• Journal of Digital Convergence
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• v.14 no.12
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• pp.173-182
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• 2016

AI (Artificial Intelligence) has attracted interest as a key element for technological advancement in various fields. In Korea, internet companies are leading the development of AI business technology. Active government funding plans for AI technology has also drawn interest. But not everyone is optimistic about AI. Both positive and negative opinions coexist about AI. However, attempts on analyzing people's opinions about AI in a quantitative way was scarce. In this study, we used text mining on SNS (Social Networking Service) to collect opinions about AI. And then we performed a comparative analysis about whether people view it as a positive thing or a negative thing and performed a comparative analysis to recognize popular key-words. Based on the results, it was confirmed that the change of key-words and negative posts have increased through time. And through these results, we were able to predict trend about AI.

• Journal of KIISE
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• v.44 no.2
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• pp.139-147
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• 2017

Most of the information prevailing in the Internet space consists of textual information. So one of the main topics regarding the huge document analyses that are required in the "big data" era is the development of an automated understanding system for textual data; accordingly, the automation of the keyword extraction for text summarization and abstraction is a typical research problem. But the simple listing of a few keywords is insufficient to reveal the complex semantic structures of the general texts. In this paper, a text-visualization method that constructs a graph by computing the related degrees from the selected keywords of the target text is developed; therefore, two construction models that provide the edge relation are proposed for the computing of the relation degree among keywords, as follows: influence-interval model and word- distance model. The finally visualized graph from the keyword-derived edge relation is more flexible and useful for the display of the meaning structure of the target text; furthermore, this abstract graph enables a fast and easy understanding of the target text. The authors' experiment showed that the proposed abstract-graph model is superior to the keyword list for the attainment of a semantic and comparitive understanding of text.

• Fashion & Textile Research Journal
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• v.11 no.2
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• pp.210-218
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• 2009

The Purpose of this study is to demonstrate Storytelling as an effective device for Fashion Design by establishing relationship between Fashion Design Process and Storytelling. Through researching a social background and a concept of storytelling, found that story used interactively is a powerful tool for attention, understanding and change in both individuals and communities. Analysed the elements and the structure of storytelling and Fashion Design Process, by researching preceding researches. Therefore, we proposed a new four elements -text factor, visual factor, audio factor and virtual factor- and four steps (1)exploring stories, (2)planning a story, (3)building the story, (4)do storytelling- of storytelling and four steps-(1)gathering and analysing informations, (2)building a concept, (3)planning and developing a design, (4)do evaluation and make decision- of fashion design process. Through comparative analysis, we found a closeness between two structures, a use of common factors and also found characteristics to be considered in each stage. In the first stage, we found text, visual and audio factor as common factors. In the second stage, we suggested text and visual factor as common factors and also suggested clarity, realism and probability as characteristics. In the third stage, we found text, visual and virtual factor and also found dynamism, immersion and continuity. In the last stage, we suggested text, visual, virtual and audio factor and also suggested presence and interactivity as characteristics.

• The Journal of Information Systems
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• v.28 no.2
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• pp.153-179
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• 2019

Purpose This study collects the issues about work-life balance in Korea and United States and suggests the specific plans for work-life balance by the comparison and analysis. The objective of this study is to contribute to the improvement of people's life quality by understanding the concept of work-life balance that has become the issue recently and offering the detailed plans to be considered in respect of individual, corporate and governmental level for society of work-life balance. Design/methodology/approach This study collects work-life balance related issues through recruit sites in Korea and United States, compares and analyzes the collected data from the results of three text mining techniques such as LDA topic modeling, term frequency analysis and keyword extraction analysis. Findings According to the text mining results, this study shows that it is important to build corporate culture that support work-life balance in free organizational atmosphere especially in Korea. It also appears that there are the differences against whether work-life balance can be achieved and recognition and satisfaction about work-life balance along type of company or sort of working. In case of United States, it shows that it is important for them to work more efficiently by raising teamwork level among team members who work together as well as the role of the leaders who lead the teams in the organization. It is also significant for the company to provide their employees with the opportunity of education and training that enables them to improve their individual capability or skill. Furthermore, it suggests the roles of individuals, company and government and specific plans based on the analysis of text mining results in both countries.

• The Mathematical Education
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• v.38 no.1
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• pp.1-14
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• 1999

It has already been fifty years since the Korean peninsula was divided into two nations, South and North Korea. Owing to forming different political and social structures with each other, we can conjecture that there are much heterogeneity in education. On the assumption that education plays important role in coming to an accommodation and in restoring homogeneity of the Korean race after unification, we consider the investigation of the contents of mathematics text-book of secondary schools as a meaningful research to make provision against unification. In this paper, we shall investigate the learning contents, and the teaming substances and sequences in mathematics of secondary schools between South and North Korea by falling into four regions; algebra and statistics, analysis and geometry. By grasping the special features of terms, teaming subject matters and learning substances, and clarifying their distinctions, we shall present some reforms measure of distinctions.

