• Title/Summary/Keyword: RFM Method

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Prediction of New Customer's Degree of Loyalty of Internet Shopping Mall Using Continuous Conditional Random Field (Continuous Conditional Random Field에 의한 인터넷 쇼핑몰 신규 고객등급 예측)

  • Ahn, Gil Seung;Hur, Sun
    • 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.

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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Homogenized thermal properties of 3D composites with full uncertainty in the microstructure

  • Ma, Juan;Wriggers, Peter;Li, Liangjie
    • Structural Engineering and Mechanics
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    • v.57 no.2
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    • pp.369-387
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    • 2016
  • In this work, random homogenization analysis for the effective thermal properties of a three-dimensional composite material with unidirectional fibers is presented by combining the equivalent inclusion method with Random Factor Method (RFM). The randomness of the micro-structural morphology and constituent material properties as well as the correlation among these random parameters are completely accounted for, and stochastic effective thermal properties as thermal expansion coefficients as well as their correlation are then sought. Results from the RFM and the Monte-Carlo Method (MCM) are compared. The impact of randomness and correlation of the micro-structural parameters on the random homogenized results is revealed by two methods simultaneously, and some important conclusions are obtained.

Requiremental Function Method based Owner's Requirement in VE Process Application at Planning Stage (기획단계 발주자 요구사항 기반 Requiremental Function Method VE 적용)

  • Park, In-Ji;Son, Myung-Jin;Hyun, Chang-Taek
    • Proceedings of the Korean Institute of Building Construction Conference
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    • 2012.05a
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    • pp.123-125
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    • 2012
  • It is the important accurately to identify the needs of our customers in order to success the project. Requirements in the early stages of business is very abstract or not quantitative, and that will cause problems such as cost or schedule changes. Particularly many people are likely to prefer the early stages of the project, because the time of applying VE related cost savings is important. Owner's requirement analysis for project success in the VE process does not easy, and specific ongoing management of the requirement is difficult. Therefore, the analysis and the application of owner's requirements is limited in project process. The purpose of this study is proposed to the RFM technique to supplement the functional analysis on the basis owner's requirements analysis in planning a building project.

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Weighted association rules considering item RFM scores (항목 알에프엠 점수를 고려한 가중 연관성 규칙)

  • Park, Hee-Chang
    • Journal of the Korean Data and Information Science Society
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    • v.21 no.6
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    • pp.1147-1154
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    • 2010
  • One of the important goals in data mining is to discover and decide the relationships between different variables. Association rules are required for this technique and it find meaningful rules by quantifying the relationship between two items based on association measures such as support, confidence, and lift. In this paper, we presented the evaluation criteria of weighted association rule considering item RFM scores as importance of items. Original RFM technique has been used most widely applied method using customer information to find the most profitable customers. And then we compared general association rule technique with weighted association rule technique through the simulation data.

Electromyography-signal-based muscle fatigue assessment for knee rehabilitation monitoring systems

  • Kim, Hyeonseok;Lee, Jongho;Kim, Jaehyo
    • Biomedical Engineering Letters
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    • v.8 no.4
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    • pp.345-353
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    • 2018
  • This study suggested a new EMG-signal-based evaluation method for knee rehabilitation that provides not only fragmentary information like muscle power but also in-depth information like muscle fatigue in the field of rehabilitation which it has not been applied to. In our experiment, nine healthy subjects performed straight leg raise exercises which are widely performed for knee rehabilitation. During the exercises, we recorded the joint angle of the leg and EMG signals from four prime movers of the leg: rectus femoris (RFM), vastus lateralis, vastus medialis, and biceps femoris (BFLH). We extracted two parameters to estimate muscle fatigue from the EMG signals, the zero-crossing rate (ZCR) and amplitude of muscle tension (AMT) that can quantitatively assess muscle fatigue from EMG signals. We found a decrease in the ZCR for the RFM and the BFLH in the muscle fatigue condition for most of the subjects. Also, we found increases in the AMT for the RFM and the BFLH. Based on the results, we quantitatively confirmed that in the state of muscle fatigue, the ZCR shows a decreasing trend whereas the AMT shows an increasing trend. Our results show that both the ZCR and AMT are useful parameters for characterizing the EMG signals in the muscle fatigue condition. In addition, our proposed methods are expected to be useful for developing a navigation system for knee rehabilitation exercises by evaluating the two parameters in two-dimensional parameter space.

