• Journal of Creative Information Culture
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• v.5 no.3
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• pp.215-223
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• 2019

The wave of the information age gradually accelerates, and fusion analysis solutions that can utilize these knowledge data according to accumulation of various forms of big data such as large capacity texts, sounds, movies and the like are increasing, Reduction in the cost of storing data accordingly, development of social network service (SNS), etc. resulted in quantitative qualitative expansion of data. Such a situation makes possible utilization of data which was not trying to be existing, and the potential value and influence of the data are increasing. Research is being actively made to present future-oriented education systems by applying these fusion analysis systems to the improvement of the educational system. In this research, we conducted a big data analysis on Twitter, analyzed the natural language of the data and frequency analysis of the word, quantitative measure of how domestic windows education problems and outcomes were done in it as a solution.

• Proceedings of the Korean Information Science Society Conference
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• 2012.06b
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• pp.291-293
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• 2012

SNS, 블로그의 이용이 늘어나면서, 문서의 복제와 재생산이 빈번하게 발생함에 따라 대용량 문서에서의 유사중복문서 검출이 큰 이슈로 제기되고 있다. 본 논문에서는 한국어 문서를 대상으로 이러한 문제를 해결하기 위해 품질을 유지하면서 신속하게 문서집합 중 유사중복문서를 검출하는 방법에 대해 제안한다. 제안하는 알고리즘에서는 문서를 대표하는 고빈도 Unigram Token을 활용하여 문서를 군집화함으로써 비교 대상을 최소화 하였다. 실험결과, 76만 문서에서 기존 방법 대비 평균 0.88의 Recall을 유지하면서도 중복을 검출하는데 있어서 십수초내에 처리가 가능함을 보였다. 향후 대용량 검색시스템 및 대용량 이미지, 동영상 유사중복 검출에도 활용할 수 있을 것으로 기대한다.

• The Bulletin of The Korean Astronomical Society
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• v.39 no.1
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• pp.89.2-89.2
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• 2014

정기적으로 발행되는 우주라이크 [WouldYouLike]의 간행물 홍보를 위해 가장 많은 사용자를 가진 소셜네트워크 서비스 (SNS) 페이스북을 이용한 천문우주학 대중화 활동에 대해 소개한다. 2012년 7월부터 페이스북 페이지를 운영하기 시작한 이후 현재까지 1만 2천여명의 팬을 가지게 되었고, 그곳에 올려지는 우주라이크의 게시글들은 평균적으로 약 4천명의 사람들에게 전달된다. 다양한 종류의 글, 그림, 사진 그리고 동영상등을 업로드하고 페이스북 사용자들의 반응을 살펴본결과 크게 세가지의 수요층이 존재하는 것을 알 수 있었다. 이번 발표를 통해 우주라이크 페이스북 페이지에서 지금까지 다루어졌던 컨텐츠들인 '이번주 천문학', '네모난 천문학' 그리고 '아름다운 천체사진 및 글귀' 등을 소개 및 분석하고 각각의 컨텐츠들이 가지고 있는 장단점에 대해서 논의한 후 SNS를 통한 천문우주학 대중화의 효과적인 개선책을 찾고자 한다.

• Proceedings of the Korean Society of Computer Information Conference
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• 2012.07a
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• pp.101-104
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• 2012

최근 소설 네트워크 서비스(Social Netwrok Services)를 활용한 소설 태깅 서비스에 대한 연구가 활발하게 진행 중이다. 특히 태그 기술을 이용한 협력적 태깅 시스템(collaborative tagging system)은 북마크, 문서, 사진, 동영상과 같은 웹 자원을 조직화하고 공유할 수 있는 수단으로 제공하고 있다. 그러나 광고 홍보 목적을 가진 스패머들은 콘텐츠와 관련 없는 태그를 달아 놓아 검색 키워드와 무관한 결과 값이 검색되어 웹 검색 서비스를 이용하는 사용자들에게 불편을 주고 있다. 따라서 본 연구에서는 콘텐츠와 태그의 연관성을 높이기 위해 태그에 일반 사용자가 유사도를 입력할 수 있는 추천 시스템을 적용하여 순위 조작 방지방법을 제안하였다.

• Proceedings of the Korean Society of Computer Information Conference
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• 2020.07a
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• pp.671-673
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• 2020

정보화 시대에 살고 있는 우리는 인터넷 영상 매체를 떼놓을 수 없다. 어린아이들은 스마트폰의 유튜브를 보며 꿈꾸고, 어른들은 자신의 SNS에 취미나 장기를 뽐내고 공유하며 더 넓고 다양한 세상을 경험해 나간다. 인터넷 방송도 마찬가지로 이토록 다양한 경험과 재미를 주지만 정작 이 부분에 대해서 조사해 본 적은 없었다. 본 논문에서는 플랫폼, 인기 스트리머의 각각의 특징 조사하고 신규 스트리머에게 플랫폼 병행을 제안한다.

