• Proceedings of the Korea Information Processing Society Conference
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• 2008.11a
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• pp.283-285
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• 2008

블로그 월드에는 동일한 주제와 관련된 포스트들에 공통적으로 관심을 보이는 블로거들이 존재한다. 본 논문에서는 이러한 블로거들의 집합을 블로그 커뮤니티(blog community)라 정의한다. 블로그 커뮤니티는 타겟 마케팅, 양질의 정보 공유, 블로그 월드의 활성화 등 다양한 블로그 비즈니스 정책을 수립하는데 활용될 수 있다. 그러나 블로그 커뮤니티는 카페 등과 달리 멤버쉽으로 운영되는 집단이 아니기 때문에 커뮤니티에 속하는 멤버를 쉽게 파악할 수 없다. 본 논문에서는 주어진 주제와 관련된 블로그 커뮤니티를 추출하는 효과적인 방법을 제안한다. 먼저, 주어진 주제에 대한 시드 포스트들을 선택하고, 이 시드 포스트들을 통해서 주제와 관련된 블로거들을 선택한다. 다음으로, 선택된 블로거들을 통해서 주제와 관련된 포스트들을 선택한다. 위와 같은 과정을 반복해 나가면서 블로그 월드에 존재하는 주어진 주제와 관련된 모든 블로거들을 선발한다. 실제 블로그 데이터를 이용한 실험을 통하여 제안하는 방법의 우수성을 검증하였다.

• Journal of KIISE:Databases
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• v.37 no.1
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• pp.56-69
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• 2010

In blogspace, there are posts that deal with a common topic and bloggers that are interested in these posts. In this paper, we define a blog community as a group of these bloggers and posts. With a blog community, we can establish various business policies for target marketing, sharing high quality data, and mobilizing the activities in the blogspace. Unlike internet cafes, bloggers participate in blog communities without explicit membership. So, it is not easy to identify the members of a community. In this paper, we propose an effective approach for extracting a blog community that is related to a given topic. First, we choose seed posts that is highly related to a given topic, and select bloggers that are related to the topic with the seed posts. Then, we select posts that are related to the topic with the selected bloggers. By repeating this, we find all the posts and bloggers that are members of the community related to a given topic in blogspace. We verify the superiority of the proposed approach by analyzing extracted blog communities.

• Journal of KIISE:Computing Practices and Letters
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• v.15 no.5
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• pp.385-389
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• 2009

As a new community forming environment, the blog platform enables sharing of the resources in blogosphere through active information exchange. Many researches have been performed to recommend appropriate resources to users from vast amounts of blog resources. As one of the solutions OSEM defines the knowledge base in the blogosphere with ontology for effectively modeling it. In this paper, we propose a technique of converting the knowledge base into the OWL ontology for sharing it on the semantic web environment. An inference method is then applied to the OWL ontology for recommending interest blog communities. For this aim, a mapping method is offered and then SWRL inference and SPARQL query based on the ontology are employed to extract interest blog communities.

• Proceedings of the Korea Information Processing Society Conference
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• 2014.11a
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• pp.845-848
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• 2014

블로그는 인터넷에서 개인의 정보나 의견을 표출하고 커뮤니티를 형성하는데 사용되는 중요한 수단이나, 광고 유치, 페이지 순위 올리기, 쓰레기 데이터 생성 등 다양한 목적을 가진 스팸블로그가 생성되어 악용되기도 한다. 본 연구에서는 이러한 문제를 해결하기 위해 웹 문서에서 나타나는 특징들을 이용한 스팸 탐지 기법을 제안한다. 먼저 블로그 본문의 길이, 태그의 비율, 태그 수, 이미지 수, 랭크의 수 등 하나의 웹 문서에서 추출할 수 있는 특징을 기반으로 각 문서에 대한 특징 벡터를 생성하고 기계학습을 통해 모델을 생성하여 스팸 블로그를 판별한다. 제안 방법의 성능 평가를 위해 블로그 포스트 데이터를 사용하여 제안방법과 기존의 스팸 분류 연구를 비교 실험을 진행하였다. Bayesian 필터링 기법을 사용하는 기존연구와 비교 실험 결과, 제안방법이 더 좋은 정확도를 가지면서 특징 추출 속도 및 메모리 사용 효율성을 보였다.

