• Journal of Digital Convergence
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• v.12 no.6
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• pp.655-667
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• 2014

This paper has identified five major categories of the T2D patients' concerns based on an online forum where the patients voluntarily verbalized their naturally occurring emotional reactions and concerns related to T2D. We have emphasized the fact that the lexical and phrasal analysis brought to the forefront the prevailing negative reactions and desires for clear information, professional advice, and emotional support. This study used lexical and phrasal analysis based on text-mining tools to estimate the potential of using a large sample of patient conversation of a specific disease posted on the internet for clinical features and patients' emotions. As a result, the study showed that quantitative analysis based on text-mining is a viable method of generalizing the psychological concerns and features of T2D patients.

• 한국HCI학회:학술대회논문집
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• 2007.02b
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• pp.656-663
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• 2007

최근 인터넷 공간에서 사용자가 직접 만들어 내는 컨텐츠, 즉 UCC (user created contents, 이하 UCC)에 대한 관심이 그 어느 때보다 증가하고 있다. UCC란 기존의 온라인 컨텐츠 제공업자와 달리 일반 사용자에 의해 만들어져 게시판과 같은 도구를 사용하여 온라인 상에 존재하였다. 그런데 UCC 가 최근 들어 더욱 관심을 받고 있는 이유에는 사용자들이 직접 컨텐츠를 만들어 개제하는 것이 용이하도록 변화된 환경의 조성 및 컨텐츠 제작을 쉽게 할 수 있는 저작도구가 지속적으로 만들어지고 확산되었기 때문이다. 결과적으로 사용자 측면에서는 다른 사람들과 소통하는 통로가 확대되었고, 사업자 측면에서는 보다 컨텐츠를 풍부하게 확보할 수 있는 환경이 열린 것이다. 본 연구는 구비문학의 이론을 통하여 UCC의 활성화에 영향을 미치는 요소를 탐색적으로 살펴보는 것을 목적으로 한다. 구비 문학은 텍스트를 향유하는 사람들 사이에서 공유되는 이야기로서 그 생산 환경의 매커니즘과 텍스트의 발전 양상이 UCC와 매우 유사하다. 따라서 본 연구에서는 자료의 분석과 이론적 모형의 수립 과정 전반에 있어 구비 문학의 이론과 접근 방법을 사용하였다. UCC가 매우 활발하게 생산되는 주제를 선정하여, 그 주제에 해당하는 커뮤니티의 특성, 사용자들 간의 관계, 사용자 정책 등 차이가 있는 세 온라인 커뮤니티를 선정하였다. 선정된 온라인 커뮤니티의 게시판의 포스트와 댓글을 프로그램을 통하여 수집하고 분석하였으며, 그 분석된 데이터를 바탕으로 사용자를 선정하여 심층 인터뷰를 진행하였다. 심층 인터뷰 데이터는 근거이론은 이용하여 분석하였다. 본 연구의 결과는 UCC 확산이라는 새로운 인터넷 패러다임 속에서 이를 구비 문학의 이론으로 분석했다는 점에서 학문적 의의가 있다. 또한 성격이 다른 세 개의 사이트에서의 UCC를 비교함으로써 UCC를 기반으로 한 사이트 설계의 가이드 라인이 될 수 있는 실용적 의의를 가진다.

• The Journal of the Convergence on Culture Technology
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• v.6 no.3
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• pp.275-282
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• 2020

Social interest on high-quality specialty coffee is increased due to customers' growing experience upon coffee and recent change of coffee culture, which is taking one step further from putting emphasis on not just price and quality but also psychological satisfaction. As a culture of drinking coffee and giving much value on its taste and flavor, a number of customers increasingly demand coffee which is probable to suit one's taste. Likewise, the number of specialty coffee shops is increasing with growing qualities of their coffee. Therefore, the purpose of this study is to analyze the main attributes of specialty coffee and to build a marketing system for specialty coffee shops. The text mining on domestic web portal sites by online big-data analysis is used to extract components of properties of specialty coffee and analyze the degree of how the elements affect the properties. According to the result of the study, words related to coffee taste, coffee beans and baristas were found to play a central role in the properties of specialty coffee.

• Journal of Digital Convergence
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• v.18 no.2
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• pp.285-290
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• 2020

This study focus on improving the text language proficiency regarding users' written text. In order to tone up accuracy improvement in writing, Computer Assisted Language Learning(CALL) can be primarily used as one of the most efficient tools. This study proposes a English Grammar Checking Application that can improve the accuracy over the current applications. The proposed system is capable of defining the difference between a Noun and a Noun Phrase which is critical in improving grammar accuracy for those who use Englilsh as a foreign language in English writing.

