• Journal of Creative Information Culture
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• v.5 no.3
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• pp.215-223
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• 2019

The wave of the information age gradually accelerates, and fusion analysis solutions that can utilize these knowledge data according to accumulation of various forms of big data such as large capacity texts, sounds, movies and the like are increasing, Reduction in the cost of storing data accordingly, development of social network service (SNS), etc. resulted in quantitative qualitative expansion of data. Such a situation makes possible utilization of data which was not trying to be existing, and the potential value and influence of the data are increasing. Research is being actively made to present future-oriented education systems by applying these fusion analysis systems to the improvement of the educational system. In this research, we conducted a big data analysis on Twitter, analyzed the natural language of the data and frequency analysis of the word, quantitative measure of how domestic windows education problems and outcomes were done in it as a solution.

• Journal of The Korean Association of Information Education
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• v.26 no.6
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• pp.543-552
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• 2022

This study tried to analyze the social perception of news coverage on inclusive education by using big data analysis techniques. News articles were collected according to the 5-year policy period for the development of special education, and news big data was analyzed. As a result, the frequency of media reports during the five-year policy period of special education development from 1998 in the first year to 2022 in the fifth year was steadily increased. During this period, the top topic words in news coverage changed from words conceptualizing simple definitions to words expressing the active will of students with disabilities for the actual right to education. In addition, as a result of emotional analysis of the overall keywords in the inclusive education news coverage, it was found that the positive word ratio was high. Through this study, it can be seen that interest in news coverage on inclusive education is increasing quantitatively in accordance with changes in special education policies, and the demand for inclusive education is being concreted in the direction of guaranteeing the actual right to education of students with disabilities.

• Journal of the Korean Institute of Landscape Architecture
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• v.49 no.2
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• pp.17-26
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• 2021

For the past half century, the Journal of the Korean Landscape Architecture has been leading the landscape architecture research and industry inclusively. In this study, abstracts of 1,802 articles were collected and analyzed with topic modeling and network analysis method. As a result of this paper, a total of 27 types of subjects were identified. Health and healing in the field of environmental psychology, garden and aesthetics, participation and community, modernity, place and placenness, microclimate, tourism and social equity also have been continued as important research area in this journal. Modernity, community and urban regeneration is hot topics and ecological landscape related topics were cold topics. Although there was a difference by subject, the variability of the research subjects appeared after the 2000s. In Network analysis, it shows that 'Park' is a representative keyword that can symbolize the journal, and 'landscape' is also important a leading area of the journal. Looking at the overall structure of the network, it can be seen that the journal conducts research on 'utilizing', 'using', and creating 'park', 'landscape', and 'space'. This study is meaningful in that it grasped the overall research trend of the journal by using topic modeling and network analysis of text mining.

• Journal of Industrial Convergence
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• v.22 no.6
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• pp.51-59
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• 2024

The purpose of the paper is to suggest government policies that are practically helpful to small business owners in pandemic situations such as COVID-19. To this end, keyword frequency analysis and word cloud analysis of text mining analysis were performed by crawling news articles centered on the keywords "COVID-19 Support for Small Businesses", "The Impact of Small Businesses by Response System to COVID-19 Infectious Diseases", and "COVID-19 Small Business Economic Policy", and major issues were identified through LDA topic modeling analysis. As a result of conducting LDA topic modeling, the support policy for small business owners formed a topic label with government cash and financial support, and the impact of small business owners according to the COVID-19 infectious disease response system formed a topic label with a government-led quarantine system and an individual-led quarantine system, and the COVID-19 economic policy formed a topic label with a policy for small business owners to acquire economic crisis and self-sustainability. Focusing on the organized topic label, it was intended to provide basic data for small business owners to understand the damage reduction policy for small business owners and the policy for enhancing market competitiveness in the future pandemic situation.

• Journal of the Korean Geographical Society
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• v.49 no.6
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• pp.949-969
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• 2014

The purpose of this study is to analyze the share of global citizenship education in the 2009 Revised Social Studies (geography area) School Curriculum of the Republic of Korea. I selected the achievement standards of the geography domain in the fifth and sixth grades as the subjects of analysis. The chosen subjects were examined using content analysis: I used KrKwic, a Korean language content analysis tool, to analyze the content and drew a semantic network of the analysis results using UciNet/NetDraw. I found that the geography domain of the 2009 Revised Primary School Curriculum included the concepts of and factors of global citizenship education. However, global citizenship education did not account for a major portion of the curriculum, and the curriculum achievement standards were noticeably nation-state centered. Global citizenship education factors were not closely associated with to other related factors in fact, they even revealed a isolated pattern. These findings suggest that the inclusion of global citizenship education in primary geography education is limited, because the connections between global citizenship education and related contents, such as the environment, sustainable development, conflict, and cooperation, are probably impeded. Globalization accompanies the transformation of territories, identities, and the relations between nation-states and the world, although nation-states continue to play a significant role in the globalized worlds. Therefore global citizenship education, a educational trend focusing on the global community, is particularly important and is required in the geography curriculum of the global era. I expect that the examination undertaken in this study to contribute to future curriculum revisions regarding globalizatin and global citizenship.

