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Trend Analysis using Topic Modeling for Simulation Studies (토픽 모델링을 이용한 시뮬레이션 연구 동향 분석)

  • Na, Sang-Tae;Kim, Ja-Hee;Jung, Min-Ho;Ahn, Joo-Eon
    • Journal of the Korea Society for Simulation
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    • v.25 no.3
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    • pp.107-116
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    • 2016
  • The recent diversification in terms of the scope and techniques used for simulations has highlighted the importance of analyzing state of the art trends and applying these for educational and study purposes. While qualitative methods such as literature research or experts' assessments have previously been used, such methods are in fact likely to reflect the subjective viewpoint of experts, and to involve too much time and money for the results obtained. For the purpose of an objective analysis, a quantitative analysis that included the examination of topics found in domestic academic journal articles was conducted in the present study. In this regard, simulation was found to be most actively used domestically in the electrical and electronic fields. In addition, simulation was also found to be employed for the purpose of education and entertainment in the social sciences. The results of this study are expected to help to facilitate the prediction of the direction of the development of not only the Korea Society for Simulation, but also domestic simulation studies. This study also raises the possibility of applying text mining to trend analysis, and proves that it can be a useful method for deriving future key topics and helping experts' decisions regarding quantitative data.

Methodology for Classifying Hierarchical Data Using Autoencoder-based Deeply Supervised Network (오토인코더 기반 심층 지도 네트워크를 활용한 계층형 데이터 분류 방법론)

  • Kim, Younha;Kim, Namgyu
    • Journal of Intelligence and Information Systems
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    • v.28 no.3
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    • pp.185-207
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    • 2022
  • Recently, with the development of deep learning technology, researches to apply a deep learning algorithm to analyze unstructured data such as text and images are being actively conducted. Text classification has been studied for a long time in academia and industry, and various attempts are being performed to utilize data characteristics to improve classification performance. In particular, a hierarchical relationship of labels has been utilized for hierarchical classification. However, the top-down approach mainly used for hierarchical classification has a limitation that misclassification at a higher level blocks the opportunity for correct classification at a lower level. Therefore, in this study, we propose a methodology for classifying hierarchical data using the autoencoder-based deeply supervised network that high-level classification does not block the low-level classification while considering the hierarchical relationship of labels. The proposed methodology adds a main classifier that predicts a low-level label to the autoencoder's latent variable and an auxiliary classifier that predicts a high-level label to the hidden layer of the autoencoder. As a result of experiments on 22,512 academic papers to evaluate the performance of the proposed methodology, it was confirmed that the proposed model showed superior classification accuracy and F1-score compared to the traditional supervised autoencoder and DNN model.

A Comparative Study on the Social Awareness of Metaverse in Korea and China: Using Big Data Analysis (한국과 중국의 메타버스에 관한 사회적 인식의 비교연구: 빅데이터 분석의 활용 )

  • Ki-youn Kim
    • Journal of Internet Computing and Services
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    • v.24 no.1
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    • pp.71-86
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    • 2023
  • The purpose of this exploratory study is to compare the differences in public perceptual characteristics of Korean and Chinese societies regarding the metaverse using big data analysis. Due to the environmental impact of the COVID-19 pandemic, technological progress, and the expansion of new consumer bases such as generation Z and Alpha, the world's interest in the metaverse is drawing attention, and related academic studies have been also in full swing from 2021. In particular, Korea and China have emerged as major leading countries in the metaverse industry. It is a timely research question to discover the difference in social awareness using big data accumulated in both countries at a time when the amount of mentions on the metaverse has skyrocketed. The analysis technique identifies the importance of key words by analyzing word frequency, N-gram, and TF-IDF of clean data through text mining analysis, and analyzes the density and centrality of semantic networks to determine the strength of connection between words and their semantic relevance. Python 3.9 Anaconda data science platform 3 and Textom 6 versions were used, and UCINET 6.759 analysis and visualization were performed for semantic network analysis and structural CONCOR analysis. As a result, four blocks, each of which are similar word groups, were driven. These blocks represent different perspectives that reflect the types of social perceptions of the metaverse in both countries. Studies on the metaverse are increasing, but studies on comparative research approaches between countries from a cross-cultural aspect have not yet been conducted. At this point, as a preceding study, this study will be able to provide theoretical grounds and meaningful insights to future studies.

