• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2008.04a
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• pp.190-193
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• 2008

사용자의 '참여'를 지향하는 웹2.0 서비스들은 사람간이나 정보간의 '관계'에 대한 문제에 주목하고 있다. 대표적인 서비스인 블로그는 엮인글을 통해 사용자들의 참여를 이끌고 문서를 연결하고 있으나 이를 악용하는 사례들이 발생하고 있어 이에 대한 해결을 위해 연결에 대한 분석이 요구되고 있다. 사람의 개인 정보와 친구 관계 및 주변 사물과의 관계를 모델링하는 방식인 FOAF(Friend of a Friend)는 이러한 사회연결망 분석을 가능케 하는 수단으로써 연구되고 있다. FOAF는 단순화되고 이해하기 쉬운 용어를 사용하여, 복잡하고 이해하기 어려운 시맨틱 웹의 단점을 극복하기 위한 발판으로서 또한 주목 받고 있다. 본 연구에서는 여러 웹 사이트를 하나의 ID로 이용하기 위한 OpenID를 통해 FOAF에 정보 관리 능력을 부여하여 개인정보 유출 문제를 해결하기 위한 방안을 제시한다. 또한 실제 운영되는 관리 능력을 부여하여 개인정보 유출 문제를 해결하기 위한 방안을 제시한다. 또한 실제 운영되는 사회연결망 서비스의 분석을 통해 OpenID의 정보에 따라 자동으로 사회연결망 정보를 수집하는 성장형 FOAF 프레임워크를 설계하였으며, 쉬운 FOAF를 보급하기 위한 발판을 마련하였다.

• Proceedings of the Korea Information Processing Society Conference
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• 2010.11a
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• pp.58-61
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• 2010

최근 인터넷이 보편화되면서 검색에 대한 관심도가 높아지고 있다. 특히 사용자는 정확한 키워드의 입력 없이도 자신이 원하는 검색을 하고 싶어 한다. 그러한 욕구를 충족시키기 위해서 네이트의 '시맨틱', MSN의 'Bing' 등이 새로 제작되어 지고 있으며 네이버, google 등 대형 포털 사이트들도 검색분야에 투자를 아끼지 않고 있다. 본 논문은 사용자중심의 검색을 구현하기 위해서 패턴을 분석하여 연관규칙을 사용하여 검색시간을 단축함을 물론 검색결과의 정확성을 높였다. 구현을 위해서 네이버 사이트의 블로그로 검색의 범위를 한정 하여 데이터를 분석, 관리 및 시각화 하는 사이트를 개발하였다. 또한 검색을 위한 크롤러, 루씬 등을 실질적으로 직접 개발 활용 하였다. 시제품의 시험결과 정답사이트 도출 정확도는 google에 비해 20%, 재현율은 7.2%의 향상성을 보였다.

• 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 the Korean Society for information Management
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• v.27 no.3
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• pp.35-51
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• 2010

Emerging Web 2.0 services such as Twitter, Blogs, and Wikis alongside the poorlystructured and immeasurable growth of information requires an enhanced information organization approach. Ontology has received much attention over the last 10 years as an emerging approach for enhancing information organization. However, there is little penetration into current systems. The purpose of this study is to propose ontology implementation and methodology. To achieve the goal of this study, limitations of traditional information organization approaches are addressed and emerging information organization approaches are presented. Two ontology data models, RDF/OW and Topic Maps, are compared and then ontology development processes and methodology with topic maps based medical information retrieval system are addressed. The comparison of two data models allows users to choose the right model for ontology development.

• Journal of Korea Multimedia Society
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• v.13 no.5
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• pp.730-739
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• 2010

One of core technology in Web 2.0 is tagging, which is applied to multimedia data such as web document of blog, image and video etc widely. But unlike expectation that the tags will be reused in information retrieval and then maximize the retrieval efficiency, unacceptable retrieval results appear owing to toot limitation of tag. In this paper, in the base of preceding research about image retrieval through tag clustering, we design and implement a topic map generation system which is a semantic knowledge system. Finally, tag information in cluster were generated automatically with topics of topic map. The generated topics of topic map are endowed with mean relationship by use of WordNet. Also the topics are endowed with occurrence information suitable for topic pair, and then a topic map with semantic knowledge system can be generated. As the result, the topic map preposed in this paper can be used in not only user's information retrieval demand with semantic navigation but alse convenient and abundant information service.

• The Journal of Society for e-Business Studies
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• v.17 no.4
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• pp.69-93
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• 2012

Various influence-related relationships in Social Network Services (SNS) among users, posts, and user-and-post, can be expressed using links. The current research evaluates the influence of specific users or posts by analyzing the link structure of relevant social network graphs to identify influential users. We applied the concept of mutual interactions proposed for ranking semantic web resources, rather than the voting notion of Page Rank or HITS, to blogosphere, one of the early SNS. Through many experiments with network models, where the performance and validity of each alternative approach can be analyzed, we showed the applicability and strengths of our approach. The weight tuning processes for the links of these network models enabled us to control the experiment errors form the link weight differences and compare the implementation easiness of alternatives. An additional example of how to enter the content scores of commercial or spam posts into the graph-based method is suggested on a small network model as well. This research, as a starting point of the study on identifying influential users in SNS, is distinctive from the previous researches in the following points. First, various influence-related properties that are deemed important but are disregarded, such as scraping, commenting, subscribing to RSS feeds, and trusting friends, can be considered simultaneously. Second, the framework reflects the general phenomenon where objects interacting with more influential objects increase their influence. Third, regarding the extent to which a bloggers causes other bloggers to act after him or her as the most important factor of influence, we treated sequential referencing relationships with a viewpoint from that of PageRank or HITS (Hypertext Induced Topic Selection).