• Asia Marketing Journal
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• v.10 no.4
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• pp.99-121
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• 2009

Social networks can be a powerful force in marketing because they provide new ways to market to young generation. Though many studies on evaluation of customer lifetime value have been conducted, it is not clear how to assess the value of members within social networks. The purpose of this study is to evaluate members based on customer intangible value as well as customer lifetime value. Customer network value in terms of the power and influence within a network is analyzed through network structure analysis. Using Cyworld log file data, this study have shown that high percentage of members are very influential in terms of spreading or withholding information even though their CLV is low. It is expected that the findings of this research contribute to understand the interactive behaviors of members within networks and to provide valuable implications on new product launching and customer management strategies to marketers.

• Information Systems Review
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• v.22 no.4
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• pp.75-92
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• 2020

As population and generation structures change, more and more customers tend to avoid facing relation due to the development of information technology and spread of smart phones. This phenomenon consists with efficiency and immediacy, which are the consumption patterns of modern customers who are used to information technology, so offline network-oriented distribution companies actively try to switch their sales and services to untact patterns. Recently, untact services are boosted in various fields, but beauty products are not easy to be recommended through untact services due to many options depending on skin types and conditions. There have been many studies on recommendations and development of recommendation systems in the online beauty field, but most of them are the ones that develop recommendation algorithm using survey or social data. In other words, there were not enough studies that classify segments based on user information such as skin types and product preference. Therefore, this study classifies customer segments using machine learning technique K-prototypesalgorithm based on customer information and search log data of mobile application, which is one of untact services in the beauty field, based on which, untact marketing strategy is suggested. This study expands the scope of the previous literature by classifying customer segments using the machine learning technique. This study is practically meaningful in that it classifies customer segments by reflecting new consumption trend of untact service, and based on this, it suggests a specific plan that can be used in untact services of the beauty field.

• Information Systems Review
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• v.22 no.2
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• pp.43-52
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• 2020

The mobile game industry has become the one of the fastest growing industries with its astonishing market size. Despite its industrial importance, a few studies empirically considered actual purchasing behavior in mobile games rather than the intention to purchase. Therefore, this paper investigates the key drivers of in-app purchase by analyzing the game-log dataset provided from a mobile game company in Korea. Specifically, the effects of goal-directed, habitual and social-interacted playing behavior are analyzed on in-app purchase. Furthermore, the recursive relationship with playing and purchasing behaviorsis also considered. The result shows that all suggested factors have positive impacts on in-app purchase in the current period. In addition, the effect of previous habitual playing has a positive impact, but the effect of social-interacted playing and in-app purchase in the previous period have negative impacts on in-app purchase of the current period. These findings can improve our understanding of the impact of game playing on in-app purchase in mobile games, and provide meaningful insights for researchers and practitioners.

• Information Systems Review
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• v.25 no.1
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• pp.111-128
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• 2023

With the development of artificial intelligence technology, interest in data-based product preference estimation and personalized recommender systems is increasing. However, if the recommendation is not suitable, there is a risk that it may reduce the purchase intention of the customer and even extend to a huge financial loss due to the characteristics of the financial product. Therefore, developing a recommender system that comprehensively reflects customer characteristics and product preferences is very important for business performance creation and response to compliance issues. In the case of financial products, product preference is clearly divided according to individual investment propensity and risk aversion, so it is necessary to provide customized recommendation service by utilizing accumulated customer data. In addition to using these customer behavioral characteristics and transaction history data, we intend to solve the cold-start problem of the recommender system, including customer demographic information, asset information, and stock holding information. Therefore, this study found that the model proposed deep learning-based collaborative filtering by deriving customer latent preferences through characteristic information such as customer investment propensity, transaction history, and financial product information based on customer transaction log records was the best. Based on the customer's financial investment mechanism, this study is meaningful in developing a service that recommends a high-priority group by establishing a recommendation model that derives expected preferences for untraded financial products through financial product transaction data.

• Information Systems Review
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• v.19 no.2
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• pp.115-136
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• 2017

Online communities have become substantial aspects of people's daily lives. However, only a few communities succeed and attract the majority of users, whereas the vast majority struggle for survival. When various communities coexist, important factors should be identified and examined to maintain attraction and achieve success. The concept of coexistence as been extensively explored in organizational ecology literature. However, given the similarities and differences between online communities and traditional organizations, the direct application of organizational theories to online contexts should be cautiously explored. In this study, we follow the roadmap proposed by Davis et al. (2007) in conducting agent-based modeling and simulation study to develop a novel theory based on the previous literature. In the case of two coexisting communities, we find that community size and participation costs can significantly affect the development of a community. A large community can attract a high number of active members who frequently log in. By contrast, low participation costs can encourage the reading and posting behaviors of members. We also observe the important influence of the distribution of interests on the topic trends of communities. A community composed of a population that focuses on only one topic can quickly converge on the topic regardless of whether the initial topic is broad or focused. This simulation model provides theoretical implications to literature and practical guidance to operators of online communities.

