• Journal of the Korea Society of Computer and Information
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• v.15 no.6
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• pp.121-128
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• 2010

Spatial data mining has been developed to support spatial association knowledge between spatial features or its non-spatial attributes for an application areas. At the present time, a number of researchers attempt to the data mining techniques apply to the several analysis areas, for examples, civil engineering, environmental, agricultural areas. Despite the efforts that, until such time as not existed practical systems for the gCRMDMs. gCRMDMs is merged with very large spatial database and CRM information system. Also, it is discovery the association rule for the predictions of customer's shopping pattern informations in a huge database consisted with spatial and non-spatial dataset. For this goal, gCRMDMs need spatial data mining techniques. But, nowadays, in a most case not exist utilizable model for the gCRMDMs. Therefore, in this paper, we proposed a practical gCRMDMs model to support a customer, store, street, building and geographical suited to the trade area.

• Smart Media Journal
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• v.12 no.5
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• pp.9-16
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• 2023

In the recommendation system of the credit card company, it is necessary to understand the customer patterns to predict a customer's next merchant based on their histories. The data we want to model is much more complex and there are various patterns that customers choose. In such a situation, it is necessary to use an effective model that not only shows the relevance of the merchants, but also the relevance of the customers relative to these merchants. The proposed model aims to predict the next merchant for the customer. To improve prediction performance, we propose a novel model, called Customer-based Recommendation Model (CRM), to produce a more efficient representation of customers. For the next merchant recommendation system, we use a synthetic credit card usage dataset, BC'17. To demonstrate the applicability of the proposed model, we also apply it to the next item recommendation with another real-world transaction dataset, IJCAI'16.

• The Journal of the Korea Contents Association
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• v.19 no.7
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• pp.376-383
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• 2019

In recent decades, China's economy has grown rapidly and two-dimensional bar code-based payments services have been activated. This is a model that will be introduced by developing countries that lack mobile payment infrastructure, and countries that are looking to leap into cashless societies are also drawing attention. Along with this, the existing CRM market is expanding around the mobile device called m-CRM, and research is active on the importance of collective use for online advertising and two-dimensional bar code-based payments services. Therefore, through this study, we have explored the concepts and status of online advertising and customer relationship management which using the two-dimensional bar code-based system, and designed and implemented the method and mobile application system to effectively disseminate transactional advertising information at the point of sale or at the point of share. We also presented an application approach to look at the direction of two-dimensional bar code-based ads contents sharing system and its development.

• Proceedings of the Korea Water Resources Association Conference
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• 2009.05a
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• pp.149-153
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• 2009

Physics-based distributed rainfall-runoff models are now commonly used in a variety of hydrologic applications such as to estimate flooding, water pollutant transport, sedimentation yield and so on. Moreover, it is not surprising that GIS has become an integral part of hydrologic research since this technology offers abundant information about spatial heterogeneity for both model parameters and input data that control hydrological processes. This study presents the development of a distributed rainfall-runoff prediction system for the Guem river basin ($9,835km^2$) using an Object-oriented Hydrological Modeling System (OHyMoS). We developed three types of element modules: Slope Runoff Module (SRM), Channel Routing Module (CRM), and Dam Reservoir Module (DRM) and then incorporated them systemically into a catchment modeling system under the OHyMoS. The study basin delineated by the 250m DEM (resampled from SRTM90) was divided into 14 midsize catchments and 80 sub-catchments where correspond to the WAMIS digital map. Each sub-catchment was represented by rectangular slope and channel components; water flows among these components were simulated by both SRM and CRM. In addition, outflows of two multi-purpose dams: Yongdam and Daechung dams were calculated by DRM reflecting decision makers' opinions. Therefore, the Guem river basin rainfall-runoff modeling system can provide not only each sub-catchment outflow but also dam inand outflow at one hour (or less) time step such that users can obtain comprehensive hydrological information readily for the effective and efficient flood control during a flood season.

