• Journal of Korean Institute of Industrial Engineers
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• v.41 no.1
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• pp.10-16
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• 2015

In this study, we suggest a method to predict probability distribution of a new customer's degree of loyalty using C-CRF that reflects the RFM score and similarity to the neighbors of the customer. An RFM score prediction model is introduced to construct the first feature function of C-CRF. Integrating demographical similarity, purchasing characteristic similarity and purchase history similarity, we make a unified similarity variable to configure the second feature function of C-CRF. Then parameters of each feature function are estimated and we train our C-CRF model by training data set and suggest a probabilistic distribution to estimate a new customer's degree of loyalty. An example is provided to illustrate our model.

• Journal of the Korean Data and Information Science Society
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• v.19 no.2
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• pp.597-608
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• 2008

Marketing has been used the power of data and information technology in the pursuit of personal marketing of products and service to customers, based on their preferences and needs. We analyzed the performance of twenty six combined(RFM and Confidence) response modeling methods that were proposed by Zahavi and Levin(l997) and Sho, et al.(1999). As a result, we were able to increase about 3.5%p. forecasting accuracy of customers response through combination with confidence(C) that is able to consider characteristics of product than using the single RFM model that is practically the most widely used.

• Journal of the Korean Data and Information Science Society
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• v.23 no.3
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• pp.515-523
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• 2012

Most companies make efforts to maximize their profitability by improving loyalty to existing customers through customer relationship management (CRM). According to the Wikipedia, CRM is a widely implemented strategy for managing a company's interactions with customers, clients and sales prospects. And RFM is a method used for analyzing customer behavior and defining market segments. It is commonly used in database marketing and direct marketing and has received particular attention in retail. In general, one considers recency, frequency, and monetary for customer segmentation in RFM method. In this paper, we apply RFMP method added to the purchase period of advertising items in the traditional RFM model for real estate customer segmentation. We will be able to establish the differentiated marketing strategy by RFMP method.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.13 no.2
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• pp.543-547
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• 2012

The environmental education is more and more important according to increasing environmental problems, but university students don't receive it actively. Actually, environmental education in university is conducted and focused on environmental engineering. In order to have an effect on environmental education for all engineering college students, the course of environmental education consists of various fields of engineering study including environmental engineering. The environmental education categories for engineering college students are determined by using an AHP technique in this study. After educating engineering college students with the developed environmental education course, we evaluated the environmental education performance using the survey on perception level and purchasing data of environmentally consciously products by statistical and RFM analysis.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.31 no.6_2
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• pp.577-583
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• 2013

Recently, massive archives of ground information imagery from new sensors have become available. To establish a functional relationship between the image and the ground space, sensor models are required. The rational functional model (RFM), which is used as an alternative to the rigorous sensor model, is an attractive option owing to its generality and simplicity. To determine the rational polynomial coefficients (RPC) in RFM, however, we encounter the problem of obtaining a stable solution. The design matrix for solutions is usually ill-conditioned in the experiments. To solve this unstable solution problem, regularization techniques are generally used. In this paper, we describe the effective determination of the optimal regularization parameter in the regularization technique during RPC derivation. A brief mathematical background of RFM is presented, followed by numerical approaches for effective determination of the optimal regularization parameter using the Euler Method. Experiments are performed assuming that a tilted aerial image is taken with a known rigorous sensor. To show the effectiveness, calculation time and RMSE between L-curve method and proposed method is compared.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.29 no.1
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• pp.1-9
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• 2011

The objective of this paper is to improve the accuracy of the 3D geopositioning extracted from Rational Polynomial Coefficient(RPC) provide in the KOMPSAT-2 metadata files. In this paper, we developed the algorithm to adjust a RFM(Rational Functional Model), and could improve the accuracy of a RFM with this algorithm. Furthermore, when a RFM was adjusted with this algorithm, the effects of the number of GCPs on the accuracy of the adjusted RFM was tested. For accuracy assessment using adjusted RFM, 9 ground control points(GCPs) and 24 check points could be used. Results indicated that the root mean squared errors(RMSEs) of horizontal residual errors calculated 24 check points were 2.20(m). The achieved accuracy of three dimensional object-point determination was 1.72(m) in the X-dimension and 1.37(m) in the Y-dimension and 2.20(m) in the Z-dimension.

