• Journal of Intelligence and Information Systems
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• v.27 no.3
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• pp.157-173
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• 2021

With the development of information technology, the amount of available information increases daily. However, having access to so much information makes it difficult for users to easily find the information they seek. Users want a visualized system that reduces information retrieval and learning time, saving them from personally reading and judging all available information. As a result, recommendation systems are an increasingly important technologies that are essential to the business. Collaborative filtering is used in various fields with excellent performance because recommendations are made based on similar user interests and preferences. However, limitations do exist. Sparsity occurs when user-item preference information is insufficient, and is the main limitation of collaborative filtering. The evaluation value of the user item matrix may be distorted by the data depending on the popularity of the product, or there may be new users who have not yet evaluated the value. The lack of historical data to identify consumer preferences is referred to as data sparsity, and various methods have been studied to address these problems. However, most attempts to solve the sparsity problem are not optimal because they can only be applied when additional data such as users' personal information, social networks, or characteristics of items are included. Another problem is that real-world score data are mostly biased to high scores, resulting in severe imbalances. One cause of this imbalance distribution is the purchasing bias, in which only users with high product ratings purchase products, so those with low ratings are less likely to purchase products and thus do not leave negative product reviews. Due to these characteristics, unlike most users' actual preferences, reviews by users who purchase products are more likely to be positive. Therefore, the actual rating data is over-learned in many classes with high incidence due to its biased characteristics, distorting the market. Applying collaborative filtering to these imbalanced data leads to poor recommendation performance due to excessive learning of biased classes. Traditional oversampling techniques to address this problem are likely to cause overfitting because they repeat the same data, which acts as noise in learning, reducing recommendation performance. In addition, pre-processing methods for most existing data imbalance problems are designed and used for binary classes. Binary class imbalance techniques are difficult to apply to multi-class problems because they cannot model multi-class problems, such as objects at cross-class boundaries or objects overlapping multiple classes. To solve this problem, research has been conducted to convert and apply multi-class problems to binary class problems. However, simplification of multi-class problems can cause potential classification errors when combined with the results of classifiers learned from other sub-problems, resulting in loss of important information about relationships beyond the selected items. Therefore, it is necessary to develop more effective methods to address multi-class imbalance problems. We propose a collaborative filtering model using CGAN to generate realistic virtual data to populate the empty user-item matrix. Conditional vector y identify distributions for minority classes and generate data reflecting their characteristics. Collaborative filtering then maximizes the performance of the recommendation system via hyperparameter tuning. This process should improve the accuracy of the model by addressing the sparsity problem of collaborative filtering implementations while mitigating data imbalances arising from real data. Our model has superior recommendation performance over existing oversampling techniques and existing real-world data with data sparsity. SMOTE, Borderline SMOTE, SVM-SMOTE, ADASYN, and GAN were used as comparative models and we demonstrate the highest prediction accuracy on the RMSE and MAE evaluation scales. Through this study, oversampling based on deep learning will be able to further refine the performance of recommendation systems using actual data and be used to build business recommendation systems.

• Journal of Global Scholars of Marketing Science
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• v.17 no.4
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• pp.113-139
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• 2007

This study aims to, looking from a standpoint of network, has investigated the shipping industry's B2B e-marketplace, the characteristics that can earn electronic trust from the users, and characteristics of the web-site. It has examined the mechanism whereby electronic trust be earned and how it affects web-site involvement and service transaction intention. Ultimately, The study attempts to make proposals whereby such trust can lead for a cooperative trading community in the shipping industry's B2B e-marketplace The Covalence structural equation modeling was designed and empirically tested for the shipping industry's B2B e-marketplace. The shipping industry employees were given questionnaires and data were analyzed. Except for perceived security of the three characteristic factors on the web-site, the perceived site quality and characteristics factors in operation only affected co-variables. Transaction Fairness was determined to be the most important factor among exogenous factors increasing electronic trust. With regards to transaction rules, if a transaction is beneficial only to one side, then no long term transaction will not take place. If the concerned parties properly recognize that transaction fairness is crucial to electronic transaction, then it will enormously contribute to successful operations of shipping e-marketplace. Also, Perceived efficiency in transaction also affects electronic trust. This reduces transaction costs and speeds up and simplifies the transaction process. It has reduced greater time and costs than existing off-line transaction, and would positively affect electronic trust. By making an open forum for participants to obtain information for transaction, they can gather useful information, and at the same time, the web-site operator can provide information, which, in turn, will increase electronic trust in electronic transaction. Furthermore, such formation of trust in electronic transaction influences shipping companies in such a way that they will want to continuously participate in the transaction, raising web-site involvement. The result of increased trust is that shipping companies in the future will do business with each other and form a foundation for continuous transactions amongst themselves. Consequently, the formation of trust in electronic transaction greatly influences web-site involvement and service transaction intention. The results of the study have again proved that in order to maintain continuous business relationship with the current clients, electronic trust in virtual space, which operates the shipping industry's B2B e-marketplace, is important for the interested parties.

