• 미술이론과 현장
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• 제5호
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• pp.7-24
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• 2007

The subject is connected with a structure named "The Symbolic" to Lacan, but he denied that the subject is explained simply as a fruit of language and "Other". From his point of view, passing through Subject, De-formation and Crack over it is designated as foundation of generation and creation rather than our destined defect. It should not be understood that subject of "The Real" is a concept of the subject free itself from restraint of "The Symbolic". However, this does not mean he asserts "Subject" is something incapable of being controlled by the unknown power. The problem is that this autonomous existence meets inside of it with something "more than one's own self" by "circulating around itself" like a permanent star. This is the indication of a "stranger in the middle of my privacy", or "extimit$\'{e}$", a coined-word by Lacan. Perhaps "Subject" is nothing more than the name of distance of object which is "too hot" to come close, and of this circulating movement. It's because of this object that the real subject stands against generalization and the subject can't be restored to any place in symbolic order-even though it is empty. The part which is told from Lacan's structural theory, that is to say, an importance to Lacan is that his Subject theory is not suggested or denied as a manual structure. On the contrary, it is a study of the relationship between the settled symbol that included in "real subject which is a unconscious one" and the symbolic subject hold- that is a metaphysical subject in general meaning. In Lacan's enlarged concept of subject beyond symbolic reality, it is noticeable that it gives justifiability to the union of a medium of different nature in artistic expression. We can recognize that the unconscious world is a living space which enables it to be a "condition of human being", not something dark under the surface of water through Magritte's(Rene Magritte, 1898~1967) surrealistic works. In other words, Magritte's art secures a core dimension of human nature through a mysterious gap of conscious and settled space. Magritte's drawings often evokes strange and unsettling feelings in people who view his paintings. This is because routine objects are found in "unsuitable" places from which we usually find them in our everyday lives. "Reality" in Magritte's paintings makes it aware that it is a strained field of concealment and disclosure basically between truths, and we can learn that his behavior to overturn to paint in-visible things is finally an effort to restore the "real subject" to the viewer's reality. In other words, such reversion arouses a nostalgic desire for the objects existing in their original appearance as they are - natural condition that our gaze had not been distorted yet by anamorphic stains. - and the state when we are conscious of them normally. Such desire offers an opportunity for us to get out of mental depression rather than operates to us as an abnormal crack. It's a successive process of effort to search for lost subject and Paradise Lost facing up to reality of subject human that is to be a subject of world and life are ousted from their place by structure and authority of culture.

• 지능정보연구
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• 제20권2호
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• pp.137-148
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• 2014

상품 검색시간의 단축과 쇼핑에 투입되는 노력의 감소 등, 온라인 쇼핑이 주는 장점에 대한 긍정적인 인식이 확산되면서 전자상거래(e-commerce)의 중요성이 부각되는 추세이다. 전자상거래 기업들은 고객확보를 위해 다양한 인터넷 고객관계 관리(eCRM) 활동을 전개하고 있는데, 개인화된 추천 서비스의 제공은 그 중 하나이다. 정확한 추천 시스템의 구축은 전자상거래 기업의 성과를 좌우하는 중요한 요소이기 때문에, 추천 서비스의 정확도를 높이기 위한 다양한 알고리즘들이 연구되어 왔다. 특히 협업필터링(collaborative filtering: CF)은 가장 성공적인 추천기법으로 알려져 있다. 그러나 고객이 상품을 구매한 과거의 전자상거래 기록을 바탕으로 미래의 추천을 하기 때문에 많은 단점들이 존재한다. 신규 고객의 경우 유사한 구매 성향을 가진 고객들을 찾기 어렵고 (Cold-Start problem), 상품 수에 비해 구매기록이 부족할 경우 상관관계를 도출할 데이터가 희박하게 되어(Sparsity) 추천성능이 떨어지게 된다. 취향이 독특한 사용자를 뜻하는 'Gray Sheep'에 의한 추천성능의 저하도 그 중 하나이다. 이러한 문제인식을 토대로, 본 연구에서는 소셜 네트워크 분석기법 (Social Network Analysis: SNA)과 협업필터링을 결합하여 데이터셋의 특이 취향 사용자 (Gray Sheep) 문제를 해소하는 방법을 제시한다. 취향이 독특한 고객들의 구매데이터를 소셜 네트워크 분석지표를 활용하여 전체 데이터에서 분리해낸다. 그리고 분리한 데이터와 나머지 데이터인 두 가지 데이터셋에 대하여 각기 다른 유사도 기법과 트레이닝 셋을 적용한다. 이러한 방법을 사용한 추천성능의 향상을 검증하기 위하여 미국 미네소타 대학 GroupLens 연구팀에 의해 수집된 무비렌즈 데이터(http://movielens.org)를 활용하였다. 검증결과, 일반적인 협업필터링 추천시스템에 비하여 이 기법을 활용한 협업필터링의 추천성능이 향상됨을 확인하였다.