• Journal of Digital Convergence
• /
• v.20 no.5
• /
• pp.499-512
• /
• 2022

The purpose of this study is to propose effective plans for Anyang municipal library to use online media in preparation for the post-covid-19 era. For this purpose, the main implications were summarized by analyzing the operation cases of 5 excellent libraries that received government awards in the libraries' operation evaluation in 2021. And based on the analysis, strategies that can help Anyang municipal library use online media to operate library effectively even after COVID-19 were derived. This study is meaningful in that it is an empirical study that summarizes the online media usage strategy of the Anyang municipal library in preparation for the post-COVID-19 era based on actual cases of excellent libraries in the COVID-19 period.

• Annual Conference on Human and Language Technology
• /
• 2023.10a
• /
• pp.525-530
• /
• 2023

최근 소셜 네트워크 서비스(SNS) 및 모바일 서비스가 증가함에 따라 사용자들은 다양한 종류의 위험에 직면하고 있다. 특히 온라인 그루밍과 온라인 루머 같은 위험은 한 개인의 삶을 완전히 망가뜨릴 수 있을 정도로 심각한 문제로 자리 잡았다. 그러나 많은 경우 이러한 위험들을 판단하는 시점은 사건이 일어난 이후이고, 주로 법적인 증거채택을 위한 위험성 판별이 대다수이다. 따라서 본 논문은 이러한 문제를 사전에 예방하는 것에 초점을 맞추었고, 계속적으로 발생하는 대화와 같은 event를 실시간으로 감지하고, 위험을 사전에 탐지할 수 있는 Real-Time Early Risk Detection(RERD) 문제를 정의하고자 한다. 온라인 그루밍과 루머를 실시간 조기 위험 감지(RERD) 문제로 정의하고 해당 데이터셋과 평가지표를 소개한다. 또한 RERD 문제를 정확하고 신속하게 해결할 수 있는 강화학습 기반 새로운 방법론인 RT-ERD 모델을 소개한다. 해당 방법론은 RERD 문제를 이루고 있는 온라인 그루밍, 루머 도메인에 대한 실험에서 각각 기존의 모델들을 뛰어넘는 state-of-the-art의 성능을 달성하였다.

• Proceedings of the Korea Contents Association Conference
• /
• 2014.11a
• /
• pp.223-224
• /
• 2014

최근 빅데이터 시대에 다가와서 소셜 네트워크 서비스(Social Network Service)가 중요한 정보 공유의 수단으로 발전함에 따라 그에 따른 예측분석, 동향분석, 이슈탐지 등이 증가하고 있으며, 콘텐츠 분야에서 빅데이터 기법 사례가 증가하는 추세이다. 모바일기기 보급이 빠르게 확산되면서 SNS 활성화와 함께 많은 양의 데이터가 증가하고 있으며, 인스타그램과 같은 해시태그 사용 가능 SNS 서비스에서 해시태그의 동시출현은 해시태그만의 연관성이 있음을 의미한다. 본 논문에서는 대상 SNS의 동시출현 해시태그를 분석하기 위해 발생되는 데이터를 가지고 현재 트렌드에 맞게 분석하여 정보를 제공하는 방법을 제시한다.

• Proceedings of the Korea Information Processing Society Conference
• /
• 2013.11a
• /
• pp.1042-1045
• /
• 2013

정보기술의 발달로 전 세계에서 발생하는 사건 사고들은 실시간으로 확인 가능하며 정보의 중요성은 더욱 더 중요해지고 있다. 이런 사회 현상에 맞춰 인적자원 솔루션에서도 빅 데이터 분석 기술을 이용하여 인적자원 의사결정에 도움을 주는 기술이 필요하게 되었다. 따라서 본 논문에서는 빅 데이터 분석 기술을 이용하여 인사채용과 관련된 데이터들을 추출하고 분석하여 구직자의 적성과 능력에 맞는 직업을 예측하는 시스템을 설계하였다. 구직자 및 이직을 원하고 있는 사람들이 소셜 네트워크 서비스를 이용하면서 사용하고 있는 특정 단어와 특정 단어의 언급 빈도의 데이터를 추출하고 추출 된 데이터는 통계를 내어 데이터의 특성에 맞게 분류하여 분류된 데이터는 연관된 속성에 의해 그룹화 한다. 그룹화 된 정보를 분석하여 구직자의 적성과 능력을 고려한 직업을 예측하는 정보로 도출하여 직업을 추천 할 수 있는 예측 시스템을 설계하였다.

