• 한국정보통신학회논문지
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• 제25권4호
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• pp.537-542
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• 2021

스마트 TV는 인터넷을 기반으로 기존의 TV에 비해 다양한 서비스와 정보를 제공하고 있다. 보다 개인화된 서비스나 정보를 제공하기 위해서는 사용자의 시청 패턴을 분석하고 이를 기반으로 맞춤형 서비스나 정보를 제공해야한다. 제안하는 시스템은 사용자의 TV 시청 패턴을 입력받고 이를 분석하여 사용자에게 맞춤형 정보로써 TV 프로그램이나 영화를 추천한다. 이를 위해 전처리기와 딥러닝(deep learning) 모델로 시스템을 구성하였다. 전처리기는 사용자가 시청한 TV 프로그램의 이름과 해당 TV 프로그램을 시청한 날짜, 시청한 시간 등을 입력하면 이를 정제한다. 그리고 정제된 데이터를 다중속성 LSTM 모델이 학습하고 예측을 수행하게 된다. 제안하는 시스템은 사용자에게 맞춤형 정보를 제공하는 시스템으로써 기존의 IoT 기술과 딥러닝 기술을 융합한 디지털 컨버전스(convergence)의 선도 기술이 될 것으로 사료된다.

• 한국디지털정책학회:학술대회논문집
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• 한국디지털정책학회 2004년도 International Conference on Digital Policy & Management
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• pp.283-294
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• 2004

Within the rapidly changing environment of global economics, the environment of higher education in the universities & companies, also, has been, encountering various changes. Popularization on higher education related to lifetime education system, putting emphasis on the productivity of education services and the acquisition of competitiveness through the market of open education, the breakdown of the ivory tower and the Multiversitization of universities & companies, importance of obtaining information in the universities & companies, and cooperation between domestic and oversea universities, industry and educational system must be acquired. Therefore, in order to adequately cope with these kinds of rapid changes in the education environment, operating E-Learning Education & company by utilizing various information technologies and its fixations such as Internet, E-mail. CD-ROMs. Interactive Video Networks (Video Conferencing, Video on Demand), CableTV etc., which has no time or location limitation, is needed.

• 전자통신동향분석
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• 제34권6호
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• pp.71-86
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• 2019

The unprecedented demands of mobile communication networks by the rapid rising popularity of mobile applications and services require future networks to support the exploding mobile traffic volumes, the real time extraction of fine-rained analytics, and the agile management of network resources, so as to maximize user experience. To fulfill these needs, research on the use of emerging deep learning techniques in future mobile systems has recently emerged; as such, this study deals with deep learning based mobile communication research activities. A thorough survey of the literature, conference, and workshops on deep learning for mobile communication networks is conducted. Finally, concluding remarks describe the major future research directions in this field.

• Journal of Information Processing Systems
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• 제15권5호
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• pp.1119-1130
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• 2019

With the wide spread of Social Network Services (SNS), fake news-which is a way of disguising false information as legitimate media-has become a big social issue. This paper proposes a deep learning architecture for detecting fake news that is written in Korean. Previous works proposed appropriate fake news detection models for English, but Korean has two issues that cannot apply existing models: Korean can be expressed in shorter sentences than English even with the same meaning; therefore, it is difficult to operate a deep neural network because of the feature scarcity for deep learning. Difficulty in semantic analysis due to morpheme ambiguity. We worked to resolve these issues by implementing a system using various convolutional neural network-based deep learning architectures and "Fasttext" which is a word-embedding model learned by syllable unit. After training and testing its implementation, we could achieve meaningful accuracy for classification of the body and context discrepancies, but the accuracy was low for classification of the headline and body discrepancies.

• ETRI Journal
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• 제44권2호
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• pp.232-243
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• 2022

Changes in household composition and the residential environment have had a considerable impact on the features of postal delivery regions in recent years, resulting in a large increase in the overall workload of domestic postal delivery services. In this paper, we provide complex analysis results for postal delivery areas using various unsupervised learning approaches. First, we extract highly influential features using several feature-engineering methods. Then, using quantitative and qualitative cluster analyses, we find the distinctive traits and semantics of postal delivery zones. Unsupervised learning approaches are useful for successfully grouping postal service zones, according to our findings. Furthermore, by comparing a postal delivery region to other areas in the same group, workload balancing was achieved.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제17권1호
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• pp.16-30
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• 2023

The elderly population is increasing owing to a low fertility rate and an aging population. In addition, life expectancy is increasing, and the advancement of medicine has increased the importance of health to most people. Therefore, government and companies are developing and supporting smart healthcare, which is a health-related product or industry, and providing related services. Moreover, with the development of the Internet, many people are managing their health through online searches. The most convenient way to achieve such management is by consuming nutritional supplements or seasonal foods to prevent a nutrient deficiency. However, before implementing such methods, knowing the nutrient status of the individual is difficult, and even if a test method is developed, the cost of the test will be a burden. To solve this problem, we developed a questionnaire related to nutrient classification twice, based upon which an adaptive algorithm was designed. This algorithm was designed as a machine learning based algorithm for nutrient classification and its accuracy was much better than the other machine learning algorithm.

