• Knowledge Management Research
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• v.18 no.3
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• pp.81-99
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• 2017

This study is to compare the main subjects of domestic and foreign knowledge management research in terms of keywords and to clarify whether domestic knowledge management research reflects research trends in overseas knowledge management research. Specifically, we try to find out whether the central activities such as knowledge sharing, knowledge generation, and acquisition, which are knowledge management activities of knowledge management research, are being studied without bias. In order to analyze this, we analyzed the data of domestic and foreign knowledge management research for the last 5 years from 2012 to 2016. In Korea, the Knowledge Management Society of Korea collected 167 papers and 787 keywords, and collected 132 papers and 640 keywords from the Korea Society of Management Information Systems in order to distinguish the research areas. Overseas papers collected 315 papers and 1,746 keywords published by Emerald. Also, we collected 382 papers and 1,633 keywords in the Korean Management Review and collected 646 papers and 2,879 keywords in the Korean Business Education Review. Frequency analysis and network analysis of 1,642 papers and 7,685 keywords are summarized as follows. The Knowledge Management Society of Korea has focused on knowledge sharing, and in 2016, interest in knowledge transfer and knowledge search has shifted. The Journal of Knowledge Management, which is published by Emerald, has been a major concern for knowledge transfer and knowledge sharing. The research trends of the Korea Society of Management Information Systems to distinguish a clear identity of knowledge management research are focusing on smart area and mobile domain such as information security domain, cloud, smart phone, and smart work. In the Korea Society of Management Information Systems research, the main subject of knowledge sharing is also commonly found.

• The Korea Journal of Herbology
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• v.30 no.3
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• pp.63-68
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• 2015

Objectives : We applied the term weighting method used in the field of data search to quantify relevancy between symptoms and medicinal herbs, and, based on this, we aim to introduce a method of visualizing the characteristics of medicinal herbs. Methods ： We proposed HF-IFF, an adaptation of TF-IDF, which is a term weighting measurement method adapted in the field of data search. Using this method, we deduced relevancy between symptoms and medicinal herbs In Cheongkangeuigam that was published in 1984 by organizing the medical theory of Cheongkang, Kim Younghoon, and visualized this as a graph in order to compare the characteristics of medicinal herbs used for different symptoms. Results ： HF-IFF is the product of HF and IFF, where HF is the frequency of the relevant medicinal herb for a set of symptoms, and IFF is the inverse of the number of formulations (FF) containing that herb. A total of 251 types of medicinal herb are used in Cheongkangeuigam, and 1538 formulations are classified according to 67 types of symptom. The overall mean for HF-IFF was 0.491, with a maximum of 4.566 and a minimum of 0.013. Conclusions ： In spite of several limitations, we were able to use HF-IFF to measure relevancy between symptoms and medicinal herbs, with formulations as an intermediate. We were able to use the quantified results to visually express the characteristics of the herbs used for symptoms by bubble chart and word-cloud from HF-IFF.

• Journal of Cadastre & Land InformatiX
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• v.49 no.2
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• pp.67-82
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• 2019

The purpose of this study is to analyze the issues and perceptions of smart cities. First, based on the big data analysis platform, big data analysis on smart cities were conducted to derive keywords by year, word cloud, and frequency of generation of smart city keywords by time. Second, trend and flow by area were analyzed by reclassifying major keywords by year based on meta-keywords. Third, emotional recognition flow for smart cities and major emotional keywords were derived. While U-City in the past is mostly centered on creating infrastructure for new towns, recent smart cities are focusing on sustainable urban construction led by citizens, according to the analysis. In addition, it was analyzed that while infrastructure, service, and technology were emphasized in the past, management and methodology were emphasized recently, and positive perception of smart cities was growing. The study could be used as basic data for the past, present and future of smart cities in Korea at a time when smart city services are being built across the country.

• Journal of the Korean Data and Information Science Society
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• v.27 no.4
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• pp.845-854
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• 2016

Sentiment analysis or opinion mining is a technique of text mining employed to identify subjective information or opinions of an individual from documents in blogs, reviews, articles, or social networks. In the literature, only a problem of binary classification of ratings based on review texts in an online review. However, because there can be positive or negative reviews as well as neutral reviews, a multi-class classification will be more appropriate than the binary classification. To this end, we consider the multi-class classification of ratings based on review texts. In the preprocessing stage, we extract words related with ratings using chi-square statistic. Then the extracted words are used as input variables to multi-class classifiers such as support vector machines and proportional odds model to compare their predictive performances.

• The Journal of Bigdata
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• v.3 no.1
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• pp.1-12
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• 2018

Since the beginning of the first online shopping mall, BEST 100 is being provided as the core of all shopping mall websites. BEST 100 is greatly important because consumers can identify popular products at a glance. However, there are only studies using sales outcome indicators, and prior studies using BEST 100 are insignificant. Therefore, this study selected 11 online shopping malls and compared their main characteristics. As a research method, exploratory data analysis technique (EDA) was used by crawling the BEST 100 components of each shopping mall website, such as product name, price, and free shipping check. As a result, the total average price of 11 shopping malls was 72,891.41 won. Sales texts were classified into 8 categories by text mining. The most common category was the fashion part, but it is significant that the setting of the category analyzed the marketing text, not the product attribute. This study has implications for understanding the current online market flow and suggesting future directions by using EDA.