• Proceedings of the Korea Inteligent Information System Society Conference
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• 2007.11a
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• pp.343-352
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• 2007

최근 Web 2.0 발달과 더불어 블로그나 온라인 카페 등 웹 상의 사용자가 개인적인 정보를 자유롭게 개제할 수 있도록 하는 인터넷서비스가 증가하면서, 이 사용자들 간의 관계에 초점을 맞춘 소셜 네트워크 분양의 연구가 활발히 이루어지고 있다. 하지만 많은 소셜 네트워크 서비스가 정보자원을 컴퓨터가 처리할 수 있는 의미적인 정보로 표현하고 있지 않기 때문에 서로 다른 도메인 간에 공유와 재사용이 어렵고, 사회적 개체들 간의 관계가 명확하게 정의되어 있지 않아 소셜 네트워크 분석에 어려움이 있다. 본 논문에서는 가상 커뮤니티 사용자들이 업로드 한 사진 데이터를 이용한 시맨틱 웹 기반의 소셜 네트워크 분석 시스템을 제안한다. 온톨로지를 기반으로 사진에서 추출된 얼굴 개체와의 관계와 이미 인맥 관계를 형성하고 있는 사람들의 정보적 연결성을 명확하게 정의하고 도메인 규칙을 활용하여 의미 있는 사회적 연결 관계를 추론한다. 이를 그래프로 시각화하여 사용자에게 제공함으로써 온라인 상에서 형성된 커뮤니티 내에서 효율적인 소셜 네트워크 분석을 도모하고 이를 기반으로 다양한 응용 분야에 활용하는 방법을 모색한다.

• Spatial Information Research
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• v.20 no.2
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• pp.129-136
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• 2012

Recently international organizations such as ISO/TC211, OGC, INSPIRE (Infrastructure for Spatial Information in Europe) make an effort to share geospatial data using semantic web technologies. In addition, smart phone and social networking services enable community-based opportunities for participants to share issues of a social phenomenon based on geographic area, and many researchers try to find a method of extracting issues from that. However, serviceable spatial ontologies are still insufficient at application level, and studies of spatial information extraction from SNS were focused on user's location finding or geocoding by text mining. Therefore, a study of extracting spatial phenomenon from social media information and converting it into geosemantic knowledge is very usable. In this paper, we propose a framework for extracting keywords from micro-blog, one of the social media services, finding their relationships using data mining technique, and converting it into spatiotemopral knowledge. The result of this study could be used for implementing a related system as a procedure and ontology model for constructing geoseem antic issue. And from this, it is expected to improve the effectiveness of finding, publishing and analysing spatial issues.

• Journal of Korea Multimedia Society
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• v.9 no.10
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• pp.1332-1343
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• 2006

This paper proposes an educational community service system that manages information of good quality intensively without overlapping, and that provides an effective searching function by using a personal community with many user layers. This system raises the efficiency of searching and management by using Metadata and Category. It is a self-leading educational community system that brings merits into relief and improves weak points. We constructed an autogenous Blog chain service as a tool which verifies this system, which is called 'EduLOG(Educational Blog) service' Especially we extracted Metadata suitable for this service, which is on the basis of worldfamous Dublin Core Metadata. And we made a new category on the basis of categories which were proposed by some educational community sites and public educational authorities, and we applied it to this system. To ascertain whether this service system provide adequate function or not, we made a questionnaire on the basis of the appraisal table in websites, and evaluated it at the request of experts. In view of the results so far achieved, it returned good scores (above 3.5/5.0) in accuracy of evaluation, low-end reappearance ratio, easiness of registering and approaching information, and intensive management of a categorical information, confirming the efficiency of the ECSS system. Therefore we believe firmly that the ECSS system will play a efficient information storing and searching roles in the near future.

• Journal of Intelligence and Information Systems
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• v.15 no.1
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• pp.87-102
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• 2009

With the growth of Web 2.0, lots of services allow yours to post their personal information and useful knowledges on networked information spaces such as blogs and online communities etc. As the services are generalized, recent researches related to social network have gained momentum. However, most social network services do not support machine-processable semantic knowledge, so that the information cannot be shared and reused between different domains. Moreover, as explicit definitions of relationships between individual social entities do not be described, it is difficult to analyze social network for inferring unknown semantic relationships. To overcome these limitations, in this paper, we propose a social network analysis system with personal photographic data up-loaded by virtual community users. By using ontology, an informative connectivity between a face entity extracted from photo data and a person entity which already have social relationships was defined clearly and semantic social links were inferred with domain rules. Then the inferred links were provided to yours as a visualized graph. Based on the graph, more efficient social network analysis was achieved in online community.

• Journal of Digital Convergence
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• v.10 no.2
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• pp.255-267
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• 2012

High Internet usage and the public's keen interest on health have influenced the health care system, and a potential value of the online health information and medical consultation market is immense. This study reveals results from data collected from Seoul residents in the age group of 20s in 2011. Out of 499 respondents, 75.2% answered that they used online health information; however, only 7.2% answered that they have used online medical consultation services. Findings on the purposes of using online medical consultation included treatments of symptoms(33.6%) and self-disciplines of one's health(19.5%). Mostly used Websites for health information search included search engines and blogs, but respondents preferred to use government sites and hospital sites in the future. When choosing a medical consultation, respondents preferred a certain website for different reasons including creditability of the consultant(23.7%), creditability of the organization(23.7%), rapid responses(21.2%), and more. Overall, although health information search via web is being highly utilized among people in their 20s, utilization of online medical consulting is not. Thus, promotion efforts to increase awareness and utilization of online medical consulting based on the site selection criteria, type of personal information disclosure, and other preferences are essential. Also, creating websites meeting these criteria is important.