• Journal of the Korean Home Economics Association
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• v.41 no.8
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• pp.19-31
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• 2003

This study was intended to present the plan for preventing and solving the seriousness of the consumer problem perceived in the e-commerce. For this purpose, 723 questionnaires were distributed to university As a result of analysis, the following findings were obtained: 1) It was found that e-commerce users had higher knowledge of the degree of internet un, the ability to use information on the internet, the disposition of computerization, and e-commerce related consumer than e-commerce non-users. 2) It was found that e-commerce non-users had the higher level of perceived seriousness of the consumer problem than e-commerce users. Especially, it was found that e-commerce non-users had the high level of perceived seriousness of the consumer problem related to the problem of exchange, termination and after-sale nice and the leakage of exchange, termination and after-sale service and the leakage of private information e-commerce user. 3) It was found that university consumers' perceived seriousness of the consumer problem in e-commerce over the internet showed a significant difference in the ability to use information on the internet between e-commerce users and non-users.

• Journal of Korean Academy of Nursing
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• v.48 no.2
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• pp.195-207
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• 2018

Purpose: The purpose of the study was to develop and test a model for predicting problem gambling in speculative game users based on Blaszczynski and Nower's pathways model of problem and pathological gambling. Methods: The participants were 262 speculative game users recruited from seven speculative gambling places located in Seoul, Gangwon, and Gyeonggi, Korea. They completed a structured self-report questionnaire comprising measures of problem gambling, negative emotions, attentional impulsivity, motor impulsivity, non-planning impulsivity, gambler's fallacy, and gambling self-efficacy. Structural Equation Modeling was used to test the hypothesized model and to examine the direct and indirect effects on problem gambling in speculative game users using SPSS 22.0 and AMOS 20.0 programs. Results: The hypothetical research model provided a reasonable fit to the data. Negative emotions, motor impulsivity, gambler's fallacy, and gambling self-efficacy had direct effects on problem gambling in speculative game users, while indirect effects were reported for negative emotions, motor impulsivity, and gambler's fallacy. These predictors explained 75.2% problem gambling in speculative game users. Conclusion: The findings suggest that developing intervention programs to reduce negative emotions, motor impulsivity, and gambler's fallacy, and to increase gambling self-efficacy in speculative game users are needed to prevent their problem gambling.

• Journal of Information Processing Systems
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• v.15 no.3
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• pp.616-631
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• 2019

With the rapid increase of information on the World Wide Web, finding useful information on the internet has become a major problem. The recommendation system helps users make decisions in complex data areas where the amount of data available is large. There are many methods that have been proposed in the recommender system. Collaborative filtering is a popular method widely used in the recommendation system. However, collaborative filtering methods still have some problems, namely cold-start problem. In this paper, we propose a movie recommendation system by using social network analysis and collaborative filtering to solve this problem associated with collaborative filtering methods. We applied personal propensity of users such as age, gender, and occupation to make relationship matrix between users, and the relationship matrix is applied to cluster user by using community detection based on edge betweenness centrality. Then the recommended system will suggest movies which were previously interested by users in the group to new users. We show shown that the proposed method is a very efficient method using mean absolute error.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.15 no.6
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• pp.2069-2085
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• 2021

A Social Networking Service (SNS) platform provides digital footprints to discover users' interests and track the social diffusion of product adoptions. How to identify a small set of seed users in a SNS who is potential to adopt a new promoting product with high probability, is a key question in social networks. Existing works approached this as a social influence maximization problem. However, these approaches relied heavily on text information for topic modeling and neglected the impact of seed users' relation in the model. To this end, in this paper, we first develop a general product adoption function integrating both users' interest and social influence, where the user interest model relies on historical user behavior and the seed users' evaluations without any text information. Accordingly, we formulate a product adoption maximization problem and prove NP-hardness of this problem. We then design an efficient algorithm to solve this problem. We further devise a method to automatically learn the parameter in the proposed adoption function from users' past behaviors. Finally, experimental results show the soundness of our proposed adoption decision function and the effectiveness of the proposed seed selection method for product adoption maximization.

