• Journal of KIISE:Software and Applications
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• v.36 no.8
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• pp.673-682
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• 2009

Recently, photo sharing and publishing based Social Network Sites(SNSs) are increasingly attracting the attention of academic and industry researches. Unlike the face recognition environment addressed by existing works, face annotation problem under SNSs is differentiated in terms of daily updated images database, a limited number of training set and millions of users. Thus, conventional approach may not deal with these problems. In this paper, we proposed a face annotation method for sharing and publishing photographs that contain faces under a social network service using random projection, non-linear regression and representational state transfer. Our experiments on several databases show that the proposed method records an almost constant execution time with comparable accuracy of the PCA-SVM classifier.

• 한국벤처창업학회:학술대회논문집
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• 2017.04a
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• pp.46-46
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• 2017

최근 경기 침체에 불구하고 피부관리에 아낌없이 투자하는 소비자들이 늘어나면서 가정용 안면피부미용기기 (뷰티디바이스) 열기가 거세다. 시간과 장소에 제약이 없이 가성비가 뛰어난 가정용 안면피부미용기기 시장은 지난해 약 1000억으로 전년 대비 약 25%의 성장을 보이고 있으며 당분간 이 열기는 지속될 것이다. 본 연구는 이런 가정용 안면피부미용기기 시장이 이제 막 주목받고 있는 분야임에도 불구하고 연구된 바가 거의 없다. 라서 본 연구는 기업의 중요한 마케팅수단인 SNS의 구전 정보의 특성이 가정용 안면피부미용기기 (뷰티디바이스) 구매의도에 어떠한 영향을 미치는가를 분석하고 구매의도에 중요한 역할하는 소비자의 태도가 어떤 매개역할을 하지는 분석하여 성장해가고 있는 가정용 안면피부미용기기(뷰티디바이스) 창업기업의 마케팅 전략에 기여할 것으로 판단된다. 연구모형에 있어서 SNS의 구전정보의 특성으로는 구전정보의 방향성, 구전정보의 수량, 구전정보의 내용 품질, 구전정보의 유형 들로 독립변수를 설정하였고, 종속변수인 구매의도사이에 매개변수로서 소비자태도를 선정하였다. 서울지역 여성 소비자들 중에서 가정용 안면 피부 미용기기를 사용해 본 경험이 있는 조건부 불특정 다수를 대상으로 150개의 표본을 추출하였다. 분석 방법은 확인적 요인분석과 크론바하 알파 계수로 변수의 타당성, 신뢰성 분석을 하고 경로분석을 통하여 변수간 가설 검정을 분석중에 있다.

• Journal of KIISE
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• v.43 no.3
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• pp.380-388
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• 2016

Graph clustering is widely used to analyze a graph and identify the properties of a graph by generating clusters consisting of similar vertices. Recently, large graph data is generated in diverse applications such as Social Network Services (SNS), the World Wide Web (WWW), and telephone networks. Therefore, the importance of graph clustering algorithms that process large graph data efficiently becomes increased. In this paper, we propose an effective clustering algorithm which generates clusters for large graph data efficiently. Our proposed algorithm effectively estimates similarities between clusters in graph data using Min-Hash and constructs clusters according to the computed similarities. In our experiment with real-world data sets, we demonstrate the efficiency of our proposed algorithm by comparing with existing algorithms.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.17 no.6
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• pp.1432-1440
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• 2013

In spite of advantages to using internet, but there are many adverse effects. The most well-known negative effects include internet addiction, personal information infringement, copyright violation, spread of harmful information, cyber bullying, online fraud, hacking and virus distribution, and online prostitution. Until now, the government and public organization strived to prevent and reduce the negative effects but have faced limitations. In accordance with, one of the measures the solve the problems caused by internet is to strengthen the internet ethics education. This study aims to consider and analyze the negative effects of internet and provide measures to promote internet ethics education to prevent and reduce such effects.

