• Archives of design research
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• v.14 no.3
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• pp.165-176
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• 2001

A corporate identity is an expression of a company's personality and philosophy. From Trademarks to Letterheads, most of companies are eager to show up themselves to the audience. Nowadays the Web has quid(Iy emerged as the most influential communications media for the public. In aspects of this situation, traditional corporate identity program has to change to accord with the new media. Especially print media news has broaden their line to the Web, but most of them are lacking in the express their Identity, Therefore, it is an urgent problem to find their Identity on the Web site. In this paper, I am going to analyze the new aspects of identity in the news site on the web.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2009.10a
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• pp.1071-1074
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• 2009

In a pre-existing online newspaper has inconvenience such that a difference of a newspaper from other newspapers is confirmed on another script window. To solve this inconvenience, we propose a system called Rose News Reader. Since our proposed system classifies the articles with respect to the publishers and domain, a user can compare the articles from diverse publisher and analyze them to obtain correct facts.

• The Journal of the Korea Contents Association
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• v.19 no.9
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• pp.1-10
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• 2019

The purpose of this study is to investigate the influence of exogenous variables on the intention to use AI speaker. An online survey was administrated to 305 AI speaker users in order to examine the effect of the personal characteristics (self-efficacy, innovativeness, suitability, and enjoyment) and social impact (social conformity and social image) on perceived usefulness and easiness. The results indicate that (1) self-efficacy and social conformity have positively effect on perceived easiness; (2) suitability and social image have positively effect on perceived usefulness whereas innovativeness has negatively effect on perceived usefulness; (3) perceived usefulness and perceived easiness have significant effect on the intention to use AI speaker.

• KIPS Transactions on Software and Data Engineering
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• v.9 no.8
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• pp.251-258
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• 2020

A training dataset for text summarization consists of pairs of a document and its summary. As conventional approaches to building text summarization dataset are human labor intensive, it is not easy to construct large datasets for text summarization. A collection of news articles is one of the most popular resources for text summarization because it is easily accessible, large-scale and high-quality text. From social media news services, we can collect not only headlines and subheads of news articles but also summary descriptions that human editors write about the news articles. Approximately 425,000 pairs of news articles and their summaries are collected from social media. We implemented an automatic extractive summarizer and trained it on the dataset. The performance of the summarizer is compared with unsupervised models. The summarizer achieved better results than unsupervised models in terms of ROUGE score.

• The Journal of the Korea Contents Association
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• v.22 no.4
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• pp.301-313
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• 2022

This study aims to investigate the causal relationship between variables of UTAUT2 model and the acceptance intention by Netflix and Wavve intention to adopt and acceptance intent by plan package. The results indicate that (1)First, the intention of Netflix adoption was influenced by performance expectancy, effort expectancy, hedonic motivation, price value, and habit; (2) the intention of wave adoption was influenced by performance expectancy, social influence, price value, and habit. (3)in the acceptance intention of Netflix's acceptance intent by plan package, price value and habit, performance expectancy and habit influenced on the acceptance intent of premium plan, and did not affect the standard plan; (4) in the acceptance intention of the basic plan by the Wavve plan, the price value had a negative effect on the acceptance intention of the basic plan, and the habit had a positive effect.The social impact on the acceptance intention of the standard rate plan, the price value and habit of the acceptance intention of the premium rate plan were affected.

• Journal of the Korea Convergence Society
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• v.9 no.7
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• pp.25-31
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• 2018

Online news has replaced the traditional newspaper and has brought about a profound transformation in the way we access and share information. News websites have had the ability for users to post comments for quite some time, and some have also begun to crowdsource reactions to news articles. The field of sentiment analysis seeks to computationally model the emotions and reactions experienced when presented with text. In this work, we analyze more than 100,000 news articles over ten categories with five user-generated emotional annotations to determine whether or not these reactions have a mathematical correlation to the news body text and propose a simple sentiment analysis algorithm that requires minimal preprocessing and no machine learning. We show that it is effective even for a morphologically complex language like Korean.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.21 no.9
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• pp.345-351
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• 2020

Administrative agencies today are paying keen attention to big data analysis to improve their policy responsiveness. Of all the big data, news articles can be used to understand public opinion regarding policy and policy issues. The amount of news output has increased rapidly because of the emergence of new online media outlets, which calls for the use of automated bots or automatic document classification tools. There are, however, limits to the automatic collection of news articles related to specific agencies or departments based on the existing news article categories and keyword search queries. Thus, this paper proposes a method to process articles using classification glossaries that take into account each agency's different work features. To this end, classification glossaries were developed by extracting the work features of different departments using Word2Vec and topic modeling techniques from news articles related to different agencies. As a result, the automatic classification of newspaper articles for each department yielded approximately 71% accuracy. This study is meaningful in making academic and practical contributions because it presents a method of extracting the work features for each department, and it is an unsupervised learning-based automatic classification method for automatically classifying news articles relevant to each agency.