• Journal of Digital Convergence
• /
• v.13 no.12
• /
• pp.179-185
• /
• 2015

Along with the recent advances of mobile internet technology, use of social network service(SNS) is very common among adolescents or college students in their daily lives. Although there have been a lot of studies on Internet addiction or mobile phone addiction, however, there were little research on SNS addiction so far. Scholars investigated somewhat broader and obscure phenomenon of Internet addiction. In this regard, the current study tried to examine factors which influence SNS addiction behavior. Unlike Internet addiction, there are positive influencing factors such socialization, enjoyment as well as problematic ones like loneliness. Data were collected from college students in Korea to examine how those factors influence addiction behavior and hypotheses were tested using the partial least square method. All three factors, socialization, enjoyment, and loneliness, were found to significantly influence SNS addiction and socialization was positively associated with enjoyment.

• The Journal of the Convergence on Culture Technology
• /
• v.7 no.3
• /
• pp.475-480
• /
• 2021

With the rapid development of mobile, cloud computing technology and social network services, we are in the flood of huge data and realize that these large-scale data contain very precious value and important information. Big data, however, have both latent useful value and critical risks, so, nowadays, a lot of researches and applications for big data has been executed actively in order to extract useful information from big data efficiently and make the most of the potential information effectively. At this moment, the data analysis technique that can extract precious information from big data efficiently is the most important step in big data computing process. In this study, we investigate various data analysis techniques that can extract the most useful information in big data computing process efficiently, compare pros and cons of those techniques, and propose proper data analysis method that can help us to find out the best solution of the big data analysis in the peculiar situation.

• Journal of Advanced Navigation Technology
• /
• v.20 no.1
• /
• pp.79-85
• /
• 2016

Network traffic is increased rapidly, due to mobile and social network, such as smartphones and facebook, in recent web environment. In this paper, we improved web response time of existing system using direct buffer of NIO and DMA. This solved the disadvantage of JAVA, such as CPU performance reduction due to the blocking of I/O, garbage collection of buffer. Key values circulated many data due to priority change put on a hash map operated easily and apply a priority modification algorithm. Large response data is separated and stored at a fast direct buffer and improved performance. This paper showed that the proposed method using NIO was much improved performance, in many test situations of cache hit and cache miss.

• Journal of the Korea Institute of Information and Communication Engineering
• /
• v.16 no.3
• /
• pp.499-510
• /
• 2012

An SNS(Social Network Service) is an online service that supports an effective way to share information over virtual communities. Recently, as SNSs such as Twitter, Facebook, and Me2day are getting bigger, the purposes of using popular SNSs are expanded to broadcastings, politics, marketings and so on. In this paper, we propose an API to integrate and manage open APIs for various SNSs, presenting a library as an implementation of the proposed API. Also, utilizing the developed library, a smartphone application is provided which supports integrated management of popular SNSs and personal schedules. Using the library, developers can reduce costs when they need to implement specific functions for managing various SNSs. With the developed application, we can read and write to/from the related SNSs on same screen, automatically reminding our schedule and sharing the schedule with friends over the SNSs.

• The Journal of the Korea Contents Association
• /
• v.13 no.9
• /
• pp.20-27
• /
• 2013

In recently years, with the growth of social media and the development of mobile devices, the data have been significantly increased. MapReduce is an emerging programming model that processes large amount of data. However, since MapReduce evenly places the data in the dedicated distributed computing environment, it is not suitable to the non-dedicated distributed computing environment. The data replacement algorithms were proposed for performance optimization of MapReduce in the non-dedicated distributed computing environments. However, they spend much time for date replacement and cause the network load for unnecessary data transmission. In this paper, we propose an efficient data replacement algorithm for the performance optimization of MapReduce in the non-dedicated distributed computing environments. The proposed scheme computes the ratio of data blocks in the nodes based on the node availability model and reduces the network load by transmitting the data blocks considering the data placement. Our experimental results show that the proposed scheme outperforms the existing scheme.

• Journal of Digital Convergence
• /
• v.12 no.4
• /
• pp.293-303
• /
• 2014

The mobile game market is fast growing after the Kakao game launched. Especially, the market is placed at the second highest by occupying 33.1% of the market. However, the rate of the total sales amount is only 6%, showing quite an imbalance between the market occupancy and the sales amount. This means that the profit-making models are not stabilized yet in the mobile game market. The absence of profit-making models can be ascertained by the relationship of DAU and sales ranking. There are several games which are ranked at DAU Top10 among Google free games, but not ranked at top 10 among sales amounts. On the other hand, there are several games which are low in DAU ranking but high in sales amount ranking. This result shows that there is no direct interrelation between the product attractiveness which users feel and the profit-making models in the market. This study compared the Google play free games which are ranked at top 10 in terms of DAU ranking and sales amount ranking to find out the factor which causes the imbalance between the DAU ranking and sales amount ranking. Based on this outcome, this study presents the reference point for the design of profit-making models on behalf of the manufacturers who wish to launch into the mobile game market in the future.