• 한국경영정보학회:학술대회논문집
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• 2008.06a
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• pp.153-170
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• 2008

Customers' needs change every moment. Profitability of stores can't be increased anymore with an existing standardized chain store management. Accordingly, a personalized store management tool needs through prediction of customers' preference. In this study, we propose a recommending procedure using dynamic customers' preference by analyzing the transaction database. We utilize self-organizing map algorithm and association rule mining which are applied to cluster the chain stores and explore purchase sequence of customers. We demonstrate that the proposed methodology makes an effect on recommendation of products in the market which is characterized by a fast fashion and a short product life cycle.

• Journal of the Korean Society of Clothing and Textiles
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• v.21 no.2
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• pp.302-313
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• 1997

The purpose of this study was to investigate the meaning structure of Korean costume image in contemporary Korean fashion design expressed beauty of traditional dress. This study compared Korean and American regarding the evaluation of Korean costume image. The result was as follows; 1. The constructing factors of Korean costume image were found out as elegance, simplicity, neatness, femineity, looseness. (total variance; 62%) 2. The visual evaluation between Korean and American were sinificantly different regarding 5 factors. 3. Korean costume design were classified 4 clusters. Korean traditional fabrics and colors were commonly used in the 4 clusters. Difference of design were found in the structure of form. Formation of Korean costume image were influenced by silhouette and pattern of fabric. 4. Image of 'Would like to purchase' were influenced by image of taste.

• Proceedings of the Korean Society of Computer Information Conference
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• 2013.07a
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• pp.185-187
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• 2013

유비쿼터스 컴퓨팅이 생활의 일부가 되어가면서 정보의 양도 급속도로 늘어나고 있으며, 이로 인해 많은 데이터 속에서 정보를 찾아내는 기술이 부각되고 있다. 고객 기반의 협력적 필터링을 이용한 고객 선호도 예측 방법에서는 아이템에 대한 사용자의 선호도를 기반으로 이웃 선정 방법을 사용하므로 아이템에 대한 내용을 반영하지 못할 뿐만 아니라 희박성 문제를 해결하지 못하고 있다. 그리고 비슷한 선호도를 가진 일부 아이템의 정보를 바탕으로 하기 때문에 아이템의 속성은 무시하는 경향이 있다. 본 논문에서는 유비쿼터스 상거래에서 RFM(Recency, Frequency, Monetary) 분석 기반의 SOM을 이용한 군집방법을 제안한다. 제안 방법은 고객의 구매 데이터 기반의 유사한 속성의 데이터끼리의 클러스터링을 통해 보다 빠른 시간 내에 고객 성향에 맞는 추천이 가능한 구매 패턴 추출이 가능하다.

• Journal of the Korean Society of Costume
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• v.21
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• pp.219-226
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• 1993

The main purpose of this study is to inves-tigate brand loyalty on ready-to-wear of fe-male. The subjects were two hundred ninty females in Taegu. Using SPSS package in or-der to identify relations of clothing selection behavior and information source uses multivariate analysis of variance(MANPVA) univariate analysis of variance(ANOVA) were executed. Scheffe est a kind of post-hoc multiple comparisons methods was adapted. conclusions reached in this study are as follows: 1. Clothing purchase pattern of consumers classified brand loyal group and brand dis-loyal group. The number of people in the brand loyal group was fifty more than that of the brand disloyal group. 2. In relation of brand loyalty and clothing selection behavior brand loyal group had high scores on individuality and exhibition of clothing selection behavior. Brand dis-loyal group had high scors on economy practicality courtesy facility. 3. In difference of information uses on brand loyalty brand loyal group had high scores on printed-information source, broadcast-ing-information source broadcast-ing-information sources. Among them brand loyal group particularly used printed-infor-mation source more than brocasting infor-mation source. On the contray brand dis-loyal group have high scores on human-in-formation source.

• Agribusiness and Information Management
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• v.5 no.2
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• pp.1-5
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• 2013

Demographic transition drives changes in consumer demand for food products. This study examines how rising incomes and population trends affect spending on food purchased for home. The objective of this study is to characterize the relationships between selected socio-demographic factors and food selection among South Korean households. Panel data from Rural Development Administration (RDA) in South Korea in 2010 was used (n=971). Household food purchases were classified into one of the five food groups from Composition of Foods of RDA. Multiple regression analysis was used to analyze the effects of household size and income based on the expenditure share on each food group. All statistical analyses were performed using SAS/ PC version 9.3. Results show that household socio- demographic characteristics have a strong influence on food purchasing, with the purchase of vegetables and fruit, and processed food and pre-packaged being particularly sensitive.

