• International Commerce and Information Review
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• v.19 no.3
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• pp.107-127
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• 2017

This paper aims to analyze comparing the international competitiveness of Korea and China of ICT 10 goods in ASEAN Big 6 countries.(Malaysia, Indonesia, Vietnam, Singapore, Thailand, Philippines). In this study, we investigate major trends in Korea's ICT goods through various data analysis and evaluate. From 2009 to 2016, As analyzed by ESI, CTB, and EMS, This paper showed Korea has increased its export, EMS and Export Competitiveness to ASEAN. However, due to rapid imports, the trade balance deteriorated and ESI decreased. China showed signs of improvement in international competitiveness, although exports, ESI and EMS were declining. Compared to South Korea, China has seen less export bias to ASEAN. ASEAN is becoming an increasingly important trade partner in Korea's ICT exporting. This paper points out several policy implications drawn from its analyses and findings.

• Korean Journal of Plant Resources
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• v.16 no.2
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• pp.99-108
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• 2003

This study was carried out to make a standard criteria for protection and maintenance of the big and old trees in Ansung city, Kyonggi Prvince. There have been found 6 vegetative species cultivated in this area, which are Zelkova serrata, Gingko biloba, Kalopanax pictus, Pyrus ussuriensis var. macrostipes, Pyrus ussuriensis var. acidula, Pinus densiflora, etc. The Zelkova serrata tree is the major species among them and about 73.5％ in the population of the big and old trees in this area. The DBH (diameter at brest height) of them is 1.5-1.9m in 29.4% of whole population and the tree height is 10-l4m in 47.1%. The estimate age of 7 trees is more than 500 years old and they were 20.6％ of the whole population. Interesting point is that about 64.7％ of these trees in this area have own succeed story in terms of folk religion, object of worship, taboo, legend or secret. This study has also revealed that many fowls, small animals and epiphyte inhabited with the big and old trees have been found. However, 97.1％ of them are in danger from the plant disease and noxious insects or cutting damage of branches, but no management has been taken. More over, 85.3％ of the whole investigated big and old trees have been in the poor condition for percolation or aeration because the area around them has been payed with asphalt or concrete.

• Management & Information Systems Review
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• v.36 no.5
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• pp.85-98
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• 2017

The purpose of this study is to exploratory examine the structural relationships among meaningfulness of work, personality(Big 5 character-types) and job stress. To conduct such examination, the author (i) designated meaningfulness of work, personality(Big 5 character-types) and job stress as variables and (ii) designed a research model by conducting preceding studies on the variables. To examine the research model the author collected the survey data from the residents in Kyoungsangbuk-do, 332 copies of questionnaire. Collected data were analyzed using SPSS and AMOS programs. The analysis results are as follows. Especially, (1) the meaningfulness of work had a positive effect on agreeableness, conscientiousness, and extraversion. (2) the meaningfulness of work had a negative effect on neuroticism. (3) the meaningfulness of work had no effect on openness to experience. (4) the neuroticism factor had a positive effect on psychological job stress and physical job stress. (5) the openness to experience had a negative effect on psychological job stress and physical job stress. (6) the meaningfulness of work had no effect on psychological job stress and physical job stress. The implications and limitation which this study are as follows. First, this study has discovered that there was statistically significant relationship between the meaningfulness of work and Big 5 character-types. Second, Big 5 character-types(neuroticism, openness to experience) had statistically effect on psychological job stress and physical job stress. This study have limitation in that was conducted based on cross-sectional design of research. Because, the mechanism of job stress is a dynamic process.

• The Journal of the Korea Contents Association
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• v.20 no.6
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• pp.1-8
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• 2020

The use of text data in big data analytics has been increased. So, much research on methods for text data analysis has been performed. In this paper, we study Bayesian learning based on conjugate prior for analyzing keyword data extracted from text big data. Bayesian statistics provides learning process for updating parameters when new data is added to existing data. This is an efficient process in big data environment, because a large amount of data is created and added over time in big data platform. In order to show the performance and applicability of proposed method, we carry out a case study by analyzing the keyword data from real patent document data.

• Culinary science and hospitality research
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• v.24 no.3
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• pp.167-176
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• 2018

In this study, Big Data was used to collect the information related to 'Cooking Academy' keywords. After collecting all the data, we calculated the frequency through the text mining and selected the main words for future data analysis. Data collection was conducted from Google Web and News during the period from January 1, 2013 to December 31, 2017. The selected 64 words were analyzed by using UCINET 6.0 program, and the analysis results were visualized with NetDraw in order to present the relationship of main words. As a result, it was found that the most important goal for the students from cooking school is to work as a cook, likewise to have practical classes. In addition, we obtained the result that SNS marketing system that the social sites, such as Facebook, Twitter, and Instagram are actively utilized as a marketing strategy of the institute. Therefore, the results can be helpful in searching for the method of utilizing big data and can bring brand-new ideas for the follow-up studies. In practical terms, it will be remarkable material about the future marketing directions and various programs that are improved by the detailed curriculums through semantic network of cooking school by using big data.

