• 한국경영정보학회:학술대회논문집
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• 2008.06a
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• pp.428-433
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• 2008

The online advertising industry's business model undertakes the change from CPM (cost-per-mille)-based to CPC (cost-per-click)-based. However, due to the problem of 'Click Fraud', CPA (cost-per-action) has been regarded as a new step. For CPA, publishers need to get information after a user clicks an advertisement. Therefore, in CPA, the key is to get Conversion Action Data (CAD). This paper introduces two existing mechanisms for getting CAD, compare their characteristics, and analyze their limitations. Then the two new mechanisms are introduced and their requirements and feasibility are analyzed. Lastly, we compare the existing two and the new two mechanisms, and point out each mechanism's business possibility, value and Application Area. This paper will help publishers choose the most appropriate mechanism on the basis of their situation.

• Asia pacific journal of information systems
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• v.16 no.2
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• pp.69-84
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• 2006

Importance of Today's diffusion of integrated hospital information systems is that various and huge amount of data is being accumulated in their database systems. Many researchers have studied utilizing such hospital data. While most researches were conducted mainly for medical diagnosis, there have been insufficient studies to develop medical care cost prediction model, especially using machine learning techniques. In this research, therefore, we built a medical care cost prediction model for cancer patients using CBR (Case-Based Reasoning), one of the machine learning techniques. Its performance was compared with those of Neural Networks and Decision Tree models. As a result of the experiment, the CBR prediction model was shown to be the best in general with respect to error rate and linearity between real values and predicted values. It is believed that the medical care cost prediction model can be utilized for the effective management of limited resources in hospitals.

• International conference on construction engineering and project management
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• 2015.10a
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• pp.660-661
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• 2015

Building Information Modeling (BIM) is a nascent technology in Korea, and currently lacks formal guidelines to assist Architectural and Engineering (AE) firms in estimating BIM service fees, while also allowing government agencies to allocate budgets for the rendered BIM services. This research provides a method to estimate costs for BIM services based on the cost-plus pricing framework. The approach requires a generalized estimate of the man hour per floor area data to calculate the direct labor costs. Man-hour data were collected from forty five projects that have implemented BIM. Interpolation of the man-hours was performed to develop a general reference table for 'Type 2' (i.e., public schools and office buildings, etc.) projects. By providing an objective approach for estimating the costs of BIM services, it allows clients and AE firms to agree upon a fair cost for BIM related services, and thus expedite its adoption in Korea.

• Journal of the Korea Institute of Building Construction
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• v.14 no.5
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• pp.477-485
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• 2014

Standard production unit system and historical cost data are the most typical data base for calculating budget price in construction. However, these construction cost estimation methods are difficult to calculate proper construction cost because definition, additional allowance or modification criteria is not clear in construction within one day. Therefore, this study identifies problems for standard production unit system and historical cost data and suggests the improvements for them. For the objectives, this study analyzes frequency after implementing survey for 44 specialty contractors in placing at kyeonggi-province. As the results of the study, labor costs in standard production unit system and equipment costs in historical cost data and in construction of pavement and maintenance by project type was exceeded at most high rate against construction cost estimation methods. Based on this result, standard production unit system and historical cost data need to be modified by three improvements such as classification by project scale. These will be baseline data for improvement of construction cost estimation methods for less than one day workload.

• Journal of Information Technology Services
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• v.17 no.3
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• pp.1-16
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• 2018

There exist a number of studies pertaining to the determinants of customer satisfaction between low-cost and full-service carriers in the airline industry. Most studies measured service quality using SERVQUAL based on a survey method. This study offers a new perspective by employing a big data analytic approach using SNS data, which reflects the immediate response of customers as well as trends in real time. This study chose eight factors from TripAdvisor's customer review site as determinants of customer satisfaction and compared the differences between low-cost and full-service airlines. The factors analyzed were seat comfort, customer service, cleanliness, food and beverage, legroom, entertainment, value for money, and check-in and boarding. Additionally, ratings from domestic and foreign customers were compared. The findings show that customer service and value for money are significant factors in satisfaction with low-cost airlines while all variables except legroom and entertainment are significant for full-service airlines. The results show that SNS-based data and analysis of big data are important for improving decision-making effectiveness and increasing customer satisfaction in the airline industry.

