• Journal of The Korean Association of Information Education
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• v.9 no.2
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• pp.177-185
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• 2005

The latest BLOG is highlighted both freely writing about the personal life and the tool which is maintaining friendly relations with many people by trackback. In this study, this BLOG system is designed for improving self-esteem in the class by using these characteristic of BLOG. the internet activity of students and their normal activity in the classroom connects with The Star-Gift-Shop module. This module induces students to an active BLOG, activity with interest. as a result of this activity in the class BLOG system, students improves their computer application ability and confidence of them. Which is effected teacher's efficient classroom management.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2010.05a
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• pp.905-908
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• 2010

Our purpose is to develope the system which detects splogs automatically among blogs on Web environment. After removing HTML of blogs, they are tagged by part of speech(POS) tagger. Words and their POS tags information is used as a feature type. Among features, we select useful features with $x^2$ statistics and train the SVM with the selected features. Our system acquired 90.5% of F1 measure with SPLOG data set.

• Proceedings of the Korea Information Processing Society Conference
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• 2008.05a
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• pp.239-242
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• 2008

블로그 환경에서의 중복문서는 블로그 검색 서비스 성능의 저하를 초래한다. 기존의 웹 페이지 환경에서와는 달리 블로그 환경에서는 문서의 생성 시점을 알 수 있어 원본 문서와 중복문서를 쉽게 파악 할 수 있다는 특징이 있다. 본 논문에서는 이 점에 착안하여 문서를 저장하는 시점에 중복 여부를 판정함으로써 검색 결과에 중복문서가 반영되는 것을 원천적으로 방지할 수 있는 효과적인 중복문서 핸들링 프레임워크를 제안한다. 또한, 성능 평가를 통해 제안하는 프레임워크의 우수성을 보인다.

• Journal of the Korea Society of Computer and Information
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• v.16 no.1
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• pp.19-29
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• 2011

As people have heightened attention to blogs that are individual media, a variety rank algorithms was proposed for the blog search. These algorithms was modified for structural features of blogs that differ from typical web sites, and measured blogs' reputations or popularities based on the interaction results like links, comments or trackbacks and reflected in the search system. But actual blog search systems use not only blog-ranks but also search words, a time factor and so on. Nevertheless, those might not produce desirable results. In this paper, we suggest a topic-rank technique, which can find blogs that have significant degrees of association with topics. This technique is a method which ranks the relations between blogs and indexed words of blog posts as well as the topics representing blog posts. The blog rankings of correlations with search words are can be effectively computed in the blog retrieval by the proposed technique. After comparing precisions and coverage ratios of our blog retrieval system which applis our proposed topic-rank technique, we know that the performance of the blog retrieval system using topic-rank technique is more effective than others.

• The KIPS Transactions:PartD
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• v.16D no.5
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• pp.817-824
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• 2009

In recent years, Weblog has become the most typical social media for citizens to share their opinions. And, many Weblogs reflect several social issues. There are many internet users who actively express their opinions for internet news or Weblog articles through the replying comments on online community. Hence, we can easily find internet blogs including more than 10 thousand replying comments. It is hard to search and explore useful messages on weblogs since most of weblog systems show articles and their comments to the form of sequential list. In this paper, we propose a visualizing and clustering system called TRIB (Telescope for Responding comments for Internet Blog) for a large set of responding comments for a Weblog article. TRIB clusters and visualizes the replying comments considering their contents using pre-defined user dictionary. Also, TRIB provides various personalized views considering the interests of users. To show the usefulness of TRIB, we conducted some experiments, concerning the clustering and visualizing capabilities of TRIB, with articles that have more than 1,000 comments.

• The Journal of Korean Institute for Practical Engineering Education
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• v.1 no.1
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• pp.7-12
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• 2009

The worldwide spread of the internet has made it an important topic in our everyday lives. It has not only changed ordinary lives, but also the whole spectrum of modern society. Thus, it is necessary to understand the characteristic changes in learners as well as social demand in this drastic transformation period and to modify the goal and methods of learning to nurture future intellects. To achieve this, there have been recent attempts to invent new learning methods involving Web 2.0, which focuses on the user. Out of the various aspects of Web 2.0, the blog is expected to invoke learner-oriented education and active discussions between learners, in that the individual manages the blog autonomously and there is much interaction between users. This study will construct a learning system using the blog, apply it on real learners, and analyze its effect on the learners' scholastic achievements, interests, and learning transfer.

