• 한국멀티미디어학회논문지
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• 제14권8호
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• pp.1061-1069
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• 2011

정보통신기술의 발달로 인터넷을 이용하는 패션/코디 쇼핑몰은 그 시장이 매년 큰 폭으로 증가하고 있다. 하지만, 자신의 신체나 패션스타일에 맞는 의류를 온라인 쇼핑몰에서 검색하는 것은 쉽지 않다. 본 논문은 여성 의류의 패션/코디 추천시스템에 대하여 특히, 개인의 신체적 특성에 가장 잘 맞추어진 의류 추천기능에 대하여 논한다. 또한, 계절별 유행에 대한 전문가의 추천도 고려할 수 있고, 자신의 좋아하는 의류스타일도 미리 등록해 둔 후에, 다양한 방법의 선택을 통하여 등록된 상품 중 자신이 원하는 최적의 상품을 추천받을 수 있도록 패션/코디 쇼핑몰에서의 추천방법을 제안하였다.

• 한국전자거래학회:학술대회논문집
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• 한국전자거래학회 2005년도 종합학술대회
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• pp.147-153
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• 2005

최근 인터넷 쇼핑몰에서 상품을 구매하는 고객들에게 편의성과 효율성을 제공하기 위하여 구매자들의 선호도나 가격에 맞는 상품을 추천해 주는 연구들이 활발하게 진행되고 있지만추천된 상품들의 구매시점에 관한 연구는 찾아보기 어렵다. 이에 본 논문에서는 인터넷 쇼핑몰의 적극적인 마케팅 일환으로 판매가격의 흐름을 시계열 패턴으로 분석하여 상품의 구매시점 정보를 제공하는 방안을 제안한다. 이를 위하여 과거의 판매 기록 데이터베이스에 있는 판매가격의 기준이 되는 패턴과 유사한 변화를 보이는 패턴을 정규화된 유사도로써 검색하고, 검색된 가격 패턴을 기준으로 미래의 가격 패턴의 변화를 분석하여, 미래 가격 패턴의 변화 폭에 따라 상품에 대한 구매시점을 제공한다.

• 한국HCI학회:학술대회논문집
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• 한국HCI학회 2007년도 학술대회 1부
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• pp.268-273
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• 2007

In this paper, we present effective methods for automatic music recommendation system which automatically recommend music by signal processing technology. Conventional music recommendation system use users’ music downloading pattern, but the method does not consider acoustic characteristics of music. Sometimes, similarities between music are used to find similar music for recommendation in some method. However, the feature used for calculating similarities is not highly related to music characteristics at the system. Thus, our proposed method use high-level music characteristics such as rhythm pattern, timbre characteristics, and the lyrics. In addition, our proposed method store features of music, which individuals queried, to recommend music based on individual taste. Experiments show the proposed method find similar music more effectively than a conventional method. The experimental results also show that the proposed method could be used for real-time application since the processing time for calculating similarities between music, and recommending music are fast enough to be applicable for commercial purpose.

• 대한예방한의학회지
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• 제26권3호
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• pp.49-58
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• 2022

Objectives : The purpose of this study is to analyze the factors affecting the intention of traffic accident patients, who had visited Korean medicine clinics for the purpose of treating traffic accidents, on revisiting and recommending those clinics to others. Methods : This study conducted the frequency analysis, Rao-scott chi-square test, and logistic regression analysis on 389 people, who answered that they had once visited Korean medicine clinics for treatment in traffic accidents, using data from the 2020 Korean Medicine Utilization and Herbal Medicine Consumption Survey. Results : As a result of the analyses, it was revealed that the significant influencing factors entailed marital status, job status, the attitude of medical staff, and access to the Korean medicine clinics, while only access to the Korean medicine clinics was a significant influencing factor for the intention to recommend to others. Especially, the intention of to revisit and to recommend in case of satisfying access to the Korean medicine clinics were 8.476 times and 6.784 times higher than when it is not the case. Conclusions : The results of this study reflect the characteristics of automobile insurance, and indicate that both further study and policy establishment on the operation of the automobile insurance system are required to ensure sufficient treatment for traffic accident patients.

• 가정과삶의질연구
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• 제22권5호
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• pp.345-355
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• 2004

The purpose of this study is to recommend the roles, Qualification, and fostering system of healthy families specialist. In 2003, 'Organic Law to Develop the healthy Families' was legislated. The law endows the responsibilities and duties of the government, local government, and families, in order to embody the healthy families. Also, this suggests appropriate ways to solve diverse families problems and identifies the necessities of establishing social policies to increase the well-being of family members. The enactment system of this law is to place 'Healthy Families Center' under the Prime Minister, and to foster 'healthy families specialist' who have professional knowledge and skills for strengthen diverse families. The major recommend are as follow. First, the roles of healthy families specialist are a practician, deliverer, and administrator to enact the law's philosophy and ideal. Secondly, to protect the competency of those, the qualification is restricted to university and the same level school graduate people, who majored in Home Economics, Social Work. and Women Studies. Finally. to foster and qualify this specialist. the Council of Healthy Families will be compound.