• Journal of Intelligence and Information Systems
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• v.19 no.2
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• pp.177-189
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• 2013

In Smart Education, the roles of digital textbook is very important as face-to-face media to learners. The standardization of digital textbook will promote the industrialization of digital textbook for contents providers and distributers as well as learner and instructors. In this study, the following three objectives-oriented digital textbooks are looking for ways to standardize. (1) digital textbooks should undertake the role of the media for blended learning which supports on-off classes, should be operating on common EPUB viewer without special dedicated viewer, should utilize the existing framework of the e-learning learning contents and learning management. The reason to consider the EPUB as the standard for digital textbooks is that digital textbooks don't need to specify antoher standard for the form of books, and can take advantage od industrial base with EPUB standards-rich content and distribution structure (2) digital textbooks should provide a low-cost open market service that are currently available as the standard open software (3) To provide appropriate learning feedback information to students, digital textbooks should provide a foundation which accumulates and manages all the learning activity information according to standard infrastructure for educational Big Data processing. In this study, the digital textbook in a smart education environment was referred to open digital textbook. The components of open digital textbooks service framework are (1) digital textbook terminals such as smart pad, smart TVs, smart phones, PC, etc., (2) digital textbooks platform to show and perform digital contents on digital textbook terminals, (3) learning contents repository, which exist on the cloud, maintains accredited learning, (4) App Store providing and distributing secondary learning contents and learning tools by learning contents developing companies, and (5) LMS as a learning support/management tool which on-site class teacher use for creating classroom instruction materials. In addition, locating all of the hardware and software implement a smart education service within the cloud must have take advantage of the cloud computing for efficient management and reducing expense. The open digital textbooks of smart education is consdered as providing e-book style interface of LMS to learners. In open digital textbooks, the representation of text, image, audio, video, equations, etc. is basic function. But painting, writing, problem solving, etc are beyond the capabilities of a simple e-book. The Communication of teacher-to-student, learner-to-learnert, tems-to-team is required by using the open digital textbook. To represent student demographics, portfolio information, and class information, the standard used in e-learning is desirable. To process learner tracking information about the activities of the learner for LMS(Learning Management System), open digital textbook must have the recording function and the commnincating function with LMS. DRM is a function for protecting various copyright. Currently DRMs of e-boook are controlled by the corresponding book viewer. If open digital textbook admitt DRM that is used in a variety of different DRM standards of various e-book viewer, the implementation of redundant features can be avoided. Security/privacy functions are required to protect information about the study or instruction from a third party UDL (Universal Design for Learning) is learning support function for those with disabilities have difficulty in learning courses. The open digital textbook, which is based on E-book standard EPUB 3.0, must (1) record the learning activity log information, and (2) communicate with the server to support the learning activity. While the recording function and the communication function, which is not determined on current standards, is implemented as a JavaScript and is utilized in the current EPUB 3.0 viewer, ths strategy of proposing such recording and communication functions as the next generation of e-book standard, or special standard (EPUB 3.0 for education) is needed. Future research in this study will implement open source program with the proposed open digital textbook standard and present a new educational services including Big Data analysis.

• The Korean Journal of Vision Science
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• v.20 no.4
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• pp.579-588
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• 2018