• Digital Contents
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• no.11 s.90
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• pp.88-97
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• 2000

정보통신부가 후원하고 한국데이터베이스진흥센터와 조선일보, 매일경제신문, 한국소프트웨어진흥원이 주관한 2000년도 제 3/4분기 디지털콘텐츠 대상 수상식이 지난 10월 6일 정보통신부 중회의실에서 열렸다. 이날 수상식에는 안병엽 정보통신부 장관을 비롯 한국데이터베이스 진흥센터의 이준우 전무이사 정보통신분야 주요 인사들이 대거 참석해 눈길을 끌었다. 이날 수상한 업체 및 수상한 컨텐츠를 살펴보면 다음과 같다. 디지털정보 및 웹케스팅 부문에서는 (주)코스모정보통신의 '사이버타운'과 (주)에듀원커뮤니케이션의 '라카데미'가 수상했다. 공익 및 교육용 콘텐츠 부문에는 (주)윈글리쉬닷컴의 '윈글리시'가 수상했으며, 온라인 및 네트워크게임 부문에는 (주)엔포에버의 '게임에버랜드'가 수상을 했다. 또한 디지털영상 부문에서는 (주)코리아인터미디어의 '예카'가 각각 수상했다.

• Proceedings of the Korea Multimedia Society Conference
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• 2002.05c
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• pp.16-21
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• 2002

현재의 웹은 신문, 잡지, 책 등의 온라인 출판뿐 아니라, 전자상거래, 금융, 가상 공동체, 마케팅, 광고 둥의 다양한 분야에서 실생활과 밀접하고, 기업에서도 웹 사이트가 제품 홍보 뿐 아니라 제품의 판매, 마케팅 등 매출에 막대한 영향을 미치는 중요한 위치를 차지하고 있다. 웹 사이트의 규모가 커지고 복잡해져감에 따라서 소수의 웹 디자이너들이 웹 사이트를 개발했던 것에서 개발에 필요한 인력과 그 역할을 나누게 되었고, 다른 제품처럼 납기를 위한 일정 관리가 필요하게 되었다. 그동안 웹 사이트 개발에 있어서 일련의 과정들에 대한 정형화되고 표준화된 작업 방법을 별로 적용하지는 않았다. 소프트웨어 공학을 그대로 웹 사이트 개발에 적용할 수는 없지만, 점차 웹 사이트가 소프트웨어 처럼 되어 가고 있고, 현재 웹 사이트 개발에 있어서 필요한 표준 개발 방법론이나 프로젝트 관리 둥을 소프트웨어 공학에서 적용시킬 수 있다. 본 논문에서 웹 사이트 개발에 있어서 더 나은 생산성과 품질을 얻기 위해 기획, 설계, 개발, 그래픽 디자인, 정보 설계, 컨텐츠, 테스트, 유지보수 등의 일련의 과정들을 프로세스화 하고, 구조적으로 접근하는 방법을 소프트웨어 공학의 표준 개발 방법론이나 프로젝트 관리, 품질관리 등에 관한 연구와, 실제로 이러한 방법론을 적용한 웹 서버을 구축하였다.

• Korean journal of communication and information
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• v.42
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• pp.79-106
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• 2008

Based on the third-person effect hypothesis, this study conducted a nation-wide online survey to assess how Korean voters perceived the mass media's effect on the candidates' image and voting behavior during the 17th presidential election. The research results showed that the voters tended to perceive that the mass media such as newspaper, television and the Internet had a greater effect on others than on themselves with regards to the formation of the three candidates' images. The third-person effect on the voting behavior was also revealed differently in terms of the medium according to age and political tendency of the voters. For instance, the younger and liberal voters were likely to see newspaper as having a greater influence on other voters' choice of candidate, while the older voters saw TV as having a greater effect on other voters. The conservative tendency did not affect the perception of the voters at all. Another noteworthy result was that personal characteristics of the candidates' images such as appearances and communication skills did not affect the voters' behaviors in the election process.