• Korean Journal of Construction Engineering and Management
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• v.10 no.5
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• pp.47-56
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• 2009

As contemporary society becomes information-oriented, major construction companies have recently invested in information management, but small and medium ones have not. Though the small and medium companies recognize the information management is necessary and important, they don't have an ability to possess technical expertises. The purpose of this study is to develop a Schedule Risk Control System based on blogs using IT and web technologies for construction managers in small and medium construction companies. The system makes a chance to identify risk factors and prepare for responses to settle risks happened in preconstruction phases, and enables the managers and headquarters to predict and handle schedule risks by sharing information about risks on the blogs.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.19 no.11
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• pp.730-737
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• 2018

With the increasing number of health consumers aiming for a happy quality of life, the O2O medical marketing market is activated by choosing reliable health care facilities and receiving high quality medical services based on the medical information distributed on web's blog. Because unstructured text data used on the Internet, mobile, and social networks directly or indirectly reflects authors' interests, preferences, and expectations in addition to their expertise, it is difficult to guarantee credibility of medical information. In this study, we propose a blog reading system that provides users with a higher quality medical information service by classifying medical information blogs (medical blog, ad blog) using bigdata and MLP processing. We collect and analyze many domestic medical information blogs on the Internet based on the proposed big data and machine learning technology, and develop a personalized health information recommendation system for each disease. It is expected that the user will be able to maintain his / her health condition by continuously checking his / her health problems and taking the most appropriate measures.

• 한국경영정보학회:학술대회논문집
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• 2007.11a
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• pp.402-407
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• 2007

웹2.0이라는 개념과 트랜드는, 개방성, 사용자 참여, 집단 지성, 인간중심의 IT 서비스 등을 키워드로 하는, 플랫폼 기반 비즈니스 모델을 통칭한다. 전세계적 블로그 열풍이나, Googlization으로 불리기도하는 주요 웹포탈의 성장은 이러한 현상을 뒷받침하는 증거이며, 미래 인터넷 시장을 개척하는 엔진으로 자리잡고 있다. 그런데 웹2.0을 기술적으로(descriptive) 소개하거나 관련된 요소기술에 대한 문헌은 많음에도 불구하고, 이러한 현상을 경영/경제학적 시각에서 체계적으로 분석한 연구는 의외로 많지 않다. 본 논문에서는 기존의 웹(웹1.0)과 웹2.0 서비스 모형을 경영 경제학적 관점에서 구조화하고, 이들 서비스 모형을 Stakelberg 게임의 관점에서 분석한다. 특히 본 연구에서는 웹2.0의 다양한 국면 중에서 프로슈밍(prosuming)에 초점을 맞춘다. 분석 결과, 웹2.0에서 사용자 후생이 웹1.0에 비해 크게 증가한다는 것을 확인할 수 있었다. 또한 사용자 스스로 맞춤화된 정보를 창출하는 노력과 한계편익간의 비율을 나타내는 ${\delta}_c$('고객화 요소'로 부름) 분포의 범위(파라미터 ${\delta}$)가 사회후생에 중요한 역할을 함을 발견하였다. 이는 고객화 요구의 다양성이 커짐에 따라 사용자 후생을 비롯한 사회후생도 증진됨을 의미한다.

• The Journal of the Korea Contents Association
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• v.10 no.8
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• pp.38-50
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• 2010

In recent years, the number of users who are actively express their opinions about Internet articles is more and more growing up, as the use of cyber community such as weblog or Internet discussion board increases. In fact, it is not difficult to find an article with hundreds of comments in famous Internet discussion boards. Most of the weblogs or Internet discussion boards present comments in the form of list and do not yet support even the basic operation such as searching comments. In this paper, we analysed large sets of comments in Internet discussion board named AGORA. It was found that from the result that the distribution of comment writers follows power-law. So we suppose a new search structure of comments using skip lists. The main idea of our approach is to reflect the probabilistic distribution properties of the commenters following the power-law to the data structure. Our empirical results show that the proposed method performs more efficient in searching the nodes with fewer number of comparison operations than logN, which is the theoretical time complexity of general indexed structure such as B-trees or typical skip lists.