Purpose : To analyze the eyeglasses supply system for ametropic soldiers in ROK military. Methods : We investigated and analyzed the supply system of eyeglasses for the ametropic soldiers provided by the Korean military. The refractive powers and corrected visual acuity were measured for 37 ametropic soldiers who wear insert glasses for ballistic protective and gas-masks supplied by the military based on their habitual prescriptions. Full correction of refractive error was prescribed for subjects having less than 1.0 of distance visual acuity, and comparison was held for inspecting the changes in corrected visual acuity. Suggestions were provided for solving the issues regarding current supplying system, and this study investigated the applicabilities for utilizing professional optometric manpower. Results : The new glasses supplied by army for ametropic soldiers were duplicated from the glasses they worn when entering the army. The spherical equivalent refractive powers of the conventional, ballistic protective and gas-mask insert glasses supplied for 37 ametropic soldiers were $-3.47{\pm}1.69D$, $-3.52{\pm}1.66D$ and $-3.55{\pm}1.63D$, respectively, and the spherical equivalent refractive power of full corrected glasses was $-3.79{\pm}1.66D$, which showed a significant difference(p<0.05). The distant corrected visual acuity measured at high and low contrast(logMAR) of conventional, ballistic protective and gas-mask insert glasses were $0.06{\pm}0.80$, $0.21{\pm}0.82$, $0.15{\pm}0.74$, $0.34{\pm}0.89$, $0.10{\pm}0.70$ and $0.22{\pm}0.27$, respectively, while the corrected visual acuity by full corrected glasses were increased to $0.02{\pm}1.05$, $0.10{\pm}0.07$, $0.09{\pm}0.92$, $0.26{\pm}0.10$, $0.04{\pm}1.00$ and $0.19{\pm}1.00$, respectively. There was a significant difference(p<0.05) except for the case of the low contrast corrected visual acuity of the conventional and gas-mask insert glasses. The procedure for ordering, dispensing, and supplying military glasses consists of 5 steps, and it was found that approximately two weeks or more are required to supply from the initial examination. Conclusion : The procedure of supplying the military glasses showed three issues: 1) a lack of refraction for prescription system, 2) relatively long length of time required for supplying the glasses, 3) an inaccurate power of supplied glasses. In order to solve those issues, in the short term, education is necessarily required for soldiers on the measurement of the refractive powers, and in the near future, further standard procedures for prescription of glasses as well as the securement of optometric manpower are expected.

• Journal of Intelligence and Information Systems
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• v.17 no.4
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• pp.157-173
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• 2011

As the Internet use explodes recently, the malicious attacks and hacking for a system connected to network occur frequently. This means the fatal damage can be caused by these intrusions in the government agency, public office, and company operating various systems. For such reasons, there are growing interests and demand about the intrusion detection systems (IDS)-the security systems for detecting, identifying and responding to unauthorized or abnormal activities appropriately. The intrusion detection models that have been applied in conventional IDS are generally designed by modeling the experts' implicit knowledge on the network intrusions or the hackers' abnormal behaviors. These kinds of intrusion detection models perform well under the normal situations. However, they show poor performance when they meet a new or unknown pattern of the network attacks. For this reason, several recent studies try to adopt various artificial intelligence techniques, which can proactively respond to the unknown threats. Especially, artificial neural networks (ANNs) have popularly been applied in the prior studies because of its superior prediction accuracy. However, ANNs have some intrinsic limitations such as the risk of overfitting, the requirement of the large sample size, and the lack of understanding the prediction process (i.e. black box theory). As a result, the most recent studies on IDS have started to adopt support vector machine (SVM), the classification technique that is more stable and powerful compared to ANNs. SVM is known as a relatively high predictive power and generalization capability. Under this background, this study proposes a novel intelligent intrusion detection model that uses SVM as the classification model in order to improve the predictive ability of IDS. Also, our model is designed to consider the asymmetric error cost by optimizing the classification threshold. Generally, there are two common forms of errors in intrusion detection. The first error type is the False-Positive Error (FPE). In the case of FPE, the wrong judgment on it may result in the unnecessary fixation. The second error type is the False-Negative Error (FNE) that mainly misjudges the malware of the program as normal. Compared to FPE, FNE is more fatal. Thus, when considering total cost of misclassification in IDS, it is more reasonable to assign heavier weights on FNE rather than FPE. Therefore, we designed our proposed intrusion detection model to optimize the classification threshold in order to minimize the total misclassification cost. In this case, conventional SVM cannot be applied because it is designed to generate discrete output (i.e. a class). To resolve this problem, we used the revised SVM technique proposed by Platt(2000), which is able to generate the probability estimate. To validate the practical applicability of our model, we applied it to the real-world dataset for network intrusion detection. The experimental dataset was collected from the IDS sensor of an official institution in Korea from January to June 2010. We collected 15,000 log data in total, and selected 1,000 samples from them by using random sampling method. In addition, the SVM model was compared with the logistic regression (LOGIT), decision trees (DT), and ANN to confirm the superiority of the proposed model. LOGIT and DT was experimented using PASW Statistics v18.0, and ANN was experimented using Neuroshell 4.0. For SVM, LIBSVM v2.90-a freeware for training SVM classifier-was used. Empirical results showed that our proposed model based on SVM outperformed all the other comparative models in detecting network intrusions from the accuracy perspective. They also showed that our model reduced the total misclassification cost compared to the ANN-based intrusion detection model. As a result, it is expected that the intrusion detection model proposed in this paper would not only enhance the performance of IDS, but also lead to better management of FNE.