• The KIPS Transactions:PartA
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• v.8A no.4
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• pp.509-516
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• 2001

As results of many genome projects, genomic sequences of many organisms are revealed. Various methods such as global alignment, local alignment are used to analyze the sequences of the organisms, and k -mer analysis is one of the methods for analyzing the genomic sequences. The k -mer analysis explores the frequencies of all k-mers or the symmetry of them where the k -mer is the sequenced base with the length of k. However, existing on-memory algorithms are not applicable to the k -mer analysis because a whole genomic sequence is usually a large text. Therefore, efficient data structures and algorithms are needed. String B-tree is a good data structure that supports external memory and fits into pattern matching. In this paper, we improve the string B-tree in order to efficiently apply the data structure to k -mer analysis, and the results of k -mer analysis for C. elegans and other 30 genomic sequences are shown. We present a visualization system which enables users to investigate the distribution and symmetry of the frequencies of all k -mers using CGR (Chaotic Game Representation). We also describe the method to find the signature which is the part of the sequence that is similar to the whole genomic sequence.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.22 no.6
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• pp.514-523
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• 2021

Recently, the proliferation of mobile simple payment services has been increasingly affecting people's lives. In addition, the increase in research from both China and Korea shows that the continuous development of simple mobile payment services will be very important in the future. The blog posts mentioning Kakao Pay and Alipay were collected, and keyword analysis was performed to investigate differences in consumers' responses to Kakao Pay and Alipay on social media. The frequency of keywords for each part of speech and the frequency of co-occurred words mentioned in one sentence were analyzed. Specifically, common words that appear in both Kakao Pay and Alipay blogs were extracted. The cooccurred words were analyzed to examine how different reactions were made on the same subject. As a result of the analysis, there were concerns among consumers about the trust of Kakao Pay and Alipay's benefits. For a mobile payment service to become competitive, it is necessary to add various additional services or solve security problems.

• Proceedings of the Korean Society of Computer Information Conference
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• 2024.01a
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• pp.55-58
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• 2024

최근 각 기업의 AI 면접시스템 도입이 증가하고 있으며, AI 면접에 대한 실효성 논란 또한 많은 상황이다. 본 논문에서는 AI 면접 과정에서 지원자를 평가하는 방식을 시각, 음성, 자연어처리 3영역에서 구현함으로써, 면접 지원자를 다방면으로 분석 방법론의 적절성에 대해 평가하고자 한다. 첫째, 시각적 측면에서, 면접 지원자의 감정을 인식하기 위해, 합성곱 신경망(CNN) 기법을 활용해, 지원자 얼굴에서 6가지 감정을 인식했으며, 지원자가 카메라를 응시하고 있는지를 시계열로 도출하였다. 이를 통해 지원자가 면접에 임하는 태도와 특히 얼굴에서 드러나는 감정을 분석하는 데 주력했다. 둘째, 시각적 효과만으로 면접자의 태도를 파악하는 데 한계가 있기 때문에, 지원자 음성을 주파수로 환산해 특성을 추출하고, Bidirectional LSTM을 활용해 훈련해 지원자 음성에 따른 6가지 감정을 추출했다. 셋째, 지원자의 발언 내용과 관련해 맥락적 의미를 파악해 지원자의 상태를 파악하기 위해, 음성을 STT(Speech-to-Text) 기법을 이용하여 텍스트로 변환하고, 사용 단어의 빈도를 분석하여 지원자의 언어 습관을 파악했다. 이와 함께, 지원자의 발언 내용에 대한 감정 분석을 위해 KoBERT 모델을 적용했으며, 지원자의 성격, 태도, 직무에 대한 이해도를 파악하기 위해 객관적인 평가지표를 제작하여 적용했다. 논문의 분석 결과 AI 면접의 다면적 평가시스템의 적절성과 관련해, 시각화 부분에서는 상당 부분 정확도가 객관적으로 입증되었다고 판단된다. 음성에서 감정분석 분야는 면접자가 제한된 시간에 모든 유형의 감정을 드러내지 않고, 또 유사한 톤의 말이 진행되다 보니 특정 감정을 나타내는 주파수가 다소 집중되는 현상이 나타났다. 마지막으로 자연어처리 영역은 면접자의 발언에서 나오는 말투, 특정 단어의 빈도수를 넘어, 전체적인 맥락과 느낌을 이해할 수 있는 자연어처리 분석모델의 필요성이 더욱 커졌음을 판단했다.