Collaborative Filtering System using Self-Organizing Map for Web Personalization (자기 조직화 신경망(SOM)을 이용한 협력적 여과 기법의 웹 개인화 시스템에 대한 연구)

  • 강부식
    • Journal of Intelligence and Information Systems
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    • v.9 no.3
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    • pp.117-135
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    • 2003
  • This study is to propose a procedure solving scale problem of traditional collaborative filtering (CF) approach. The CF approach generally uses some similarity measures like correlation coefficient. So, as the user of the Website increases, the complexity of computation increases exponentially. To solve the scale problem, this study suggests a clustering model-based approach using Self-Organizing Map (SOM) and RFM (Recency, Frequency, Momentary) method. SOM clusters users into some user groups. The preference score of each item in a group is computed using RFM method. The items are sorted and stored in their preference score order. If an active user logins in the system, SOM determines a user group according to the user's characteristics. And the system recommends items to the user using the stored information for the group. If the user evaluates the recommended items, the system determines whether it will be updated or not. Experimental results applied to MovieLens dataset show that the proposed method outperforms than the traditional CF method comparatively in the recommendation performance and the computation complexity.

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A Review on the Taguchi Method and Its Alternatives for Dynamic Robust Design (다구치의 동적 강건설계와 그 대안에 관한 고찰)

  • Kim, Seong-Jun
    • Journal of Korean Institute of Industrial Engineers
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    • v.39 no.5
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    • pp.351-360
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    • 2013
  • Taguchi's robust design is a method for quality improvement by making a system insensitive to uncontrollable variations incurred by noise factors and it has received much attention in a wide range of engineering fields. Robust design can be broadly classified into static and dynamic ones. This paper is concerned with dynamic robust design. Taguchi suggested to use a signal-to-noise ratio as a robustness measure, but there has been much debate and criticism on its blind use. In order to cope with this drawback, many alternatives have been proposed. They are divided into performance measure modeling (PMM) and response function modeling (RFM) approaches. In this paper, both PMM and RFM approaches for dynamic robust design are reviewed. An example for illustration is provided as well.

Development of Modeling Method for 3-D Positioning of IKONOS Satellite Imagery (IKONOS 위성영상의 3차원 위치 결정 모형화 기법 개발)

  • 진경혁;홍재민;유환희;유복모
    • 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.

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The Suggestion of the Image Registration Using Terrain Relief Correction Based on RFM (유리함수모델 기반 표고시차보상기법을 사용한 Image Registration 방안 제안)

  • Kim, Hyun-Suk;Kim, Moon-Gyu;Seo, Doo-Chun
    • Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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    • v.30 no.1
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    • pp.21-30
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    • 2012
  • When two bands have different look angle in a space-borne camera system, the registration between two bands is required. The registration cannot be modeled with constant parameters because of dynamic of platform and parallax effect. The parallax effect is caused by terrain relief, hence it causes local distortion between two bands. Therefore, the terrain relief correction in order to reduce the parallax effect is required for better registration result, especially for high resolution image data. Such terrain relief correction also can be applied to image data acquired from multiple detectors with different look angle within a band, which is a one of commonly used configuration for a wider swath in space-borne camera system, in order to reduce the distortion between detectors. The RFM is a popular abstract model in remote sensing field, which gives us the relationship between the image plane and geodetic coordinate system. Therefore, we propose a terrain relief correction method based on the RFM. The experiment showed very promising result.