• Journal of Construction Engineering and Project Management
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• v.5 no.1
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• pp.26-31
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• 2015

Success of the construction companies is based on the successful completion of projects within the agreed cost and time limits. Artificial neural networks (ANN) have recently attracted much attention because of their ability to solve the qualitative and quantitative problems faced in the construction industry. For the estimation of cost and duration different ANN models were developed. The database consists of data collected from completed projects. The same data is normalised and used as inputs and targets for developing ANN models. The models are trained, tested and validated using MATLAB R2013a Software. The results obtained are the ANN predicted outputs which are compared with the actual data, from which deviation is calculated. For this purpose, two successfully completed highway road projects are considered. The Nftool (Neural network fitting tool) and Nntool (Neural network/ Data Manager) approaches are used in this study. Using Nftool with trainlm as training function and Nntool with trainbr as the training function, both the Projects A and B have been carried out. Statistical analysis is carried out for the developed models. The application of neural networks when forming a preliminary estimate, would reduce the time and cost of data processing. It helps the contractor to take the decision much easier.

• Journal of Families and Better Life
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• v.15 no.4
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• pp.103-124
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• 1997

The purpose of this study was to analyze marriage cost planning and marriage cost for the children. Data were obtained from 306 households with at least one child married within past 5 years in Seoul. There were significant differences in marriage cost planning. The average marriage cost was 46,410,000won. Earned income finance asset child's sex child's marriage type the length of planning whether debts were incurred or not and whether the property was sold for child's marriage were significantly associated with the marriage cost. Finally socio-economic variable and marriage cost planning variables played more imprtant role in determining child's marriage cost than child related variables.

• Korean Management Science Review
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• v.23 no.2
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• pp.75-91
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• 2006

The purpose of this paper is to propose a new software development cost estimation method using SVR(Support Vector Regression) SVR, one of machine learning techniques, has been attracting much attention for its theoretic clearness and food performance over other machine learning techniques. This paper may be the first study in which SVR is applied to the field of software cost estimation. To derive the new method, we analyze historical cost data including both well-known overseas and domestic software projects, and define cost drivers affecting software cost. Then, the SVR model is trained using the historical data and its estimation accuracy is compared with that of the linear regression model. Experimental results show that the SVR model produces more accurate prediction than the linear regression model.

• Proceedings of the Korean Institute of Building Construction Conference
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• 2011.11a
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• pp.17-18
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• 2011

Over the past 20 years, Researchers have tried to develop "Integration Model of Cost and Schedule" in construction industry. They suggested various models and techniques, however, it is still required to develop new methodology for AL Form Work in Public Multi-Housing Projects. Accordingly, this research focused on measuring quantity take-offs of on-going projects and analysing the basic process of using the resources(Labor, Material, Plant) related to cost and time data. There are 3 steps of this research : 1) The literature review of previous studies about Integration Model of Cost and Schedule was conducted. 2) Model for integration between cost and schedule was developed. 3) the accuracy of developed model was verified. The results are expected to improve in integrated managing the cost and schedule data of AL form work.

• Journal of Industrial Technology
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• v.26 no.B
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• pp.207-213
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• 2006

Mobility Anchor points are used for the mobility management in HMIPv6 networks. Currently a mobile node selects the MAP farthest away from itself as a new MAP among available candidates when it undertakes a macro hand off. With this technique, however, the traffic tends to be concentrated at a MAP with the largest domain size and the communication cost increases due to the distance between the mobile node and the MAP. In this work, we propose a novel scheme to select a MAP to minimize the communication cost, taking the mobile node's moving speed and data rate into account. To come up with the scheme we analyses the communication analyses the communication cost into the binding update cost and the data packet delivery cost, and derive an equation representing the optimal MAP domain size to minimize the total cost.