• Journal of Advanced Navigation Technology
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• v.27 no.5
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• pp.528-533
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• 2023

Airlines tried to introduce training programs in connection with practical work in order to provide more effective education and training. To this end, airlines have been conducting evidence-based training(EBT) to strengthen the practical capabilities of aviation personnel and enhance safety culture. Airlines can systematically evaluate the capabilities and practical capabilities of aviation personnel by analyzing operational data and case studies for effective EBT model development. In addition, EBT models can be constructed by applying technical methods such as crew resource management (CRM) and a holistic approach that includes human factors. Due to the introduction of EBT, airlines will establish diagnostic and feedback systems for pilots' practical work, provide personalized education, and establish an education and training system that verifies the effectiveness of education through educational outcomes.

• Journal of Information Technology Applications and Management
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• v.25 no.2
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• pp.73-90
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• 2018

Despite of increasing studies for product recommendation, the recommendation of product repurchase timing has not yet been studied actively. This study aims to propose deep neural network models usingsimple purchase history data to predict the repurchase timing of each customer and compare performances of the models from the perspective of prediction quality, including expected ROI of promotion, variability of precision and recall, and diversity of target selection for promotion. As an experiment result, a recurrent neural network (RNN) model showed higher promotion ROI and the smaller variability compared to MLP and other models. The proposed model can be used to develop a CRM system that can offer SMS or app-based promotionsto the customer at the right time. This model can also be used to increase sales for product repurchase businesses by balancing the level of ordersas well as inducing repurchases by customers.

• Journal of Korea Society of Industrial Information Systems
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• v.15 no.5
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• pp.79-87
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• 2010

This paper is proposed that implemental model of customer relationship management system for oriental hospital is designed by customer segmentation using personal information and medical record of outpatients in existing integrated medical information system database. Proposed model can be practical model at once, because it can construct by partial modification of existing medical information system without additional information technology and infrastructure. And, if we use the proper variable and method of customer segmentation according to marketing strategy, it can be flexible customer relationship management system not only improvement of customer satisfaction but also various marketing supports.

• Journal of Intelligence and Information Systems
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• v.7 no.1
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• pp.17-25
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• 2001

Tree model is the most popular classification algorithm in data mining due to easy interpretation of the result. In CART(Breiman et al., 1984) and C4.5(Quinlan, 1993) which are representative of tree algorithms, the split fur classification proceeds to attain the homogeneous terminal nodes with respect to the composition of levels in target variable. But, fur instance, in the chum prediction modeling fur CRM(Customer Relationship management), the rate of churn is generally very low although we are interested in mining the churners. Thus it is difficult to get accurate prediction modes using tree model based on the traditional split rule, such as mini or deviance. Buja and Lee(1999) introduced a new split rule, one-sided purity for classifying minor interesting group. In this paper, we compared one-sided purity with traditional split rule, deviance analyzing churning vs. non-churning data of ISP company. Also reviewing the result of tree model based on one-sided purity with some simulated data, we discussed problems and researchable topics.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.20 no.8
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• pp.1460-1465
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• 2016

Lots of costs threaten the sustainability of the national health-guarantee system. Despite research by the national center for disease control and prevention on health care dynamics with its auditing systems, there are still restrictions of time limitation, sample limitation, and, target diseases limitation. Against this backdrop, using huge volume of total data, many technologies could be fully adopted to the preliminary forecasting and its target-disease expanding of health. With structured data from the national health insurance and unstructured data from the social network service, we attempted to design a model to predict disease. The model can enhance national health and maximize social benefit by providing a health warning service. Also, the model can reduce the advent increase of national health cost and predict timely disease occurrence based on Big Data analysis. We researched related medical prediction cases and performed an experiment with a pilot project so as to verify the proposed model.

• Journal of the Korean Data and Information Science Society
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• v.21 no.2
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• pp.251-262
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• 2010

While outsourcing has become a basic strategy of the information system adoption, there is an emerging needs to analyze the gap between the required data and the existing data for the new system from an adopting company's perspective. In CRM adoption failure cases, the first reason is adopting company pay no attention to the data that will support investment and systems. So far, there is no attempt to consider data driven approach in information system adoption field. Hence, we propose Information System Adoption Model based on Data (ISAMD) and show how to use in real world by simulation. By using ISAMD, information system adoption decision maker can simulate the needed data and related cost with various information system alternatives in short term, and long term planning. ISAMD can prevent the possible threat of unexpected data cost in adopting new system at the adopting decision stage.