• 한국지형공간정보학회:학술대회논문집
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• 2002.03a
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• pp.27-33
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• 2002

최근 들어 다항식비례모형(RFM: Rational Function Model)은 비전문가에게 있어서 지형보정을 위한 정확도 문제를 해결함과 동시에 센서 종류에 상관없이 적용 가능한 범용적인 센서모델링 기법으로 각광을 받고 있다. 그러나 엄밀(physical) 모델이 없는 센서 혹은 위성의 궤도력 자료를 제공하지 않는 센서의 경우 다항식비례모형의 적용을 위해서는 다수의 매개변수 사용으로 인한 계수들 간의 상관성을 고려해야 한다. 이에 본 연구에서는 2차 다항식비례모형에 기초하여 전방 다항식비례모형(Forward RFM)과 상관도 분석을 통한 전방 다항식비례모형의 이른 및 위치정확도에 관한 연구를 수행하였다. 대상연구지역은 KOMPSAT(Korea Multi-Purpose Satellite)과 SPOT으로 촬영한 대전광역시와 그 주변지역으로 SPOT과 KOMPSAT 모두 상관성 분석 전에는 대략 50% 정도의 검사점에 대해 과대오차(>100m)가 얻어졌으며, 이 점들을 제외한 검사점에 대해서도 SPOT은 평균수평오차 20-24m, 평균표고오차 25m, KOMPSAT은 평균수평오차 15-24m, 평균표고오차 30m를 나타내었다. 전방 다항식비례모형에 대하여 상관성 분석을 수행한 후에는 검사점에 대한 모든 과대오차 조정결과가 소거되었고 검사점에 대해서 SPOT은 평균수평오차 8.8m, 평균표고오차 25.2m, KOMPSAT은 평균수평오차 8.4m, 평균표고오차 14.5m를 나타내었다. 최종적으로 연구지역에 대한 수치표고모형의 제작을 통해 상관도 분석을 통한 다항식비례모형의 실제 적용 가능성을 보여주었다.

• Proceedings of the Korean Association of Geographic Inforamtion Studies Conference
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• 2003.04a
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• pp.121-128
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• 2003

사면관측 원리에 의해 획득되는 레이더 영상은 레이더파의 입사각도와 지표면의 경사도 및 방위각에 따라 기하학적 왜곡이 발생하게 된다. 전 국토의 70% 이상이 산악지형인 국내 여건을 감안한다면 레이더 영상의 정량적 활용을 위해서는 정밀한 기하보정이 반드시 필요하다. 본 연구에서는 RADSARSAT-1 SAR 영상에 대하여 세 가지 기하보정 방법을 적용하였다. 먼저 GCP 만을 이용한 단순기하보정을 수행하였고, 두번째로 위성의 자세와 위치정보 등을 이용하여 센서모델을 통한 보정을 하였다. 마지막으로 다양한 영상자료에 적용할 수 있는 RFM(Rational Function Model)을 이용하여 기하보정을 하였다. 이 세 가지 방법으로 기하보정된 레이더 영상의 위치정확도를 모의 레이더 영상과 비교 분석하였다. 또한 RFM을 이용한 보정결과를 검증하기 위하여 SIR-C 영상을 추가로 분석하였다.

• Proceedings of the Korean Society of Surveying, Geodesy, Photogrammetry, and Cartography Conference
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• 2004.11a
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• pp.269-274
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• 2004

Recent adoption of the generalized sensor model to IKONOS and Quickbird satellite imagery have promoted various research activities concerning alternative sensor models which can replace conventional physical sensor models. For example, there are the Rational Function Model(RFM), the Direct Linear Transform(DLT) and the polynomial transform. In this paper, the DLT model which uses just a few number of GCPs was suggested. To evaluate the accuracy of the proposed DLT model, the RFM using 35 GCPs and the bias compensation method(Fraser et al., 2003) were compared with it. Quantitative evaluation of 3B positioning results were performed with independent check points and the digital elevation models(DEMs). In result, a 1.9- to 2.2-m positioning accuracy was achieved for modeling and DEM accuracy is similar to the accuracy of the other model methods.

• Proceedings of the Korean Society of Surveying, Geodesy, Photogrammetry, and Cartography Conference
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• 2003.10a
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• pp.417-422
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• 2003

The KOMPSAT-2 MSC(Multi-Spectral Camera), with high spatial resolution, is currently under development and will be launched in the end of 2004. A sensor model relates a 3-D ground position to the corresponding 2-D image position and describes the imaging geometry that is necessary to reconstruct the physical imaging process. The Rational Function Model (RFM) has been considered as a generic sensor model. form. The RFM is technically applicable to all types of sensors such as frame, pushbroom, whiskbroom and SAR etc. With the increasing availability of the new generation imaging sensors, accurate and fast rectification of digital imagery using a generic sensor model becomes of great interest to the user community. This paper describes the procedure to generation of the RPC (Rational Polynomial Coefficients) for KOMPSAT-2 MSC.