• Journal of Intelligence and Information Systems
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• v.27 no.3
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• pp.75-94
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• 2021

The low birth rate and shortened military service period are causing concerns about selecting excellent military officers. The Republic of Korea entered a low birth rate society in 1984 and an aged society in 2018 respectively, and is expected to be in a super-aged society in 2025. In addition, the troop-oriented military is changed as a state-of-the-art weapons-oriented military, and the reduction of the military service period was implemented in 2018 to ease the burden of military service for young people and play a role in the society early. Some observe that the application rate for military officers is falling due to a decrease of manpower resources and a preference for shortened mandatory military service over military officers. This requires further consideration of the policy of securing excellent military officers. Most of the related studies have used social scientists' methodologies, but this study applies the methodology of text mining suitable for large-scale documents analysis. This study extracts words of discriminative characteristics from the Republic of Korea Air Force Non-Commissioned Officer Applicant cover letters and analyzes the polarity of pass and fail. It consists of three steps in total. First, the application is divided into general and technical fields, and the words characterized in the cover letter are ordered according to the difference in the frequency ratio of each field. The greater the difference in the proportion of each application field, the field character is defined as 'more discriminative'. Based on this, we extract the top 50 words representing discriminative characteristics in general fields and the top 50 words representing discriminative characteristics in technology fields. Second, the number of appropriate topics in the overall cover letter is calculated through the LDA. It uses perplexity score and coherence score. Based on the appropriate number of topics, we then use LDA to generate topic and probability, and estimate which topic words of discriminative characteristic belong to. Subsequently, the keyword indicators of questions used to set the labeling candidate index, and the most appropriate index indicator is set as the label for the topic when considering the topic-specific word distribution. Third, using L-LDA, which sets the cover letter and label as pass and fail, we generate topics and probabilities for each field of pass and fail labels. Furthermore, we extract only words of discriminative characteristics that give labeled topics among generated topics and probabilities by pass and fail labels. Next, we extract the difference between the probability on the pass label and the probability on the fail label by word of the labeled discriminative characteristic. A positive figure can be seen as having the polarity of pass, and a negative figure can be seen as having the polarity of fail. This study is the first research to reflect the characteristics of cover letters of Republic of Korea Air Force non-commissioned officer applicants, not in the private sector. Moreover, these methodologies can apply text mining techniques for multiple documents, rather survey or interview methods, to reduce analysis time and increase reliability for the entire population. For this reason, the methodology proposed in the study is also applicable to other forms of multiple documents in the field of military personnel. This study shows that L-LDA is more suitable than LDA to extract discriminative characteristics of Republic of Korea Air Force Noncommissioned cover letters. Furthermore, this study proposes a methodology that uses a combination of LDA and L-LDA. Therefore, through the analysis of the results of the acquisition of non-commissioned Republic of Korea Air Force officers, we would like to provide information available for acquisition and promotional policies and propose a methodology available for research in the field of military manpower acquisition.

• Journal of Practical Agriculture & Fisheries Research
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• v.20 no.2
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• pp.57-72
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• 2018

In order to extract meaningful information from the excellent farming settlement cases of young farmers published by KNCAF, we studied the key words with text mining and created a word cloud for visualization. First, in the text mining results for the entire sample, the words 'CEO', 'corporate executive', 'think', 'self', 'start', 'mind', and 'effort' are the words with high frequency among the top 50 core words. Their ability to think, judge and push ahead with themselves is a result of showing that they have ability of to be managers or managers. And it is a expression of how they manages to achieve their dream without giving up their dream. The high frequency of words such as "father" and "parent" is due to the high ratio of parents' cooperation and succession. Also 'KNCAF', 'university', 'graduation' and 'study' are the results of their high educational awareness, and 'organic farming' and 'eco-friendly' are the result of the interest in eco-friendly agriculture. In addition, words related to the 6th industry such as 'sales' and 'experience' represent their efforts to revitalize farming and fishing villages. Meanwhile, 'internet', 'blog', 'online', 'SNS', 'ICT', 'composite' and 'smart' were not included in the top 50. However, the fact that these words were extracted without omission shows that young farmers are increasingly interested in the scientificization and high-tech of agriculture and fisheries Next, as a result of grouping the top 50 key words by crop, the words 'facilities' in livestock, vegetables and aquatic crops, the words 'equipment' and 'machine' in food crops were extracted as main words. 'Eco-friendly' and 'organic' appeared in vegetable crops and food crops, and 'organic' appeared in fruit crops. The 'worm' of eco-friendly farming method appeared in the food crops, and the 'certification', which means excellent agricultural and marine products, appeared only in the fishery crops. 'Production', which is related to '6th industry', appeared in all crops, 'processing' and 'distribution' appeared in the fruit crops, and 'experience' appeared in the vegetable crops, food crops and fruit crops. To visualize the extracted words by text mining, we created a word cloud with the entire samples and each crop sample. As a result, we were able to judge the meaning of excellent practices, which are unstructured text, by character size.