• Journal of Construction Engineering and Project Management
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• v.2 no.4
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• pp.32-41
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• 2012

In recent times, multi-centralization and decentralization as well as large Capital area and suburbanization in the spatial structure of capital area. With rapid growth, urbanization and industrialization are unsystematic, and growth inequality between regions caused negative effects such as discordant centralization and decentralization, fluctuating land value, and gap between living conditions. Accordingly, this study analyzed urban spatial indexes by the self-governed body in the capital area such as Seoul, Incheon, and Gyeonggi province for the analysis of the regional inequality phenomenon. We examined the characteristics of temporal and spatial changes in urban spatial structure in the capital area by utilizing the distribution pattern and density of city indexes such as population, employment, etc, and then drew the commonality of those factors through factor analysis. We evaluated the drawn results through the city standard index by each city, conducted factor score analysis, and identified the interaction between each factor and Housing Purchase Price Composite Indices index, housing rent price index(Housing Jeonse Price Composite Indices), land price fluctuation rate, diffusion ratio of house, and financial independence.

• Journal of Families and Better Life
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• v.14 no.3
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• pp.197-210
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• 1996

The purpose of this study was to investigate the correlation and the influence of the environmental education and the environmental awareness on environmental awareness behavior of consumer. the finding were as follows; The environmental awareness behavior of consumer had significant difference according to degree of education and house pattern but had no significant difference according to state of job. The environmental education had significant difference all type in environmental awareness behavior of consumer but the environmental awareness had significant difference except II(behavior of purchase in green product), The correlation among the environmental education the environmental awareness and the environmental awareness behavior of consumer was very high but the environmental education and type II in the environmental awareness behavior of consumer was very. low The environmental education and the environmental awareness had direct and indirect influence on the envir nmental awareness behavior of consumer expect type II.

• Journal of Information Technology Applications and Management
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• v.24 no.4
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• pp.1-12
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• 2017

Item-based collaborative filtering (IBCF) is an important technology that is widely used in recommender system of online shopping malls. It uses historical information to compute item-item similarity and make predictions. However, in offline shopping each customer's purchasing pattern can be occurred continuously and repeatedly due to time and space constraints contrast to online shopping. Those facts can make IBCF to have limitations from being applied to offline shopping malls directly. In order to improve the quality of recommendations made by IBCF in offline shopping mall, we propose an ensemble approach that considers both item-item similarity of IBCF and each customer's purchasing patterns which are modeled by item networks. Our experimental results show that this approach produces recommendation results superior to those of existing works such as pure IBCF or bestseller approaches.

• Journal of the Korean Home Economics Association
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• v.30 no.1
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• pp.67-86
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• 1992

The author distributed the questionaires which ask the idea of the purchase of children's clothes in order to help the emotinal development of children and to raise demostic economy. 89% of those who answered realized the necessity of home sewing. Because of the lack of sewing ability(66%), the author made comparatively easy patterns such as blouses for summer, skirts, short pants and one-piece dresses. To populrize these patterns, the aother used the measurements of body-measurement which were made by Korea Institute of Standard. The author studied the patterns and choice of patterns according to growing body. The author tested the clothes worn and visual evaluation for fitness of the patterns. The results are as follows: First; The author developed basic pattern 1 and 2 and applied to design A, B and C. Second: For every design, the author made patterns fit to the children. Third: According to age, the author curtailed or enlarged patterns. Lastly: The author tried to reduce living expenses through making children's clothes using the sewing machine and supress over-consumption and lead the people toward normal economic life.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2005.04a
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• pp.323-326
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• 2005

실세계에서 일어나는 문제는 매우 복잡하고 다양하기 때문에 예측하기가 어렵고 다양한 상황들이 발생한다. 특히, 소비자의 구매에 따르는 행동을 분석하고 소비자의 다양한 기호를 예측하기 위해서는 구매자의 심리적 요인과 내적 요인이 많은 영향을 미치게 된다. 이러한 요인들은 직접적인 정보 처리가 어렵기 때문에 정보의 불확실성을 취급하는 기술이 필요하다. 따라서 본 논문에서는 상품 구매에 따르는 소비자의 구매행동 패턴을 분석하기 위해 판매자의 노하우와 소비자의 구매의식을 조사하여 이 데이터를 바탕으로 베이지안 네트워크를 구성하고 구매패턴을 분류하는 방법을 제안하였다. 특히, 베이지안 네트워크를 이용하여 불필요한 속성을 가진 데이터를 제거한 후 코호넨의 SOM을 이용하여 소비자의 구매 패턴을 분류하도록 하였다.