• The Journal of Information Systems
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• v.28 no.4
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• pp.359-375
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• 2019

Purpose The purpose of this study is to investigate the nature of temporal non-use, namely, the type of temporal non-use and the dynamic relationships between temporary non-use and use by expanding the model of dynamic state transition of non-use which is proposed by the previous study. Design/methodology/approach This study adopted grounded theory methodology as a research methodology. Fifteen university students were interviewed for open coding and for selected coding which leads the research model ten students were interviewed. Findings Based on the coding, the types of use were divided into interactive use and one-way use, and the types of temporal use were classified into temporal non-use in which use is intended and temporal non-use in which use is not intended. The dynamic transition model is presented for each type of use and temporalnon-use, and an integrated model that combines them is presented. This study found the following four things: First, all non-use can be temporal Second, there are different types of temporal non-use. Third, the pattern of use is not just one, but new patterns will continue to emerge. Fourth, we found a change in the function of SNS.

• Journal of Digital Contents Society
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• v.15 no.3
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• pp.387-393
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• 2014

This study investigates the worlds most favorite SNS, the Facebook, with the theory of Empathy, that there will be an effect to users due to their characteristics. We approach the data scientifically with using an Eye tracker, by analyzing the vision and attention of users of Facebook with stimuli of whether it's an image or text filled contents in newsfeed of Facebook. With the result of an eye tracker, we cross analyzed with General Empathy Scale to compare that users limit of feeling of empathy gave effect on contents of Facebook. Discussion and implications are discussed in terms of empathy.

• Journal of Information Technology Services
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• v.13 no.3
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• pp.235-255
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• 2014

Social Network Service (SNS) with emergence of Web 2.0 have been developed rapidly. Unlike other games, social network game is based on the relationship with smart devices and studied for user-centered behavior as a potential factor derived from the Technical Acceptance Model (TAM). This research is conducted for finding out influencing factors on continuous intention for smart device users. Therefore, the independent variables consist of subjective norm, mobility, playfulness, self-efficacy, and ease of use. The intermediate variables also compose of flow, and user satisfaction and the dependent variables as continuous intention. The result of study shows the following: First, subjective norm, playfulness, self-efficacy and ease of use except mobility have the positive effect on user flow. Second, subjective norm, mobility, playfulness and ease of use except self-efficacy have significantly the positive effect on user satisfaction. Finally, user flow has significantly the positive effect on user satisfaction and continuance intention and a factor of user satisfaction have significantly the positive effect on continuance intention.

• Journal of Biomedical Engineering Research
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• v.34 no.1
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• pp.1-7
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• 2013

According to the frequent use of mobile devices, risk of repetitive strain injury for the finger joints was increasing recently. The purpose of this study was to investigate the difference of muscular endurance limit of the thumb between adults and children. A total of thirty subjects (15 adults: $41.0{\pm}7.9$ years and 15 children: $9.5{\pm}2.7$ years) was recruited for this experiment. Maximum voluntary contraction (MVC) of the thumb was measured for 100 trials for each subject by using a push-pull gauge. From the maximum peak value obtained, three main factors (MVC, endurance limit, and fatigue index) were defined to quantify fatigue characteristics of the thumb flexor muscle. The experimental results showed that the mean of MVC, endurance limit, and fatigue index of the children were approximately 50% compared to the adults (p < 0.001). From the results of Pearson correlation test, the endurance limit was highly correlated with weight, age, hand length rather than height. Based on this study, children are more vulnerable to repetitive task using the thumb such as text/SNS messaging, gaming, and scrolling.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.13 no.4
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• pp.117-126
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• 2013

Recently, as Social Network Services(SNS), such as Twitter, Facebook, are becoming more popular, much research has been doing on opinion mining. However, current related researches are mostly focused on sentiment classification or feature selection, but there were few studies about opinion document retrieval. In this paper, we propose a new retrieval method of short opinion documents. Proposed method utilizes previous sentiment classification methodology, and applies several features of documents for evaluating the quality of the opinion documents. For generating the retrieval model, we adopt Learning-to-rank technique and integrate sentiment classification model to Learning-to-rank. Experimental results show that proposed method can be applied successfully in opinion search.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.28 no.1
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• pp.241-248
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• 2018

A Recommender System (RS) is a system that provides optimized information to users in an over-supply situation. The key to RS is to accurately predict the behavior of the user. The Matrix Factorization (MF) method was used for this prediction in the early stage, and according to the recent SNS development, social information is additionally utilized to improve prediction accuracy. In this paper, we use RS internal trust cluster, which was overlooked in previous studies, to further improve performance and analyze the characteristics of trust clusters.