• Culinary science and hospitality research
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• v.23 no.8
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• pp.195-205
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• 2017

The purpose of this study was to compare the Starbucks in South Korea with Starbucks in U.S.A through the semantic network analysis of big data by collecting online data with SCTM(Smart Crawling & Text Mining) program which was developed by big data research institute at Kyungsung University, a data collecting and processing program. The data collection period was from January 1st 2014 to December 7th 2017, and packaged Netdraw along with UCINET 6.0 were utilized for data analysis and visualization. After performing CONCOR(convergence of iterated correlation) analysis and centrality analysis, this study illustrated the current characteristics of Starbucks for Korea and U.S.A reflected by the social network and the differences between Korea and U.S.A. Since the Starbucks was greatly developed, especially in Korea. this study also was supposed to provide significant and social-network oriented suggestions for Starbucks USA, Starbucks Korea and also the whole coffee industry. Also this study revealed that big data analytics can generate new insights into variables that have been extensively studied in existing hospitality literature. In addition, implications for theory and practice as well as directions for future research are discussed.

• Journal of Environmental Impact Assessment
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• v.6 no.1
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• pp.67-76
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• 1997

The purpose of this research is to draw out the factors affecting the residents' evaluation on valuable animal and vegetation and the naturality of vegetation seen near regional environment. With this purpose, Questionnaire research and vegetation survey focusing on area of types of vegetation and species of big trees were made in 30 points of midstream of Tama River, Tokyo, Japan. The questionnaire research was based on basin environment units in order to be reflective of regional natural environment. The vegetation was classified into 5 types according to its flora and observed the covering area of each points and types through the aerial photograph. In addition, the species of big trees in habitat were listed by the survey. Results as below came out by analyzing the outcome of the questionnaire research and vegetation survey by multiple regression. First, residents are most likely not to distinguish precisely between the quantitative and qualitative aspects of vegetation. Both of the researches are apt to be influenced by quantitative factors of vegetation. Second, residents are assumed to consider forest of big trees, inhabitant of groups of big trees, highly natural.

• Asia-Pacific Journal of Business
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• v.12 no.2
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• pp.161-174
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• 2021

Purpose - The purpose of this study was to examine the recent popular consumption trend, the hocance phenomenon, using social media big data. The study intended to present practical directions and marketing measures for the recovery and growth of the hotel industry after COVID-19 pandemic. Design/methodology/approach - Big data analysis has been used in various fields, and in this study, it was used to understand the hocance phenomenon. For three years from January 1, 2018 to December 31, 2020, we collected text data including the keyword 'hocance' from the blog and cafe of NAVER and Daum. TEXTOM and UCINET 6 were used to collect and analyze the data. Findings - According to the results of analysis, the words such as 'hocance', 'hotel', 'Seoul', 'travel', 'swimming pool', 'Incheon', 'breakfast', 'child' and 'friend' were identified with high frequency. The results of CONCOR analysis showed similar results in all three years. It has been confirmed that 'swimming pool', 'breakfast', 'child' and 'friend' are important when deciding on the hocance package. Research implications or Originality - The study was differentiated in that it used social media big data instead of traditional research methods. Furthermore, it reflected social phenomena as a consumption trend so there was practical value in establishing marketing strategies for the tourism and hotel industry.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.16 no.8
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• pp.2772-2786
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• 2022

We had researched an automatic authentication-supported medical information platform[6]. The proposed automatic authentication consists of user authentication and mobile terminal authentication, and the authentications are performed simultaneously in patients' emergency conditions. In this paper, we studied on finding emergency conditions for the automatic authentication by applying big data processing and AI mechanism on the extended medical information platform with an added edge computing system. We used big data processing, SVM, and 1-Dimension CNN of AI mechanism to find emergency conditions as authentication means considering patients' underlying diseases such as hypertension, diabetes mellitus, and arrhythmia. To quickly determine a patient's emergency conditions, we placed edge computing at the end of the platform. The medical information server derives patients' emergency conditions decision values using big data processing and AI mechanism and transmits the values to an edge node. If the edge node determines the patient emergency conditions, the edge node notifies the emergency conditions to the medical information server. The medical server transmits an emergency message to the patient's charge medical staff. The medical staff performs the automatic authentication using a mobile terminal. After the automatic authentication is completed, the medical staff can access the patient's upper medical information that was not seen in the normal condition.

• International Journal of Advanced Culture Technology
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• v.12 no.1
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• pp.270-275
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• 2024

Introduction. In this study, purpose is to analize the types of golf tourism, inbound or outbound, by using big data and see how movement of industry is being changed and what changes have been made during and after Covid-19 in golf industry. Method Using Textom, a big data analysis tool, "golf tourism" and "Covid-19" were selected as keywords, and search frequency information of Naver and Daum was collected for a year from 1 st January, 2023 to 31st December, 2023, and data preprocessing was conducted based on this. For the suitability of the study and more accurate data, data not related to "golf tourism" was removed through the refining process, and similar keywords were grouped into the same keyword to perform analysis. As a result of the word refining process, top 36 keywords with the highest relevance and search frequency were selected and applied to this study. The top 36 keywords derived through word purification were subjected to TF-IDF analysis, visualization analysis using Ucinet6 and NetDraw programs, network analysis between keywords, and cluster analysis between each keyword through Concor analysis. Results By using big data analysis, it was found out option of oversea golf tourism is affecting on inbound golf travel. "Golf", "Tourism", "Vietnam", "Thailand" showed high frequencies, which proves that oversea golf tour is now the re-coming trends.