• Food Industry
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• s.13
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• pp.80-83
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• 1973

70년대의 소비자패턴은 큰 변모를 갖어 올것이라고 평론가들이 말 하였듯이 이미 모든 분야에 걸쳐서 일대격변의 시대가 찾아왔다고 말하지 않으면 안될것이다. 원인은 여러가지로 생각할수 있겠으나 소득증대, 여가선용, 가치관의 변화라고하는 요인을 들수있을 것이다. 60년대라고하면 소비자에 있어서 생리적욕구와 물리적 욕구를 충족만 시켜주면 되었던 시대였었다. 그리고 이와같은 욕구를 만족시킬 상품이나 서어비스는 비교적 라이프싸이클(生活環)이 길고 안정된 시장이 였었다. 기업측에서 볼것 같으면 물건을 팔기쉬운 시대였다고 말할수 있을것이다. 그러나 70년대라고 하면 소비자가 저차원의 욕구라고 할 기본적인 욕구는 일단 만족되고 자기실현의 욕구와 같은 고차원의 욕구를 구하는 방향으로 이행하고 있는 시대인 것이다.

• Proceedings of the Korea Multimedia Society Conference
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• 2002.11b
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• pp.5-8
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• 2002

전자상거래의 보편화와 더불어 인터넷 쇼핑몰이 급격히 늘어나면서 선택의 폭이 커짐과 동시에 고객에게는 선택의 불편이 있고, 판매자에게는 경쟁이 가중될 것이므로 더욱 치밀하고 편리한 마케팅 기법이 요구되어지고 있다. 따라서 인터넷 쇼핑몰에서의 개별고객의 니즈를 파악하기 위한 다양한 분석적 접근이 이루어지고 있다. 웹 데이터마이닝은 웹사이트에 접근한 사용자들의 개인별 접근패턴을 파악하고 예측하기 위해 로그파일을 분석한다. 본 연구에서는 eCRM의 핵심요소인 로그분석을 위한 데이터마이닝 엔진을 설계하고 구현한다.

• Journal of Korea Technology Innovation Society
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• v.2 no.2
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• pp.187-200
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• 1999

전자상거래는 유통업의 형태를 바꿀 정도로 엄청난 기술혁신이지만, 적어도 앞으로 상당기간, 산업적인 성과는 기대이상으로 그렇게 커 보이지 않는다. 기술혁신이 분명 존재하였건만 이 효과를 가로막는 다른 한계들이 있기 때문이다. 바로 이러한 한계가 무엇인가를 보다 집중적으로 분석하고자 한 것이 본고의 목적이다. 이는 전자상거래가 어떻게 하면 성공할 것인가를 살펴보는 것과도 일맥 상통한 것이다. 본고는 종전의 전자상거래 분석 관점과는 달리 유통 전문가적인 시각을 견지한다. 유통 전문가적인 시각이란 유통업적인 관점이고 유통업체를 바탕으로 한 관점이다. 유통업적인 입장을 강조하기 위해 본고는 먼저 점포도 불필요하고 인건비나 관리비를 절감할 수 있다는 전자상거래가 오히려 전통상거래보다 비싸다는 점에서 출발한다. 그리고 매입의 문제, 택배비용의 문제, 거래의 신뢰성 문제, 시장기반의 문제 등이 있다는 점을 지적한다.

• Proceedings of the KIEE Conference
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• 2008.07a
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• pp.558-559
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• 2008

현재 수요반응(Demand Response) 프로그램은 발전설비 용량의 부족이나 높은 발전 연료비용의 상승으로 인해 다양한 나라들에서 도입되고 있는 실정이다. 그것은 실시간으로 소비자들이 그들의 소비패턴을 선택할 수 있는 프로그램이라 말할 수 있다. 다시 말하면, 수요반응이란 소비자들의 일반적인 전력소비패턴에서 전력가격이나 기타 다른 신호에 반응하여 전력 사용량을 변화시키는 것으로 정의할 수 있다. 수요반응의 효과는 전력가격의 급상승 방지, 공급 신뢰도 향상, 그로 인한 사회적인 복지향상 등 여러 가지 측면에서 생각해 볼 수 있다. 이러한 다양한 효과 가운데, 본 논문에서는 thermal comfort zone을 고려하여 수요반응 프로그램을 수행하는 동안 전력판매사업자 입장에서 최대의 이득을 얻기 위한 적정 인센티브와 부하 감축량을 결정한다.

• Journal of the Korean Institute of Intelligent Systems
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• v.15 no.3
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• pp.306-311
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• 2005

To analyze the consumer's purchase pattern, we must consider a factor which is a cultural, social, individual, psychological and so on. If we consider the internal state by the consumer's purchase, Both the consumer's purchase action and the purchase factor can be predicted, so the corporation can use effectively in suitable goods development in a consumer's preference. These factors need a technology that treat uncertain information, because it is difficult to analyze by directly information processing. Therefore, bayesian network manages elements those the observation of inner state such as consumer's purchase is difficult. In addition, it is interpretable about data that the observation is impossible. In this paper, we examine the seller's know-how and the way of consumer's purchase to analyze consumer's purchase action pattern through goods purchase. Also, we compose the bayesian network based on the examined data, and propose the method that predicts purchase patterns. Finally, we remove the data including unnecessary attribute using the bayesian network, and analyze the consumer's Purchase pattern using Kohonen's SOM method.

