• Title/Summary/Keyword: RFM모델

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Posting RFM Model for Evaluating the Member Loyalty in Social Network Sites (소셜 네트워크 사이트 회원 충성도 평가를 위한 Posting RFM 모델)

  • Li, De-Kui;Ha, Byung-Kook
    • Journal of Service Research and Studies
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    • v.1 no.1
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    • pp.49-60
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    • 2011
  • Recently, with the growing of social network sites, people's choice is also getting more and more. So the notion of loyalty has become an important construct within the Social Network framework because of member is easy switching on the social networking sites. Despite the increasing importance of social network sites loyalty question, there's very little research in this area. In electronic commerce, the website loyalty development process is based on both website satisfaction and website trust toward the net-enabled business. But how to target the members with high or low loyalty in the social network sites is still a question. In this paper we propose one improved RFM model to evaluate the member loyalty to find the potential members for improving the service quality of the social network site. In addition, an empirical case study is performed to demonstrate how this procedure works. Moreover, further applications of this research are provided for improved social network sites experiences and how to use the model to practice.

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The Application of RFM for Geometric Correction of High-Resolution Satellite Image Data (고해상도 인공위성 영상데이터의 기하보정을 위한 RFM의 적용)

  • 안기원;임환철;서두천
    • Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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    • v.20 no.2
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    • pp.155-164
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    • 2002
  • In this study, in order to discuss the geometric correction methods of high-resolution IKONOS satellite image, the existing polynomial model and RFM which is able to rectify satellite image without auxiliary data are applied to IKONOS satellite image data. Then the accuracy of ground point versus number of GCPs and each order of RFM are assessed. A numerical instability is removed by application of Tikhonov regularization method. As the results of this study, the root mean square errors of RFM is decreased more than 2 pixels in comparison with the two dimensional polynomial model.

RFM for High Resolution Satellite Sensor Modeling (RFM을 이용한 고해상도 인공위성 센서모델링)

  • 조우석;이동구
    • Korean Journal of Remote Sensing
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    • v.18 no.6
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    • pp.337-344
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    • 2002
  • In general, in order to obtain position information from satellite images, satellite sensor model which represents the geometric relationship between sensor and targeted area should be established in the first place. However, it is not simple for modelling pushbroom satellite sensor due to the image capturing process. In recent development of new generation imaging sensors, a generic sensor model, which is applicable to all types of sensors such as frame, pushbroom, whiskbroom, and SAR is in great need to the remote sensing and photogrammetry community. In this paper, the RFM as sensor model was implemented with KOMPSAT EOC and SPOT satellite images and analyzed in cases where the number and distribution of ground control points were varied. The test results of RFM were presented and compared with those of Direct Linear Transformation(DLT).

A study on proposing a method for grouping R, F, and M in RFM model (RFM에서 등급부여 방법에 관한 연구)

  • Ryu, Gui-Yeol;Moon, Young-Soo
    • Journal of the Korean Data and Information Science Society
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    • v.24 no.2
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    • pp.245-255
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    • 2013
  • The object of study is to propose a method for grouping R, F, and M in RFM model. Our model uses 6 levels using standard normal distribution. First level is upper 2.5% and second level next 13.5%, third level next 34%, fourth level next 34%, fifth level next 13.5%, sixth level next 2.5%. Values are symmetric and limits are clear. We compare proposed model with traditional 5 level model and 10 level model using NDSL data of KISTI. Proposed model divides most clearly the distribution of the RFM function for all cases of weights, because it uses the distribution of customers. Comparison studies of our model with grouping using cluster analysis and studies on weights of RFM model are needed.

A Study on RFM Based Stereo Radargrammetry Using TerraSAR-X Datasets (스테레오 TerraSAR-X 자료를 이용한 RFM 기반 Radargrammetry에 관한 연구)

  • Bang, SooNam;Koh, JinWoo;Yun, KongHyun;Kwak, JunHyuck
    • KSCE Journal of Civil and Environmental Engineering Research
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    • v.32 no.1D
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    • pp.89-94
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    • 2012
  • The RFM (Rational Function Model), as an alternative to physical sensor models has been widely used for photogrammetric processing of high resolution optical satellite imagery. However, the application of RF modeling to the SAR (Synthetic Aperture Radar) is very limited. In this paper, stereo radargrammetric processing of TerraSAR-X stereo pairs with RFM is implemented and analyzed. The investigation has shown that the accuracy of TerraSAR-X DSM is similar to that of the commercial S/W product. Finally, it is demonstrated that RFM is effective and feasible in the application to the radargrammetric SAR image processing.

