeared through abstracts, subjects, full-text and so on. This paper is focused on subject terms of Domestic journal papers. The experimental data are 80 domestic journals, 7,616 papers and 58,143 subject terms and papers published in 2009. As the result, it was different to use subject terms on each research area: Engineering, Agriculture & Oceanography, Interdisciplinary Science, Social Science, Arts & Physical Education, Medicine & Pharmacology, Humanities and Natural Science. Subject terms of Engineering have used the most in the other research areas in aspect of term co-occurrence. The 8 research areas were grouped in 3 clusters: C1(Engineering, Natural Science, Social Science, Interdisciplinary Science, Humanities), C2(Medicine & Pharmacology, Arts & Physical Education), and C3(Agriculture & Oceanography).

• Journal of Menopausal Medicine
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• v.24 no.3
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• pp.150-154
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• 2018

As disasters have been increasing in recent years, disaster health literacy is gaining more important for a population such as middle-age women. This is because they face developmental crises (menopause) and situational crisis (disaster). Due to the growing elderly population, it is imperative to seriously consider the issue of aging women's healthcare, and their educational needs relative to emergencies and disasters. The purpose of study was to clarify the importance of disaster health literacy for middle-age women. This study is a review of the literature using PubMed, ScienceDirect, Web of Science, Google Scholar, SCOPUS, OVID, ProQuest, Springer, and Wiley. Data was collected with keywords related to the research topic ("Women's health" OR "Geriatric health") AND ("Health literacy" OR "Disaster health literacy" OR "Disaster prevention literacy" OR "Risk knowledge" OR "Knowledge management") AND ("Disasters" OR "Risk" OR "Crises") in combination with the Boolean-operators OR and AND. We reviewed full text English-language articles published November 2011 November 2017. Additional references were identified from reference lists in targeted publications, review articles and books. This review demonstrated that disaster health literacy is critical for elderly women, because they may suffer from physical and psychological problems triggered by developmental crises such as menopause and situational crises such as disasters. Disaster literacy could enable them to improve resiliency and reduce disaster risk. Education has vital role in health promotion of middle-age women. Policymakers and health managers should be aware of the challenges of elderly women as a vulnerable group in disasters and develop plans to incorporate disaster health literacy for preparedness and prevention in educating this group.

• Journal of Multimedia Information System
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• v.9 no.2
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• pp.113-120
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• 2022

Mongolian folk songs are inspired by Mongolian labor songs and are classified into long and short songs. Mongolian long songs have ancient origins, are rich in legends, and are a great source of folklore. So it was inscribed by UNESCO in 2008. Mongolian written literature is formed under the direct influence of oral literature. Mongolian long song has 3 classes: ayzam, suman, and besreg by their lyrics and structure. In ayzam long song, the world perfectly embodies the philosophical nature of world phenomena and the nature of human life. Suman long song has a wide range of topics such as the common way of life, respect for ancestors, respect for fathers, respect for mountains and water, livestock and animal husbandry, as well as the history of Mongolia. Besreg long songs are dominated by commanded and trained characters. In this paper, we proposed a method to classify their 3 types of long songs using machine learning, based on their lyrics structures without semantic information. We collected lyrics of over 80 long songs and extracted 11 features from every single song. The features are the name of a song, number of the verse, number of lines, number of words, general value, double value, elapsed time of verse, elapsed time of 5 words, and the longest elapsed time of 1 word, full text, and type label. In experimental results, our proposed features show on average 78% recognition rates in function type machine learning methods, to classify the ayzam, suman, and besreg classes.