• Spatial Information Research
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• v.23 no.3
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• pp.23-33
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• 2015

Most data used for urban planning is aggregated by administrative district. Thus, a fundamental limit to analysing the changes of micro-geographical units exists. The object of this study is to estimate spatial development patterns based on characteristic city indicators. Gangnam, an area that was analysed, was divided into hexagon polygons. The development density and characteristic city indicators were input into each polygon. Moreover, this study analysed the influence of characteristic city indicators on development density using multinomial regression analysis. According to the results, distance between a polygon and both a road and a bus stop led to a decrease of development density in the polygon. However, distance between a polygon and a river led to an increase of development intensity. The method of this analysis and the results can be used to disaggregate the zonal data in the urban planing area.

• The KIPS Transactions:PartD
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• v.17D no.1
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• pp.1-8
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• 2010

Association rule mining techniques enable us to acquire knowledge concerning sales patterns among individual items from voluminous transactional data. Certainly, one of the major purposes of association rule mining is utilizing the acquired knowledge to provide marketing strategies such as catalogue design, cross-selling and shop allocation. However, this requires too much time and high cost to only extract the actionable and profitable knowledge from tremendous numbers of discovered patterns. In currently available literature, a number of interest measures have been devised to accelerate and systematize the process of pattern evaluation. Unfortunately, most of such measures, including support and confidence, are prone to yielding impractical results because they are calculated only from the sales frequencies of items. For instance, traditional measures cannot differentiate between the purchases in a small basket and those in a large shopping cart. Therefore, some adjustment should be made to the size of market baskets because there is a strong possibility that mutually irrelevant items could appear together in a large shopping cart. Contrary to the previous approaches, we attempted to consider market basket's size in calculating interest measures. Because the devised measure assigns different weights to individual purchases according to their basket sizes, we expect that the measure can minimize distortion of results caused by accidental patterns. Additionally, we performed intensive computer simulations under various environments, and we performed real case analyses to analyze the correctness and consistency of the devised measure.

• Journal of Korea Multimedia Society
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• v.15 no.7
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• pp.941-950
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• 2012

A virtual garment fitting system which fits the top and bottom of a garment on 3D body data is introduced. This system uses the laser scanned 3D body data and the digital images photographed the front and back of a garment. The digital images are modeled to reflect tensions among particles in the images and the friction and gravity effects are considered in the fitting process to the body data. When a bottom is fitted, a virtual belt to hold the bottom in the waist is introduced since gravity effects pull down it. Also the process for fitting the top and bottom on layers is proposed here. The system has the strengths that it uses only the front and back image of a garment instead of using complicated patterns of a garment, and provides a realistic fit result as a 3D figure. As on-line retailing shop in present displays front and back images of garments, this system also does. However this system provides a differentiated service to user than present retailing shop as showing a 3D fit image. It will make a new trend in online shop retailing of garment.

• Journal of Digital Convergence
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• v.14 no.9
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• pp.317-323
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• 2016

Big Data is now seen as a major asset in the company's competitiveness, its influence in the future is expected to grow. Companies that recognize the importance are already actively engaged with Big Data in product development and marketing, which are increasingly applied across sectors of society, including politics, sports. However, lack of knowledge of the system implementation and high costs are still a big obstacles to the introduction of Big Data and systems. It is an objective in this study to build a Big Data system, which is based on open source Hadoop and Hive among Big Data systems, utilizing POS sales data of small and medium-sized offline markets. This approach of convergence is expected to improve existing sales systems that have been simply focusing on profit and loss analysis. It will also be able to use it as the basis for the decisions of the executive to enable prediction of the consumption patterns of customer preference and demand in advance.

• Journal of the Korean Society for Railway
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• v.18 no.6
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• pp.630-638
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• 2015

The total number of passengers on the KTX since its construction in 2004 surpassed 500 million in October, 2015. The operation of KTX made it possible to reach anywhere in a country in half a day, which subsequently altered people's lifestyle. As the KTX has become an important mode of transportation, there is a growing interest in the optimal size and location of its stations. Currently, the stations are constructed through public-private partnerships since a sufficient amount of budget is hard to secure only from the public sector; however, because railway stations are traditionally aimed at promoting public interests, an emphasis on the profitability of the private sector could compromise public interests. At this juncture, this study separately computes the number of users based on each of the two primary functions of the stations-as a railway station and as a sales facility-and estimates the numbers of people according to various transportation modes that are taken to access the stations. This estimation is applied to the case of Dongdaegu Station, which will open in 2016. Such an application helps to predict and respond to possible congestion as brought about by the expansion of the sales facility.