• Proceedings of the Korean Society of Computer Information Conference
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• 2019.01a
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• pp.305-306
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• 2019

2019학년도 초등학교 5-6학년군에 2015 개정 교육과정이 전면 적용된다. 본 논문에서는 2015 개정 교육과정에 따른 실과 검정 교과서 6종 소프트웨어 교육 단원의 외적 체제를 비교 분석하였다. 단원 체제 분석 결과 모든 교과서에 공통적으로 대단원명, 대단원 차례, 중단원명, 본문텍스트, 본문삽화, 용어 설명, 단원 마무리 등이 제시되어 있었다. 단원 구성 분석 결과 소프트웨어 교육 단원은 전체 교과서 분량의 18.8~25%까지 교과서별로 다양한 비율을 차지하고 있었다. 후속 연구로는 본 논문에서 다룬 교과서의 외적 체제 뿐 아니라 내적 체제 까지를 포함하여 각 교과서의 소프트웨어 교육 단원을 전체적인 틀에서 비교 분석 할 것이다.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2022.10a
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• pp.34-36
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• 2022

In the existing text sentiment analysis models, the entire text is usually directly modeled as a whole, and the hierarchical relationship between text contents is less considered. However, in the practice of sentiment analysis, many texts are mixed with multiple emotions. If the semantic modeling of the whole is directly performed, it may increase the difficulty of the sentiment analysis model to judge the sentiment, making the model difficult to apply to the classification of mixed-sentiment sentences. Therefore, this paper proposes a sentiment analysis model BHGCN that considers the text hierarchy. In this model, the output of hidden states of each layer of BERT is used as a node, and a directed connection is made between the upper and lower layers to construct a graph network with a semantic hierarchy. The model not only pays attention to layer-by-layer semantics, but also pays attention to hierarchical relationships. Suitable for handling mixed sentiment classification tasks. The comparative experimental results show that the BHGCN model exhibits obvious competitive advantages.

• The Journal of Information Systems
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• v.32 no.3
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• pp.183-203
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• 2023

Purpose The purpose of this study is to examine the current operational status and problems of the Public Warning System (PWS) in China, and to propose feasible solutions to improve the performance and efficiency of the PWS through a comparative analysis with the Cell Broadcast Service (CBS)-based disaster SMS system adopted by other developed countries in the world. Design/methodology/approach In this study, the characteristics of PWS using SMS, applications, and CBS, respectively, are analyzed in detail, and compared and analyzed in terms of convenience, standardization, data security, speed, and location accuracy. In addition, CBS-based PWS in developed countries, such as U.S., E.U., Korea and Japan, were studied and their performance on key criteria was evaluated. Findings Based on the results of the study, the problems of China's PWS are summarized and recommendations are made to improve the PWS through the introduction of CBS technology. To this end, specific improvement measures are proposed in terms of the application of CBS technology, system construction and operation, and improvement of data security. In addition, the comparative analysis of PWSs in other developed countries is conducted to provide reference for the direction of PWS's improvement.

• The Journal of Korean Medical History
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• v.31 no.1
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• pp.57-70
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• 2018

Much research has already been done on Donguibogam. However, comparison of specific characters was not done because researchers found it difficult to compare different editions of the text in one place. Recently, important editions have been published on the Internet, making comparison possible. In this paper, researchers compare eight editions Donguibogam, including the original edition published in 1613 and seven other editions corrected by the Naeuiwon (Joseon Dynasty National Medical Center). The comparison results were summarized and tabulated. The results of the comparison are analyzed and presented in this article as a chart. The result of comparing the characters and the analyzed graph were in agreement. The authors propose that all written and electronic publications of Donguibogam should refer to other editions implied, quoted or referenced within the text and including with proper citations, and reference the original and first edition. Inadequate referencing will pollute future knowledge of this foundational text of Traditional Korean Medicine and may result in perpetration of mis-information. Based on accumulated knowledge and study of historical Korean Medicine texts, the Namsan edition made a mistake in the editing process. The year of publication of Gabsul-yoengyoeng-gegan Edition needs to be studied again and corrections made where appropriate.

• Journal of Korean Medical classics
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• v.33 no.2
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• pp.51-59
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• 2020

Objectives : We would like to study what is the most appropriate "feature" to effectively perform authorship attribution of the text of Traditional East Asian Medicine Methods : The authorship attribution performance of the Support Vector Machine (SVM) was compared by cross validation, depending on whether the function words or content words, single word or collocations, and IDF weights were applied or not, using 'Variorum of the Nanjing' as an experimental Corpus. Results : When using the combination of 'function words/uni-bigram/TF', the performance was best with accuracy of 0.732, and the combination of 'content words/unigram/TFIDF' showed the lowest accuracy of 0.351. Conclusions : This shows the following facts from the authorship attribution of the text of East Asian traditional medicine. First, function words play an important role in comparison to content words. Second, collocations was relatively important in content words, but single words have more important meanings in function words. Third, unlike general text analysis, IDF weighting resulted in worse performance.