• Journal of the Korea Society of Computer and Information
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• v.24 no.12
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• pp.201-207
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• 2019

In this paper, we propose an effective method to block illegal gambling advertisement on social media. With the increase of smartphone and internet usage, users can easily access various information while sharing information such as text and video with a large number of others. In addition, illegal sports gambling advertisements are also continue to be transmitted on SNS. To avoid most surveillance networks, users are easily exposed to illegal sports gambling advertisement images by including phrases in the images that indicate illegal sports gambling advertisements. In order to cope with these problems, we proposed a method to actively block illegal sports gambling advertisements in a way different from the conventional passive methods. In this paper, we select words frequently used for illegal sports gambling, classifies them into three groups according to their importance, calculate WF for each word using weighted formula by degree of relevance and frequency, and then sum the WF of the words in the image. Blocking, warning, and passing were determined by cv, the total of WF. Experimenting with the proposed method, 193 out of 200 experimental images were correctly judged with 96.5% accuracy, and even though 7 images were illegal sports gambling advertisements. Further research is needed to block 3.5% of illegal sports betting ads that cannot be blocked in the future.

• The Journal of the Korea Contents Association
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• v.13 no.12
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• pp.81-91
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• 2013

Social Media has been vitalized according to development of technology, it make the crowd-funding which have a form of new donation culture. The crowd-funding has been known as form that is supported for getting investments of ongoing or new project by much public in area of cultural art. Nowadays it receive attention from the movie content production. There are so many successful case such as , in abroad while it is hard to find distinct case in Korea' the movie content production market. Since the movie <26 years> informed public of 'the crowd-funding', recently was successfully complete first and second fund-raising and third fund-raising is in progress. It is upraised as a representative successful case.

• The Journal of the Korea Contents Association
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• v.13 no.4
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• pp.155-169
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• 2013

This research aims to consider the participatory behaviors and the relationship building of the Hong Kong Korean Wave fans on YouTube and to explores the effect of the behaviors in order to spread the Korean Wave. Furthermore, this research seek ways of developing the Korean Wave contents based on fan participation on YouTube. The research conducted both Focus Group Interview and three rounds of email interviews with the Korean Wave fans in Hong Kong. They actively participated in expressing themselves, replying to other comments, and providing video contents as a fan. Also, the fans delivered the YouTube video contents to other Social Network Services(SNS), including facebook, and online fan pages in order to build ties with friends and other the Korean Wave global fans in daily lives. Their YouTube participation contributes to creating two-way communication between the Korean Wave and its global fans by spreading and re-creating the Korean Wave contents.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.23 no.3
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• pp.193-198
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• 2023

We study a learner-customized lecture recommendation project using deep learning. Recommendation systems can be easily found on the web and apps, and examples using this feature include recommending feature videos by clicking users and advertising items in areas of interest to users on SNS. In this study, the sentence similarity Word2Vec was mainly used to filter twice, and the course was recommended through the Surprise library. With this system, it provides users with the desired classification of course data conveniently and conveniently. Surprise Library is a Python scikit-learn-based library that is conveniently used in recommendation systems. By analyzing the data, the system is implemented at a high speed, and deeper learning is used to implement more precise results through course steps. When a user enters a keyword of interest, similarity between the keyword and the course title is executed, and similarity with the extracted video data and voice text is executed, and the highest ranking video data is recommended through the Surprise Library.

• The Journal of the Korea Contents Association
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• v.13 no.3
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• pp.32-42
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• 2013

As the smartphone market grows, the needs for its new business model are also increased. However, most previous researches on smartphone applications focused on Technology Acceptance Model(TAM) and Rogers' Diffusion of Innovation Theory so that there was lack of researches on characteristics for actual smartphone users. In this research, we divided the smartphone applications into five category functions (Call & Text/Music & Video/Information Search/Game/Social Network Service (SNS)). We analyzed characteristic differences of users who used the each application category and found that the differences were statistically significant in both demographic and smartphone usage characteristics (frequency of downloading applications, and download experience of paid applications). Additionally, the smartphone usage characteristic is closely related to the usage duration. The representative result is that the characteristics of people used Music & Video function actively were women in their 20s who downloaded applications more than three times per week, and had a download experience of paid applications. It is positive result for players in the application markets, because it means the users are willing to pay for downloading the paid applications. However, large companies already occupied most of the market share in music applications so that small and medium-sized players should develop an innovative and distinguishable business model in order to success. We believe this research result would provide significant implications for the players in planning the successful business model and developing an user-specific application product.