A Study on the Selection Criteria for Picture Books as Reading Materials for Middle School Students (중학생을 위한 독서자료로써 그림책의 선정 기준에 관한 연구)

  • Song-Hee Kim;Byoung-Moon So
    • Journal of the Korean BIBLIA Society for library and Information Science
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    • v.34 no.3
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    • pp.297-318
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    • 2023
  • The purpose of this study is to propose criteria for selecting picture books as various reading education materials for middle school students and to check whether it can be applied to book selection. First, identified the educational value of picture books as reading materials and the criteria for selecting picture books by academic field through previous studies. After integrating the commonalities of various picture book selection criteria presented in previous studies by categorizing them into illustrations, text, and other categories. And it devised selection criteria that can be applied after selecting middle school students as readers. Based on the unified picture book selection criteria, a survey was conducted to ask in-service librarians about the main criteria to consider when selecting picture books for middle school students, and intensive interviews were conducted with experts who have experience in picture book education. As a result, the picture book selection criteria from previous studies were revised and supplemented with two criteria related to text, four criteria related to pictures, and five other criteria, and presented as picture book selection criteria for middle school students. To verify the practicality of the picture book selection criteria, it checked the applicability of each category of criteria to picture books recommended by the Children's Book Research Society (ages 13 and older). Out of 22 picture books for middle school students, 15 books could be applied to all categories of the selection criteria, showing significant practicality.

Abbreviation Disambiguation using Topic Modeling (토픽모델링을 이용한 약어 중의성 해소)

  • Woon-Kyo Lee;Ja-Hee Kim;Junki Yang
    • Journal of the Korea Society for Simulation
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    • v.32 no.1
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    • pp.35-44
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    • 2023
  • In recent, there are many research cases that analyze trends or research trends with text analysis. When collecting documents by searching for keywords in abbreviations for data analysis, it is necessary to disambiguate abbreviations. In many studies, documents are classified by hand-work reading the data one by one to find the data necessary for the study. Most of the studies to disambiguate abbreviations are studies that clarify the meaning of words and use supervised learning. The previous method to disambiguate abbreviation is not suitable for classification studies of documents looking for research data from abbreviation search documents, and related studies are also insufficient. This paper proposes a method of semi-automatically classifying documents collected by abbreviations by going topic modeling with Non-Negative Matrix Factorization, an unsupervised learning method, in the data pre-processing step. To verify the proposed method, papers were collected from academic DB with the abbreviation 'MSA'. The proposed method found 316 papers related to Micro Services Architecture in 1,401 papers. The document classification accuracy of the proposed method was measured at 92.36%. It is expected that the proposed method can reduce the researcher's time and cost due to hand work.

A Study on the Tangibility and Intangibility Value Contents Influence Factor of Jongmyo Shrine Using Text Mining Analysis (텍스트 마이닝 분석을 활용한 종묘의 유·무형 콘텐츠 영향요인 연구)

  • Park, Eun Soo;Kim, Ji Eun
    • Korea Science and Art Forum
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    • v.22
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    • pp.169-183
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    • 2015
  • As time is rapidly changing, the culture to represent an era is getting more subdivided and complex. Due to cultural diversity, the influence, cause, characteristics which could be understood in individual field centered by space in the past cannot be understood now only by the viewpoint of one field, and it has become difficult to predict and correspond to the change of the future. With the development of information and knowledge delivery system, various cultural contents to form a space are being created and lapsed, but there are a lot of parts which cannot be explained or understood by only one point of view. To inspect these situation, this study is aimed to draw the Tangibility and Intangibility Value causes that became the influence with Jongmyo Shrine, designated from UNESCO at February 1995, a traditional space with historical superiority, analyze the key factors that became the main factor to form the space, and consider the importance of the related factors. The unconstructured data technique which is applied as the method of analysis in this study can be said to be a new value judgement and viewpoint in interpreting the space. Therefore, this study is a new trial to provide a frame for multilaterally interpreting the various traditional space and culture of Korea from the past to the present.

Exploratory Study on the Application of Blockchain for ESG Management in the Distribution Industry (유통업계 ESG 경영을 위한 블록체인 도입 탐색적 연구)

  • Yeji Choi;Jaewook Byun;Jiwon Moon;Hangbae Chang
    • Knowledge Management Research
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    • v.24 no.3
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    • pp.217-237
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    • 2023
  • Recently, in the face of successive and unexpected global economic risks, ESG(Environmental, Social, and Governance) management has risen as an essential survival strategy for businesses. Particularly, the supply chain disruptions due to the COVID-19 pandemic have added to the uncertainty of risks, heightening the importance of ESG management in the distribution industry. In this context, the role of blockchain technology in strengthening and managing the connection between the distribution industry and ESG management has become increasingly significant. While there have been extensive proposals for business models that integrate blockchain technology into distribution, few studies have specifically focused on the feasibility and effectiveness of applying blockchain to ESG management in this field. Therefore, this study analyzed the relationship between blockchain and ESG management in the distribution industry by employing association analysis, a text mining technique, on Korean academic research. Through this, the study confirmed the possibility of implementing blockchain in the distribution industry's ESG management and presented keywords to guide future research directions. The findings obtained from this study are expected to be utilized as foundational research for future studies in constructing blockchain-based business models for ESG management in the distribution industry.