• Journal of Internet Computing and Services
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• v.14 no.5
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• pp.101-117
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• 2013

As the number of online game user has been rapidly increased thanks to the recent vitalization of online contents market, not only new business opportunity but also the opportunity to create high profits have been provided as well. However, the increase of the number of online game user and the rapid expansion of the market evoke a cutthroat completion among online game service providers, and also high barriers to entry to online game market have been erected. Thus, what kinds of efforts need for the business success and sales increase in online game market? In lots of researches regarding online contents business, the deepening of loyalty was considered as a critical factor for the business success. According to the study on user's behavior in online environment, users would experience the Flow while using online service, and then, if they were in state of the Flow, they would use the service constantly. High customer loyalty to online game means high will to use the online game too. The purpose of this research was i) to examine what factors enable users to be naturally immersed in online game while playing it, ii) to examine what properties of online game can make game more interesting and exciting, iii) to verify that such factors are critical in deepening customer loyalty, and iv) to suggest some essential factors to be fun and exciting games, on where the focus should be put, and the directionality for the development for sales expansion of online game developer or online game service provider. The research results are as below: First, the involvement and the perceived quality which were characteristics of brand appeared to be factors most affecting Flow. This shows that once game user get interested in online game that user has played frequently, even though new games are released, user will continuously flow the game not moving to new games, and also shows that users not only get more interested but also put more trust in games in the site to where users are frequently going than games in other sites, and consequently user can increasingly flow the game. Second, the compensation and graphics which are the characteristics of contents appeared to be factors affecting Flow. Proper compensation which is given to game users triggers fun and interests in game and makes them flow more and more. And graphics make users to feel game space as if real space and let them flow in game with more reality. Third, challenges, support, and the stability which are technical characteristics appeared to be factors affecting Flow. Challenges enable users to not only experience new virtual world but also solve various difficulties and obstacles. Once users feel fun and interests through this challenge, they can naturally flow games. In addition, the stability of network provides reliability in security and hacking. By doing so, it can induce users to flow more and more. Lastly, when aforementioned characteristics including contents characteristics, technical characteristics, and brand characteristics are organically combined each other, game users feel fun and total minutes are naturally increased, so that game users experience Flow, and consequently the customer loyalty will be deepened as well.

• Journal of Korean Tunnelling and Underground Space Association
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• v.20 no.6
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• pp.899-915
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• 2018

In this study, in order to construct an eco-friendly advanced road transportation network, the multi-layer tunnel, which is a small-sized car road, is designed to have a height of less than 60 cm. However, the shape of the tunnel is low and the height of the traffic sign is small. In order to solve these problems, traffic sign characters were designed in three dimensions, and the possibility of applying the design of the three - dimensional sign that can obtain greater visibility than the existing signs at the same distance and the possibility verification through virtual simulation were performed. The three-dimensional sign is horizontally installed on the ceiling of the multi-layer tunnel. To be seen vertically, it is enlarged by a certain ratio by the perspective, and the width and height are enlarged. Respectively. In addition, 3D simulation was performed to verify the visibility of the stereoscopic signs when the driver ran through the stereoscopic sign design specifications. As a result of the design and experimental study, it was confirmed that the stereoscopic sign could be designed through the theoretical formula and that it could provide the driver with a larger traffic sign character because there is no limitation of the facility limit compared to the existing vertical traffic sign. Also, we confirmed that it can be implemented in the side wall by using the stereoscopic sign design principle installed on the ceiling part. It was confirmed that the design of the stereoscopic sign can be designed to be smaller as the distance that the driver visually recognizes the sperm is shorter, the height of the protrusion vertically at the lower part of the stereoscopic sign becomes higher. As a result of 3D simulation running experiment based on the design information of the stereoscopic sign, it was confirmed that the stereoscopic sign is visually the same as the vertical sign at the planned distance. Although the detailed research and institutional improvement of stereoscopic signs have not been made in Korea and abroad, it is evolved into a core technology of new road traffic facilities through various studies through the possibility of designing and applying stereoscopic signs developed through this study Expect.

• Journal of the Korean earth science society
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• v.43 no.6
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• pp.691-711
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• 2022

The state-of-the-art Earth system model as a virtual Earth is required for studies of current and future climate change or climate crises. This complex numerical model can account for almost all human activities and natural phenomena affecting the atmosphere of Earth. The Unified Model (UM) from the United Kingdom Meteorological Office (UK Met Office) is among the best Earth system models as a scientific tool for studying the atmosphere. However, owing to the expansive numerical integration cost and substantial output size required to maintain the UM, individual research groups have had to rely only on supercomputers. The limitations of computer resources, especially the computer environment being blocked from outside network connections, reduce the efficiency and effectiveness of conducting research using the model, as well as improving the component codes. Therefore, this study has presented detailed guidance for installing a new version of the UM on high-performance parallel computers (Linux clusters) owned by individual researchers, which would help researchers to easily work with the UM. The numerical integration performance of the UM on Linux clusters was also evaluated for two different model resolutions, namely N96L85 (1.875° ×1.25° with 85 vertical levels up to 85 km) and N48L70 (3.75° ×2.5° with 70 vertical levels up to 80 km). The one-month integration times using 256 cores for the AMIP and CMIP simulations of N96L85 resolution were 169 and 205 min, respectively. The one-month integration time for an N48L70 AMIP run using 252 cores was 33 min. Simulated results on 2-m surface temperature and precipitation intensity were compared with ERA5 re-analysis data. The spatial distributions of the simulated results were qualitatively compared to those of ERA5 in terms of spatial distribution, despite the quantitative differences caused by different resolutions and atmosphere-ocean coupling. In conclusion, this study has confirmed that UM can be successfully installed and used in high-performance Linux clusters.