• Knowledge Management Research
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• v.10 no.2
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• pp.15-33
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• 2009

Telecommunications-broadcasting convergence in the domain of IT is a representative phenomenon that is expected to provide the saturated existing markets with a new source of profit. Especially, T-Commerce combines familiarity of TV and immediacy of the Internet which are expected to cover all the users familiar with each media and expand the existing commercial transactions. Telecommunications-broadcasting convergence in Korea, however, is focusing on technical and regulatory aspects so that research on the real users is not up to the mark yet. This is the most fundamental problem in hampering growth in the corresponding service and market. Thus, we are proposing an adoption model on T-Commerce to rapidly expand the convergence service through understanding the potential users. Perceived utilitarian and hedonic values, perceived interactivity, media substitution and personal innovativeness have been examined as the factors influencing the users' intention to adopt a new convergence service. As a result of empirical analysis, it is verified that perceived utilitarian and hedonic values and personal innovativeness directly influenced the users' intention to adopt whereas perceived interactivity had indirect affect on them. T-Commerce service providers should not only emphasize on the benefit that the older media could not provide the users with, but also provide them with more pleasure and entertaining experience during the course of satisfying the users' needs to distinguish T-Commerce from the other existing media.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.16 no.4
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• pp.1351-1372
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• 2022

A self-organizing multiple unmanned aerial vehicles (multi-UAVs) deployment based on virtual forces has a difficulty in ensuring the quality-of-experience (QoE) of users because of the difference between the assumed center for users in a hotspot and an actual center for users in the hotspot. This discrepancy is aggravated in a non-uniform and mobile user distribution. To address this problem, we propose a new density based virtual force (D-VF) multi-UAVs deployment algorithm which employs a mean opinion score (MOS) as a metric of QoE. Because MOS is based on signal-to-noise ratio (SNR), a sum of users' MOS is a good metric not only to secure a wide service area but to enhance the link quality between multi-UAVs and users. The proposed algorithm improves users' QoE by combining virtual forces with a random search force for the exploration of finding multi-UAVs' positions which maximize the sum of users' MOS. In simulation results, the proposed deployment algorithm shows the convergence of the multi-UAVs into the position of maximizing MOS. Therefore, the proposed algorithm outperforms the conventional virtual force-based deployment scheme in terms of QoE for non-uniform user distribution scenarios.

• Industrial Engineering and Management Systems
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• v.13 no.4
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• pp.421-431
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• 2014

The market basket data in the form of a binary user-item matrix or a binary item-user matrix can be modelled as a binary classification problem. The binary logistic regression approach tackles the binary classification problem, where principal components are predictor variables. If users or items are sparse in the training data, the binary classification problem can be considered as a cold-start problem. The binary logistic regression approach may not function appropriately if the principal components are inefficient for the cold-start problem. Assuming that the market basket data can also be considered as a special regression problem whose response is either 0 or 1, we propose three supervised learning approaches: random forest regression, random forest classification, and elastic net to tackle the cold-start problem, comparing the performance in a variety of experimental settings. The experimental results show that the proposed supervised learning approaches outperform the conventional approaches.

• Journal of Computing Science and Engineering
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• v.4 no.2
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• pp.173-187
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• 2010

Recent technological advances in mobile communication systems have made explosive growth in the number of mobile device users worldwide. One of the most important issues in designing a mobile computing system is location management of users. The hierarchical systems had been proposed to solve the scalability problem in location management. The scalability problem occurs when there are too many users for a mobile system to handle, as the system is likely to react slow or even get down due to late updates of the location databases. In this paper, we propose a top-down clustering algorithm for hierarchical location database systems in a wireless network. A hierarchical location database system employs a tree structure. The proposed algorithm uses a top-down approach and utilizes the number of visits to each cell made by the users along with the movement information between a pair of adjacent cells. We then present a modified algorithm by incorporating the exhaustive method when there remain a few levels of the tree to be processed. We also propose a capacity constraint top-down clustering algorithm for more realistic environments where a database has a capacity limit. By the capacity of a database we mean the maximum number of mobile device users in the cells that can be handled by the database. This algorithm reduces a number of databases used for the system and improves the update performance. The experimental results show that the proposed, top-down, modified top-down, and capacity constraint top-down clustering algorithms reduce the update cost by 17.0%, 18.0%, 24.1%, the update time by about 43.0%, 39.0%, 42.3%, respectively. The capacity constraint algorithm reduces the average number of databases used for the system by 23.9% over other algorithms.