Accuracy of Precision Ground Coordinates Determination Using Inverse RPC in KOMPSAT Satellite Data (다목적실용위성(KOMPSAT)의 Inverse RPC 해석을 통한 정밀지상좌표 결정 정확도)

  • Seo, DooChun;Jung, JaeHun;Hong, KiByung
    • Aerospace Engineering and Technology
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    • v.13 no.2
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    • pp.99-107
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    • 2014
  • There are two types of Physical Model and RFM (Rational Function Model) is to determinate ground coordinates using KOMPSAT-2 and KOMPSAT-3 satellite data. Generally, RPCs(Rational Polynomial Coefficients) based on RFM is provided for users. This RPCs is to compute the ground coordinates to the image coordinates. If users produce ortho-image with provided RPCs is useful, directly compute the ground coordinates corresponding to image coordinates and check location accuracy etc. are difficult. In this study, a basic algorithm of inverse RPCs that calculates the image coordinates to ground coordinates, compute based on provided RPCs and evaluation of determinated ground coordinates using developed inverse RPCs were proposed.

Customer List Segmentation Using the Combined Response Modeling (결합 리스펀스 모델링을 이용한 고객리스트 세분화)

  • Eui-ho Seo;Kap-chel Noh;Eung-beom Lee
    • Asia Marketing Journal
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    • v.1 no.2
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    • pp.19-35
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    • 1999
  • 데이터베이스 마케팅 전략을 수립하고 집행함에 있어서 고객에게 접근하기 위한 촉진 매체로써 직접우편(Direct Mail)과 텔레 마케팅 등의 직접반응매체를 주요 수단으로 하는 경우 이를 다이렉트 마케팅이라고 한다. 다른 마케팅 전략들과 마찬가지로 다이렉트 마케팅에서도 마케팅 자원이 효과적으로 사용될 수 있도록 고객 데이터베이스를 세분화하는 작업을 수행한다. 리스펀스 모델링(Response Modeling)은 다이렉트 마케팅분야에서 고객리스트를 세분화하고 각 세그멘트별로 고객의 반응(구매행위)을 예측하는 기법을 말하며 RFM(Recency, Frequency, Monetary), 로지스틱, 신경망은 리스펀스 모델링을 위해서 가장 널리 사용되고 있는 기법이다. 과거에 이들 방법은 고객 데이터베이스 전체에 단독 모델로 적용되어 왔으나 이러한 단독 모델을 고객 데이터베이스에 적용하는 것이 정당화 되려면 고객들이 동일한 방식으로 반응한다는 전제가 필요하다. 그러나 일반적으로 고객의 반응방식에는 상당한 이질성이 존재한다. 예컨대 직업, 나이, 소득, 성별 등이 같다고 해서 같은 구매패턴을 보이지는 않는다는 것이다. 즉 고객A의 구매행위는 회귀선에 의해서 잘 설명되는 반면에 고객B는 신경망이나 RFM으로 잘 설명될 수 있는 경우가 존재하는 것이다. 이러한 구매행위의 이질성을 반영하기 위해서 최근에는 두개 이상의 방법을 결합하여 사용하는 결합 리스펀스 모델링 방법도 시도 되어 왔다. 그러나 결합 리스펀스 모델링에 관한 기존 연구들은 상관관계가 낮은 모델들을 결합함으로써 세분화의 효과를 단독 모델을 사용할 때 보다 개선할 수 있다고는 하였으나 구체적으로 어떤 모델들이 서로 낮은 상관관계를 갖는지는 보여주지 못하였다. 본 논문에서는 RFM 방법을 모델 내에서 사용하는 변수와 이를 이용한 모델링 방법상의 차이로 인하여 다른 두 방법(로지스틱, 신경망)과 매우 낮은 상관관계를 갖는 방법으로 제시하고 RFM과 다른 두 방법간의 낮은 상관관계를 이용하여 결합하는 경우 모델의 예측효과를 상당히 개선할 수 있음을 사례분석을 통해서 보이고자 한다.