Analysis of Changes in Restaurant Attributes According to the Spread of Infectious Diseases: Application of Text Mining Techniques (감염병 확산에 따른 레스토랑 선택속성 변화 분석: 텍스트마이닝 기법 적용)

  • Joonil Yoo;Eunji Lee;Chulmo Koo
    • Information Systems Review
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    • v.25 no.4
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    • pp.89-112
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    • 2023
  • In March 2020, as it was declared a COVID-19 pandemic, various quarantine measures were taken. Accordingly, many changes have occurred in the tourism and hospitality industries. In particular, quarantine guidelines, such as the introduction of non-face-to-face services and social distancing, were implemented in the restaurant industry. For decades, research on restaurant attributes has emphasized the importance of three attributes: atmosphere, service quality, and food quality. Nevertheless, to the best of our knowledge, research on restaurant attributes considering the COVID-19 situation is insufficient. To respond to this call, this study attempted an exploratory approach to classify new restaurant attributes based on understanding environmental changes. This study considered 31,115 online reviews registered in Naverplace as an analysis unit, with 475 general restaurants located in Euljiro, Seoul. Further, we attempted to classify restaurant attributes by clustering words within online reviews through TF-IDF and LDA topic modeling techniques. As a result of the analysis, the factors of "prevention of infectious diseases" were derived as new attributes of restaurants in the context of COVID-19 situations, along with the atmosphere, service quality, and food quality. This study is of academic significance by expanding the literature of existing restaurant attributes in that it categorized the three attributes presented by existing restaurant attributes and further presented new attributes. Moreover, the analysis results have led to the formulation of practical recommendations, considering both the operational aspects of restaurants and policy implications.

A Psychological Approach to Mass Culture for Investigation (대중문화의 심리학적 접근과 탐색 )

  • You-Kyung Yoon ;Jee-Young Chae
    • Korean Journal of Culture and Social Issue
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    • v.11 no.3
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    • pp.67-89
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    • 2005
  • This overview study of mass culture is based on an academic point of view and based thereon an investigation of mass culture from a psychological standpoint follows. This study reviewed previous studies of mass culture that have been done so far divided into Producer-oriented, Text Decoding-oriented, and Recipient Theory, according to subjects of the study. The studies were also reviewed from the viewpoints of industry, consumer science, education, and developmental psychology. Further, it was discussed how trends and limitations in research were covered according to each viewpoint on mass culture. Based on the analysis, this study aims to promote overall psychological interest in studies of mass culture; to present the necessity of analysis and measurement of emotional experience on mass culture; to increase the roles of industrial and consumer science approaches in terms of planning and culture; to change the viewpoint of developmental psychology that accepts youth culture positively; and, to present interdisciplinary studies related to mass culture. Mass culture has already penetrated deeply into real life but there are few analyses and interpretations of mass culture in terms of psychology. This study is meaningful from the aspect that discussion of mass culture has been placed in a position that recognizes the entity of and interest in mass culture. Through this study, I hope that the scope of interest in psychology will expand and that approaches to mass culture will become more diversified.

User Experience Analysis and Management Based on Text Mining: A Smart Speaker Case (텍스트 마이닝 기반 사용자 경험 분석 및 관리: 스마트 스피커 사례)

  • Dine Yeon;Gayeon Park;Hee-Woong Kim
    • Information Systems Review
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    • v.22 no.2
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    • pp.77-99
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    • 2020
  • Smart speaker is a device that provides an interactive voice-based service that can search and use various information and contents such as music, calendar, weather, and merchandise using artificial intelligence. Since AI technology provides more sophisticated and optimized services to users by accumulating data, early smart speaker manufacturers tried to build a platform through aggressive marketing. However, the frequency of using smart speakers is less than once a month, accounting for more than one third of the total, and user satisfaction is only 49%. Accordingly, the necessity of strengthening the user experience of smart speakers has emerged in order to acquire a large number of users and to enable continuous use. Therefore, this study analyzes the user experience of the smart speaker and proposes a method for enhancing the user experience of the smart speaker. Based on the analysis results in two stages, we propose ways to enhance the user experience of smart speakers by model. The existing research on the user experience of the smart speaker was mainly conducted by survey and interview-based research, whereas this study collected the actual review data written by the user. Also, this study interpreted the analysis result based on the smart speaker user experience dimension. There is an academic significance in interpreting the text mining results by developing the smart speaker user experience dimension. Based on the results of this study, we can suggest strategies for enhancing the user experience to smart speaker manufacturers.