• Journal of Korean Society of Rural Planning
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• v.24 no.3
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• pp.87-96
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• 2018

While cities became bigger and bigger since 1990s, many indiscretely high buildings started to be built in the mountain areas inside a city and in the rural areas in the suburb of each city. To regulate such indiscrete developments, the government prepared for some relevant legal and institutional criteria by having enacted the "Landscape Act" and established a strong management means in the legal and institutional aspects by having introduced the natural landscape deliberation system and the landscape deliberation one into the "Natural Environment Conservation Act." However, since some uniform levels of absolute height and no. of stories are suggested legally and institutionally, it is hard to consider the effects of a real building structure onto the relevant landscape. Accordingly, this thesis is intended to grasp the contrast of the landscape elements in the allowable height section, which is presented through landscape sensitivity. As the results from the visual contrast rating on a small apartment complex located in Dangjin and a large scale of apartment complex in Seosan as the apartment complexes surrounded with natural landscapes that were selected as the subjects of this study, the following conclusion can be finalized. First, there were deducted some factors, that is, forms, lines, colors, textures and sizes as the ones with which can measure and evaluate the contrasting properties when a structure gets into a natural landscape. Second, in case of a small scale of apartment complex (in the foreground) compared to a large one (in the foreground), it was found that the contrasting properties were bigger. In addition, it was also found that the contrasting property of the landscape factor of the foreground compared to that of the middle one becomes bigger depending on a distance. Third, as the results from an evaluation on the contrasting properties of the landscape factor depending on the changes of each floor of a structure, it was found that the factors, that is, forms, lines, colors, textures and sizes are very significant. Among those factors, the factors, forms and lines in a small scale of apartment complex (in the foreground) showed each log regression. But in all of the other cases, they showed each line regression. Fourth, as the results from examining the regression coefficients of the landscape factor, the coefficients of the shapes and lines have similar coefficients and the colors and the textures have similar ones, too. In case of the sizes of apartment complexes, the colors and the textures of a large apartment complex (in the foreground) have similar coefficients, in case of that in the middle ground, the shapes and lines have similar coefficients. Fifth, as the results from estimating the contrasting properties of the landscape factor on the floors within the allowed scope of the landscape sensitivity, it was found that the contrasting property was 3.5 to 4.9 in case of a small scale of apartment complex (in the foreground), but 2.5to 3.7 in case of a small scale of one. In case of a large scale of apartment complex, the value was 3.5 to 5.3, but in case of a large one in the middle ground was 2.9 to 4.9. Sixth, it was comprehended that the contrasting properties of the landscape factor become different depending on each size of apartment complex and the distance of a view point. In this study, it is intended to find the meaning from the aspect that the results can be used as the baseline data for comprehending a proper range of heights of structures objectively during a natural landscape deliberation or a landscape deliberation.

• Tuberculosis and Respiratory Diseases
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• v.41 no.3
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• pp.270-276
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• 1994

Background: The measurement of nonspecific bronchial hyperreactivity is valuable for diagnosis and management of bronchial asthma. Methacholine or histamine is used for the pharmacologic provocation test. Usually a methacholine bronchial provocation test is performed by a dosing technique with counted number of breaths. A dosimeter is indispensable in the dosing technique. Recently a timed tidal breathing technique which dose not need an expensive dosimeter was introduced. We measured the degree of nonspecific bronchial hyperreactivity to histamine using a simple timed tidal breathing technique. Method: Forty two healthy volunteers, 12 patients with bronchial asthma(BA), 10 patients with rhinitis(RH) and 10 patients with upper respiratory infection(URI) participated in the study. The subject's nose was clipped and inhalation continued during tidal breathing for 2 minutes via a face mask. $FEV_1$ was measured at 30 seconds, 90 seconds after inhalation and inhalation of next solution was continued until there was a fall in $FEV_1$ of 20%. Histamine PC20 was defined as the concentration at 20% fall of $FEV_1$ and it was obtained from the log dose-response curve by linear interpolation. Results: Inhalation of serial dilution of histamine could be performed in all patients without significant side effects. The geometric mean${\pm}$standard deviation of histamine PC20 in healthy volunteers is $8.27{\pm}2.22mg/ml$, BA group $0.33{\pm}3.02mg/ml$, RH group $0.85{\pm}3.24mg/ml$, and URI group $1.47{\pm}1.98mg/ml$. Conclusion: Histamine bronchial provocation test using timed tidal breath method is a simple and suitable tool for management of patients with bronchial hyperreactivity.