• Journal of the Korea Convergence Society
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• v.12 no.10
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• pp.365-372
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• 2021

The purpose of this study was to examine the statements characteristics of the pressure ulcer nursing record by natural langage processing and assess the prediction accuracy for each pressure ulcer stage. Nursing records related to pressure ulcer were analyzed using descriptive statistics, and word cloud generators (http://wordcloud.kr) were used to examine the characteristics of words in the pressure ulcer prevention nursing records. The accuracy ratio for the pressure ulcer stage was calculated using deep learning. As a result of the study, the second stage and the deep tissue injury suspected were 23.1% and 23.0%, respectively, and the most frequent key words were erythema, blisters, bark, area, and size. The stages with high prediction accuracy were in the order of stage 0, deep tissue injury suspected, and stage 2. These results suggest that it can be developed as a clinical decision support system available to practice for nurses at the pressure ulcer prevention care.

• Journal of the Korea Society of Computer and Information
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• v.26 no.9
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• pp.115-123
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• 2021

This study aims to analyze the changes in public perception of abandoned dogs through big data analysis. Data from January 2017 to July 2020 were collected to analyze how the quantitative change in social issues with abandoned dogs as a keyword had an effect on public perception of abandoned dogs, and factors that influence positive/negative perceptions. As a result of the study, it was confirmed that the number of stray dogs and the number of documents related to stray dogs had a positive correlation, and specific time series changes were found through various analysis techniques such as text mining, network analysis, and sentiment analysis. This study will have significance as basic data that can be used for policy establishment or other research on abandoned dogs. we hope it will help to solve problems so as to improve awareness of abandoned dogs and develop a sense of responsibility.

• Journal of Korean Society of Rural Planning
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• v.27 no.3
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• pp.85-92
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• 2021

As the paradigm of green has been expended as the core of sustainable development in Korea, agro-healing projects increasingly have been a priority at the national policy and investment area. But little is known about the current overview of national research and development(R&D) related to agro-healing. The aim of this study was generally to investigate the research trends of national R&D related to agro-healing over the past five years. Dataset were gathered from provided by National Science & Technology Information Service(NTIS), word cloud techniques were applied. The main results showed that amounts of number and funding related to agro-healing projects have been increasing. In particular, the Rural Development Administration had the highest number of research, and it was found that the Ministry of Trade, Industry and Energy have spended a lot of money on agro-healing. As a results, it is necessary to expand the scope of the field of agro-healing projects, especially at the multisectoral and intersectoral level for improving health, well-being and a sustainable future.

• International Journal of Internet, Broadcasting and Communication
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• v.13 no.4
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• pp.79-89
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• 2021

Electronic learning (e-learning) empowers the higher education in providing sustainable instruction during the infrequent circumstance when the wide-spreading disastrous challenge of the COVID-19 results in the closure of various sectors in the society. During this time, e-learning serves the levels of the education sector such as higher education well by delivering and receiving materials from distance with respect to movement restrictions imposed by the government, for example the Movement Control Order (MCO) in Malaysia. In this qualitative survey, the existing e-learning challenges and the recommended solutions to the problems from the senior lecturers' perspectives were collected through an online open-ended questionnaire. A number of five senior lecturers out of eight at the Universiti Teknologi Malaysia (UTM) answered the questionnaire. The UTM has been capable of providing e-learning courses for all of its lecturers and students during the closure of higher education institutions owing to the pernicious health conditions stemmed from the crisis of the COVID-19. The major existing challenges found in the e-learning program at the UTM and the suggested solutions to address them are listed and the main themes are illustrated in the word cloud format using the NVivo software. In the end, the conclusion is paragraphed and the future work is proposed. Overall, the purpose of this study is to address the e-learning challenges and to prepare a list of recommendations that can serve as solutions from the standpoint of the UTM senior lecturers during the MCO in Malaysia.

• Journal of the Korea Society of Computer and Information
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• v.25 no.12
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• pp.101-107
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• 2020

This paper aims to compare and analyze the major keywords according to the political orientation of progressive and conservative newspapers by utilizing the big data of the four major domestic daily newspapers related to COVID-19, which has entered a long-term war. To this end, 93,917 news reports from Jan. 20 to Sept. 15, 2020 were divided into four stages and the major keywords of the four newspapers were implemented and analyzed in WordCloud. According to the analysis, the conservative newspaper focused on the government's response, criticism, and China's responsibility by mentioning the keywords "government," "president," "state of affairs" and "mask" more than the progressive newspaper, while the progressive newspaper uses keywords that emphasize the seriousness of the disease and the occurrence of a dangerous situation. The Chosun Ilbo found that the use of various keywords during the massive outbreak of collective infections (2.18-5.15), and that the JoongAng Ilbo used keywords criticizing government policies in relation to reports of infectious diseases such as COVID-19, but also used keywords that emphasize the seriousness of diseases used by progressive newspapers and the occurrence of dangerous situations.