• Journal of the Korea Society of Computer and Information
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• v.14 no.8
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• pp.73-80
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• 2009

It is difficult that expertise human supply and demand for industry requires by imbalance of industry necessity human and profession organs of education's Skill Mismatch. Industry can prove productivity though reeducate school graduation person in spot and master correct technology in industry special quality. This paper is research that accommodate Demand Education that industry requires and make out full text caution Curriculum Specializing Vocational High School in e-Business field. Analysis e-Business industrial classification and occupational classification. Analysis knowledge and technological level that require in industry about e-Business education and investigate and analyze the demand. Base industry, Support industry, Apply e-Business Curriculum that is examined by practical use industry to learning, Do to estimate satisfaction about Demand Education Curriculum of industry and confirm Success special quality with research and investigation and application wave. Suggested for e-Business Curriculum's basis model in this paper and school subject Curriculum. Wish to contribute in nation development through productivity elevation through e-Business education of industry request.

• Journal of the Korean Association of Geographic Information Studies
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• v.24 no.4
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• pp.184-193
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• 2021

The system for managing spatial data updates the existing information by extracting only the information that is different from the existing information for the newly obtained spatial information file to update the stored information. In order to extract only objects that have changed from existing information, it is necessary to compare whether there is any difference from existing information for all objects included in the newly obtained spatial information file. This study was conducted to improve this total inspection method in a situation where the amount of spatial information that is frequently updated increases and data update is required at the national level. In this study, before inspecting individual objects in a new acquisition space information file, a method of determining whether individual space objects have been changed only by the information in the file was considered. Spatial data files have structured data characteristics different from general image or text document files, so it is possible to determine whether to change the file unit in a simpler way compared to the existing method of creating and managing file hash. By reducing the number of target files that require full inspection, it is expected to improve the use of resources in the system by saving the overall data quality inspection time and saving data extraction time.

• Journal of the Korea Society of Computer and Information
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• v.15 no.7
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• pp.91-98
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• 2010

Large corpus-based concatenating Text-to-Speech (TTS) systems can generate natural synthetic speech without additional signal processing. Because the improvements in the natualness, personality, speaking style, emotions of synthetic speech need the increase of the size of speech DB, it is necessary to prune the redundant speech segments in a large speech segment DB. In this paper, we propose a new method to construct a segmental speech DB for the Korean TTS system based on a clustering algorithm to downsize the segmental speech DB. For the performance test, the synthetic speech was generated using the Korean TTS system which consists of the language processing module, prosody processing module, segment selection module, speech concatenation module, and segmental speech DB. And MOS test was executed with the a set of synthetic speech generated with 4 different segmental speech DBs. We constructed 4 different segmental speech DB by combining CM1(or CM2) tree clustering method and full DB (or reduced DB). Experimental results show that the proposed method can reduce the size of speech DB by 23% and get high MOS in the perception test. Therefore the proposed method can be applied to make a small sized TTS.

• The Journal of Society for e-Business Studies
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• v.21 no.2
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• pp.135-150
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• 2016

As the privacy issues are all around the world, the intrusion into personal privacy is concerning. For that reason, government established the article from the personal information protection law that has to notice the privacy policy to users on the online site. and the matter of privacy invasion make concern toward behavior of online user. Although there are rules to carrying legal binding force in accordance with, because it is full of text and uncomfortable to read so that its readability is low. In the same context, each other has different state of understanding with the policy for personal information has been playing an important role. In this approach, companies and government do not think this over deeply and do just for what their practical use is. That is the reason why this research start, and the result expecting for real. As the result in the participant who cognize the privacy policy display pattern, they have certain type to do. In this article, the certain behavior doing is remarkable with the privacy policy. According to privacy concern, privacy fundamentalist reveals such a compromise reaction to protect their information when they know what information which the privacy manager of service provider collect. This study arrives at the result depending on the gap of privacy group that the group of checking the policy contents, especially the group which has high privacy concern, they move forward to protect their emotion and put a constructive plan into protective action. Otherwise, the group of unchecking the policy contents and following their own thinking of privacy policy are not deemed statistically significant. Therefore, this is considered to support more various implications than the previous issues and alternatives about privacy policy pattern and user protection behavior of privacy.

• 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.