• 한국IT서비스학회지
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• 제15권3호
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• pp.147-155
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• 2016

According to rapid development of technology, web text is growing explosively and attracting many fields as substitution for survey. The user of Facebook is reaching up to 113 million people per month, Twitter is used in various institution or company as a behavioral analysis tool. However, many research has focused on meaning of the text itself. And there is a lack of study for text's creation subject. Therefore, this research consists of sex/age text classification with by using 20,187 Facebook users' posts that reveal the sex and age of the writer. This research utilized Convolution Neural Networks, a type of deep learning algorithms which came into the spotlight as a recent image classifier in web text analyzing. The following result assured with 92% of accuracy for possibility as a text classifier. Also, this research was minimizing the Korean morpheme analysis and it was conducted using a Korean web text to Authorship Attribution. Based on these feature, this study can develop users' multiple capacity such as web text management information resource for worker, non-grammatical analyzing system for researchers. Thus, this study proposes a new method for web text analysis.

• 한국IT서비스학회지
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• 제20권2호
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• pp.91-109
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• 2021

Recently, social and economic environment has been rapidly changed. In particular, the development of IT technology accelerated the introduction of databases, communication networks, information processing and analyzing systems, making the use of such information and communication technology an essential factor for corporate management innovation. This change also affected the accounting areas. The purpose of this study is to document changes in accounting areas due to the adoption of IT technologies in the era of technology and information, to define the required accounting professions in this era, and to present the efficient educational methodologies for training such accounting experts. An accounting expert suitable for the era of technology and information means an accounting profession not only with basic accounting knowledge, competence, independency, reliability, communication skills, and flexible interpersonal skills, but also with IT skills, data utilization and analysis skills, the understanding big data and artificial intelligence, and blockchain-based accounting information systems. In order to educate future accounting experts, the accounting curriculum should be reorganized to strengthen the IT capabilities, and it should provide a wide variety of learning opportunities. It is also important to provide a practical level of education through industry and academic cooperation. Distance learning, web-based learning, discussion-type classes, TBL, PBL, and flipped-learnings will be suitable for accounting education methodologies to foster future accounting experts. This study is meaningful because it can motivate to consider accounting educational system and curriculum to enhance IT capabilities.

• 경영정보학연구
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• 제12권2호
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• pp.25-45
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• 2010

오늘날 인터넷의 발전과 더불어, 대학 교육에 있어 e-러닝은 매우 중요한 교과목으로 자리를 잡게 되었다. 이에 따라 학교 당국에서는 보다 양질의 교육 컨텐츠 질 개발과 e-러닝을 수강하는 학생들의 e-러닝을 통한 만족도와 학습효과를 증대하기 위해 많은 노력을 하고 있다. 본 연구에서는 기술수용모델을 이용해 학생들의 e-러닝 수용에 대한 연구를 수행하였다. 특히, 온라인 환경에서의 신뢰는 기술수용에 있어 매우 중요한 영향을 미치는데, 본 연구에서는 학생들의 e-러닝 수용에 있어 신뢰 수준에 따른 e-러닝 수용 과정을 분석하였다. 본 연구 결과는 e-러닝에 대한 수용의 심도 깊은 이해를 통해 보다 좋은 e-러닝 시스템을 구현과 e-러닝 전략 개발에 유용한 시사점을 제시해 줄 것이다.

• International Journal of Knowledge Content Development & Technology
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• 제7권3호
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• pp.67-86
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• 2017

The emergence of smart devices such as smartphones (e.g., iPhone) and tablets (e.g., iPad) may enhance e-learning by increasing communication and collaborative learning outside the classroom. These devices also facilitate the use of online technologies such as Facebook. However, the adaptation of Learning Management System (LMS) services to mobile devices took longer than social networks or online tools such as Facebook and Twitter have already been long used via smartphone. The main purposes of this study are to explore students' skill levels of LMS (Moodle) and their knowledge of online tools or technologies and then examine if there is a correlation between smartphone use and using of online tools and Moodle in learning. The study conducted among 173 students in the Department of Information Studies (DIS) in Oman, using online survey. The study found that most students demonstrated high levels of accessing course/subject materials and regularly engaging with studies of using LMSs. YouTube, Wikipedia and Facebook were clearly recorded as the most popular sites among students while LinkedIn and Academia.edu were two online tools that had never been heard of by over half of the 142 participants. Emailing and searching are recorded the most popular online learning activities among students. The study concluded that students prefer to use smartphone for accessing these tools rather than using it to access LMSs, while a positive correlation was found between the use of these tools and smartphones, but there was no correlation between smartphones and using LMSs.