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Evaluation of The Image Segmentation Method for DEM Generation of Satellite Imagery (위성영상의 DEM 생성을 위한 영상분할 방법의 적합성 평가)

  • 이효성;송정헌;김용일;안기원
    • Korean Journal of Remote Sensing
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    • v.19 no.2
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    • pp.149-157
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    • 2003
  • In this study, for efficient replacement of sensor modelling of high-resolution satellite imagery, image segmentation method is applied to the test area of the SPOT-3 satellite imagery. After that, a third-order polynomial model in the sectioned area is compared with the RFM which Is to the entire in the test area. As results, plane error of the third-order polynomial model is lower(approximately 0.8m) than that of RFM. On the other hand, height error of RFM is lower(approximately 1.0m).

Modification of IKONOS RPC Using Additional GCP (지상기준점 추가에 의한 IKONOS RPC 갱신)

  • Bang, Ki-In;Jeong, Soo;Kim, Kyung-Ok;Cho, Woo-Sug
    • Journal of Korean Society for Geospatial Information Science
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    • v.10 no.4 s.22
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    • pp.41-50
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    • 2002
  • RPM is the one of the sensor models which is proposed by Open GIS Consortium (OGC) as image transfer standard. And it is the sensor model for end-users using IKONOS, a commercial pushbroom satellite, imagery which provide about 1m ground resolution. Parameters called RPC which is IKONOS RFM coefficients are serviced to end-users. But if some users try to make additional effort to get rigorous geo-spatial information, it is necessary to apply mathematic or abstract sensor models, because vendors don't offer any ancillary data for physical sensor models such as satellite orbit and navigation. Abstract sensor models such as pushbroom Direct Linear Transform (DLT) require many GCPs well distributed in imagery, and mathematic sensor model such as RFM, polynomials need much more GCPs. Therefore RPC modification using additional a few GCPs is the best solution. In this paper, two methods are proposed to modify RPC. One is method to use pseudo GCPs generated in normalized cubic, and another method uses parameters observations and a few GCPs. Through two methods, we get improvement of accuracy 50% and over.

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Web services Framework for Loyal Customer Management based on RFM Models in Internet Retailing (인터넷 소매유통업의 RFM 모델 기반 충성고객관리를 위한 웹서비스(WsLCM) 프레임웍)

    • Journal of Intelligence and Information Systems
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    • v.8 no.1
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    • pp.41-41
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    • 2002
  • 소매유통업에 있어 충성고객을 발견하고 효과적으로 관리하는 일은 마케팅 부서의 주요 관심사라고 할 수 있다. 최근 성숙된 유통 채널로 자리잡고 있는 인터넷 소매유통업도 다양한 마케팅 노력을 기울이고 있으며 그 성과가 기존 소매유통업 보다 클 것으로 기대하고 있는데 이는 인터넷 소매유통업이 기본적으로 디지털 기반 구조 하에 사업이 수행되기 때문이다. 그러나, 매출 규모가 확장됨에 따라 고객 관계가 보다 복잡해지고 거래 건수도 크게 확장되고 있는 인터넷 소매유통업은 전자적으로 이용 가능한 고객 관리 서비스를 필요로 하고 있다 본 논문은 인터넷 소매유통업의 충성고객관리를 위한 웹서비스의 프레임웍 및 적용 사례를 제시하고 있다. 고객관리 웹서비스의 기본 모델은 전통적인 RFM분석에 기반을 두고 있는데 복잡한 충성고객관리 업무를 처리하는 에이전트를 제공한다. 인터넷 쇼핑몰이나 상점의 운영 시스템과 용이하게 통합될 수 있는 웹서비스는 적은 비용으로 효과적인 고객관리를 실현하는데 기여할 것으로 기대된다.