• Journal of the Korean Society for Library and Information Science
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• v.48 no.1
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• pp.415-439
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• 2014

The purpose of this study is to analyze mobile web accessibility of public libraries. To achieve this, accessibility checklists were driven from mobile web and application guidelines. The study also conducted automatic and manual evaluations. As results, the study found that text alternatives for resource image, main menu, image for text contents were mainly missing. In addition, focus for retrieval, operating system accessibility for retrieval, and id & password label, color difference for library calendar and seat reservation, brightness difference for main manu and resource display, and space between controls for retrieval were mainly missing. The study also suggested focal missing areas for main library services. It will be utilized as checklists for development of mobile services.

• Journal of the Institute of Convergence Signal Processing
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• v.20 no.4
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• pp.193-198
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• 2019

The wide spread of genuine and fake information on internet has lead to various studies on text analysis. Copying and pasting others' work without acknowledgement, research results manipulation without proof has been trending for a while in the era of data science. Various tools have been developed to reduce, combat and possibly eradicate plagiarism in various research fields. Text similarity measurements can be manually done by using both parametric and non parametric methods of which this study implements cosine similarity and Pearson correlation as parametric while Spearman correlation as non parametric. Cosine similarity and Pearson correlation metrics have achieved highest coefficients of similarity while Spearman shown low similarity coefficients. We recommend the use of non parametric methods in measuring text similarity due to their non normality assumption as opposed to the parametric methods which relies on normality assumptions and biasness.

• Journal of Digital Convergence
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• v.14 no.11
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• pp.101-106
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• 2016

A number of non-structured data associated with lectures in the field of university education have been generated and it is an important consideration of the students's written comments lecture evaluation. The purpose of this study is to find student interaction factors associated with the student evaluation of teaching at universities, and to provide some insights into improving the student evaluation program based on the results. So, this study consists of three steps that create interaction score, collect student's written comments satisfaction, and analyze an individual professor score. There are a number of limitations to this study. The limitation is that the study was conducted on a narrow sample of the overall student population.

• Journal of Korean Library and Information Science Society
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• v.49 no.2
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• pp.267-300
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• 2018

The purpose of this study is to develop conceptualization models of reading, information, ICT, and digital literacy through conceptual differences of these literacy by reviewing and defining the concepts of literacy as well as reading, information, ICT, and digital literacy. Computer literacy has emerged as a concept that explains the phenomenon of contemporary social, cultural, and information technology development, and since then, computer literacy has since changed to IT, ICT literacy, and digital literacy. As a result of the study, a conceptualization model of the reading, information, ICT, and digital literacy was developed. In this model, these literacy whose terms have changed according to the technological development of media, have been classified as medium-centered literacy. And reading and information literacy that focuses on the cognitive process of understanding, utilizing, and evaluating texts and information is categorized as process-oriented literacy. In the digital environment, reading and information literacy is a core competence to critically think and evaluate the texts that are on media, and further research is needed to reduce the reading and the information gap among readers.

• Journal of the Korean Institute of Intelligent Systems
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• v.25 no.5
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• pp.470-476
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• 2015

Big data has been used in diverse areas. For example, in computer science and sociology, there is a difference in their issues to approach big data, but they have same usage to analyze big data and imply the analysis result. So the meaningful analysis and implication of big data are needed in most areas. Statistics and machine learning provide various methods for big data analysis. In this paper, we study a process for big data analysis, and propose an efficient methodology of entire process from collecting big data to implying the result of big data analysis. In addition, patent documents have the characteristics of big data, we propose an approach to apply big data analysis to patent data, and imply the result of patent big data to build R&D strategy. To illustrate how to use our proposed methodology for real problem, we perform a case study using applied and registered patent documents retrieved from the patent databases in the world.

• Journal of the Korea Convergence Society
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• v.11 no.5
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• pp.199-207
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• 2020

Recently, big data analysis has drawn attention in various fields as it can generate value from large amounts of data and is also used to run political campaigns or predict results. However, existing research had limitations in compiling information about candidates at a high-level by analyzing only specific SNS data. Therefore, this study analyses news trends, topics extraction, sentiment analysis, keyword analysis, comment analysis for the 2017 presidential election of South Korea. The results show that various topics had been generated, and online opinions are extracted for trending keywords of respective candidates. This study also shows that portal news and comments can serve as useful tools for predicting the public's opinion on social issues. This study will This paper advances a building strategic course of action by providing a method of analyzing public opinion across various fields.