• Journal of information and communication convergence engineering
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• v.7 no.2
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• pp.148-151
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• 2009

We consider the problem of optimizing the performance of a system with resources shared by non-cooperative users. The worst-cast ratio between the cost of a Nash equilibrium and the optimal cost, called Price of Anarchy, is investigated. It measures the performance degradation due to the users' selfish behavior. As the objective function of the optimization problem, we are concerned in a load balancing measure, which is different from that used in the previous works. Also we consider the Stackelberg scheduling which can assign a fraction of the users to resources while the remaining users are free to act in a selfish manner.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.33 no.1B
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• pp.8-15
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• 2008

Cognitive radio technology enables to share the spectrum dedicated to primary users. In CR network, it is of primary concern to protect the primary users. Thus, it is required to periodically sense the spectrums occupied by primary users and adapt the communication parameters used by CR users to protect the primary users. However, it is inevitable to experience the hidden node problem due to the primary users, that are not detected by spectrum sensing. To perfectly protect the primary users, it is essential to address the hidden node problem in CR network. In this paper, we propose a new approach to handle the hidden node problem and evaluate the performance of proposed scheme.

• Journal of Korean Institute of Industrial Engineers
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• v.35 no.1
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• pp.87-91
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• 2009

In the server disconnection problem, a network with m servers and their users is given and an attacker is to destroy a set of edges to maximize his net gain defined as the total disconnected utilities of the users minus the total edge-destruction cost. The problem is known to be NP-hard. In this paper, we study the server disconnection problem restricted to a ring network. We present an efficient combinatorial algorithm that generates an optimal solution in polynomial time.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.6 no.5
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• pp.1286-1302
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• 2012

In this paper, the resource allocation problem with proportional fairness rate in cognitive OFDM-based wireless network is studied. It aims to maximize the total system throughput subject to constraints that include total transmit power for secondary users, maximum tolerable interferences of primary users, bit error rate, and proportional fairness rate among secondary users. It is a nonlinear optimization problem, for which obtaining the optimal solution is known to be NP-hard. An efficient bio-inspired suboptimal algorithm called immune clonal optimization is proposed to solve the resource allocation problem in two steps. That is, subcarriers are firstly allocated to secondary users assuming equal power assignment and then the power allocation is performed with an improved immune clonal algorithm. Suitable immune operators such as matrix encoding and adaptive mutation are designed for resource allocation problem. Simulation results show that the proposed algorithm achieves near-optimal throughput and more satisfying proportional fairness rate among secondary users with lower computational complexity.

• The Journal of the Convergence on Culture Technology
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• v.9 no.6
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• pp.187-192
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• 2023

A problem user in a library refers to a person who harasses others or causes a disturbance through inappropriate behavior in the library. Users' continued problematic behavior reduces the work productivity of librarians and at the same time causes inconvenience to other users. This may cause a decline in the free use of public libraries. In Korea, a user response manual has been developed to guide librarians to respond wisely to user problem behavior. However, it is true that most of the content provides guidance on how to communicate with problem users, and there is a lack of countermeasures to stipulate and regulate follow-up measures against them. The goal of this study is to further systematize response and organize them into written regulations. To this end, this study to examine regulations and legal battles surrounding problem users in oversea public libraries and to examine what can be applied in Korea in the future.

• Journal of Korea Multimedia Society
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• v.14 no.12
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• pp.1549-1558
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• 2011

In this paper, we address the problem of bandwidth sharing among multiple primary users and multiple secondary users in a cognitive radio network. In cognitive radio networks, effective spectrum assignment for primary and secondary users is a challenge due to the available broad range of radio frequency spectrum as well as the requisition of harmonious coexistence of both users. To handle this problem, firstly, Bertrand game model is used to analyze a spectrum pricing in which multiple primary users emulate with each other to acquire maximal profit. After that, we employ Cournot game to model the spectrum sharing of secondary users to obtain optimal profit for each user also. Simulation results show that our scheme obtains optimal solution at Nash equilibrium.