• The Journal of Information Systems
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• v.33 no.1
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• pp.1-30
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• 2024

Purpose The purpose of this study is to examine the customer experience of generative AI among office workers aged 30 to 40, investigating usability, usefulness, and affect, and understanding concerns and expectations. Design/Methodology/Approach This research used Q methodology to assess the customer experience of generative AI. Users are engaged in a problem-solving journey, and data is collected by having participants rank 36 statements based on usability, usefulness, and affect, referred to as the three goals of User Experience. Participants use a forced distribution table with a scale from -5 to +5 to indicate the subjective importance of each statement. The results identified four groups, reflecting different perspectives and attitudes toward generative AI. Findings Participants express overall comfort with generative AI, perceive AI as more knowledgeable in unfamiliar domains, but harbor doubts about AI's understanding. Disagreements emerge on AI replacing humans, the value of unique human roles, data confidentiality, fears of AI advancement, and emotional impacts. Identified four groups: Users who treat AI as a soulless assistant and are active in business use, Uncle users who want to use new technologies properly and are not afraid of technology, users who recognize the limits of AI despite its efficiency, and users who require strong verification in the future. It has the potential to guide future guidelines, ethical codes, and regulations for the appropriate use of AI. In addition, this approach lays the groundwork for future empirical analyses of generative AI.

• IE interfaces
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• v.5 no.2
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• pp.75-85
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• 1992

A common problem for manufacturing industries, especially consumer goods industries, is how to establish standardized procedures for loading finished goods onto pallets or containers for subsequent storage and distribution. Utilizing previous research results on the palletizing problem, this paper develops micro-computer based programs which generate an optimum loading pattern leading to the minimum amount of unused pallet or container space. Development of pallet layout chart is also included in the computer programs. The results are displayed by computer-graphic. For the users who are unfamiliar with pallet loading problem and computer system, pull-down menu and user-computer interactive data input procedures are adopted.

• Journal of the Korea Society of Computer and Information
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• v.21 no.10
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• pp.37-42
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• 2016

We investigate multi user joint rate scheduling and power allocation problem for a delay sensitive CDMA systems. First, we characterize the existing two user joint rate scheduling and power allocation. We then extend the problem to the case of the multi user systems. In general, there is no simple optimum solution for the multi user scheduling problem. To that end, we propose a sub optimum solution, termed 'virtual user approach'. We show the performance of the virtual user approach to verify the benefit of complexity.

• Journal of Information Technology Applications and Management
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• v.12 no.4
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• pp.45-57
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• 2005

In order to provide personalized knowledge recommendation services, most web portals for organizational knowledge management use category or keyword information that portal users explicitly express interests in. However, it is usually difficult to collect correct preference data for all users with this approach, and, moreover, users' preferences may easily change over time, which results In outdated user profiles and impaired recommendation qualify. In order to address this problem, this paper suggests knowledge recommendation methods for portals using user profiles that are automatically constructed from users' activities such as posting or uploading of articles and documents. The result of our experiment shows that the Proposed method can provide equivalent performance with the manual category or keyword selection method.

• Journal of the Korea Society of Computer and Information
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• v.22 no.8
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• pp.41-46
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• 2017

In this paper, we investigate the D2D Transmitter(Tx) and Receiver(Rx) pair assignment problem in the cellular system where D2D users share the uplink resource of the cellular system. Sharing the uplink resource of the cellular system may cause interference to the cellular system, though it is beneficial to improve the D2D user Capacity. Therefore, to protect the cellular users, D2D transmit power should be carefully controlled. In this work, we focus on optimal Tx-Rx assignment in such a way that the total transmit power of users is minimized. First, we consider the optimum Tx-Rx assignment in general and the corresponding complexity. Then, we propose an iterative D2D Tx-Rx assignment algorithm with low complexity that can minimize total transmit power of users. Finally, we present the numerical examples that show the complexity and the convergence to the unique transmit power level.

• Journal of Family Resource Management and Policy Review
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• v.7 no.1
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• pp.103-118
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• 2003

This study is aimed to investigate Internet Addiction among youths who are main users of computers and internet and related variables. The survey was conducted to 520 students from middle and high schools on Jeju and analyzed catmod Regression. model was used to analyse the efficients of the independent variables on the three groups according to Internet addiction level. The major results of this study are as follows; First, By the viewpoint of Young's criteria, it revealed that most young people(68.5 ％) use the internet at the level of occasional problem-solution users. The percentage two groups of average on-line users and internet addicts were 27.3% and 4.2%, respectively. Second, the variables having significant effects on the of internet addiction group are gender, the number of brothers, adaptation to school life, mother's age, and family control of internet use. Third, the variables which have a significant effect on the of average internet users group referred to internet addicts group are gender, adaptation to school life, satisfaction with family life, average monthly household income, and the number of visits to private computer establishments.