• 한국가스학회지
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• 제9권1호
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• pp.44-50
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• 2005

본 논문에서는 LNG저장탱크의 통압제어 안전관리 시스템에 대한 연구결과를 제시하고 있다. 통합제어 및 안전관리를 효과적으로 진행하기 위한 새로운 통합관리 시스템은 내부탱크로부터 유출되는 가스나 초저온 액체(LNG)에 의한 안전성과 누출문제를 제어하기 위해 온도, 압력, 진동과 같은 신호를 검지하고, 종합적으로 분석하여 시스템의 안전성을 확보할 수 있도록 개발된 것이다. 효율성과 안전성 향상측면에서 LNG저장탱크의 저장용량 증가경향과 최근에 발생된 저장탱크의 고장사례 고찰을 통하여, 기존의 측정장치와 안전장치는 개량되고, 새로운 기술개발이 필요하다는 것을 강조한다. 따라서 본 연구에서는 초대형 LNG저장탱크의 제어와 안전관리를 위해 새로이 개발된 통합제어 안전관리 시스템을 제시하고 있다. 이 시스템에서는 기존의 측정 및 안전장치에 대한 통합과 연계성 및 성능을 향상시키고, 특히 저장탱크 구조물의 변위량을 측정하여 안전성을 확보할 수 있도록 기능성을 새로이 추가하였다. 본 연구에서 개발된 통합제어 안전관리 시스템에 프로세스 통합관리 시스템(PIIS)을 연계하여 사용한다면, LNG 저장탱크의 안전성, 효율성, 생산성은 획기적으로 향상될 것이다.

• 한국정보처리학회:학술대회논문집
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• 한국정보처리학회 2006년도 춘계학술발표대회
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• pp.109-112
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• 2006

최근 대용량 추천시스템에 대한 필요성이 증가하고 있고, 특히 대규모 인터넷 쇼핑몰을 위한 개인화 추천 시스템 구조에 대한 관심이 높아지고 있다. 본 논문에서는 k-means 클러스터링과 순차 패턴 기법을 이용한 인터넷 쇼핑몰 상품 추천 시스템을 설계 및 구현한다. 사용자 정보의 일괄처리와 카테고리의 계층적 특성을 반영하면서 데이터 마이닝 기법을 활용하여 개인화된 추천 엔진을 대형 시스템에서 동작하도록 설계 하였다. 설계 구현한 시스템의 평가를 위해, 대형 쇼핑몰의 데이터를 이용하여 추천 예측 정확율(PRP: Predictive Recommend Precision), 추천 예측 재현율(PRR: Predictive Recommend Recall), 정확도 인수(PF1 : Predictive Factor One-measure)를 구하였다.

• 한국정보과학회:학술대회논문집
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• 한국정보과학회 2003년도 봄 학술발표논문집 Vol.30 No.1 (B)
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• pp.386-388
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• 2003

We are developing a web-based movie recommender system that catches and reasons with user profiles and ratings to recommend movies. In the paper, we outline the current status of our implementation with particular emphasis on the mechanisms used to provide effective recommendations. Social recommender systems collect ratings of items from many individuals and use nearest-neighbor techniques to make recommendations to a user. However, these methods only depend on the ratings and ignore other useful information. Our primary concern is to provide an approach that can recommend the movies based on not only the user ratings but also the significant amount of other information that is available about the nature of each items - such as cast list or movie genre. We experimentally evaluate our approach and compare them to conventional social filtering, which suggests merits to our approach.

• International Journal of Advanced Culture Technology
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• 제8권3호
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• pp.325-333
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• 2020

In the past, eating outside was usually the purpose of eating. However, it has recently expanded into a restaurant culture market. In particular, a dessert culture is being established where people can talk and enjoy. Each consumer has a different tendency to buy chocolate such as health, taste, and atmosphere. Therefore, it is time to recommend chocolate according to consumers' tendency to eat out. In this paper, we propose a chocolate recommendation application based on the tendency to eat out using data on social networks. To collect keyword-based chocolate information, Textom is used as a text mining big data analysis solution.Text mining analysis and related topics are extracted and modeled. Because to shorten the time to recommend chocolate to users. In addition, research on the propensity of eating out is based on prior research. Finally, it implements hybrid app base.

• 디지털산업정보학회논문지
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• 제6권2호
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• pp.1-9
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• 2010

The increasing popularity of mobile devices, such as cellular phones, smart phones, and PDAs, has fostered the need to recommend more effective information in ubiquitous environments. We propose the recommendation method for mobile contents service using contexts and prefetching in ubiquitous environment. The proposed method enables to find some relevant information to specific user's contexts and computing system contexts. The prefetching has been applied to recommend to user more effectively. Our proposed method makes more effective information recommendation. The proposed method is conceptually comprised of three main tasks. The first task is to build a prefetching zone based on user's current contexts. The second task is to extract candidate information for each user's contexts. The final task is prefetch the information considering mobile device's resource. We describe a new recommendation.