• Journal of Internet Computing and Services
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• v.14 no.4
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• pp.91-100
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• 2013

In recent years, online brand communities, whereby firms and customers interact freely, are emerging trend, because customers' opinions collected in these communities can help firms to achieve their innovation effectively. In this study, we examined whether customer opinions containing negative emotions have influence on their adoption for organizational innovation. To that end, we firstly classified negative emotions into five categories of detailed negative emotions such as Fear, Anger, Shame, Sadness, and Frustration. Then, we developed a lexicon for each category of negative emotions, using WordNet and SentiWordNet. From 81,543 customer opinions collected from MyStarbucksIdea.com which is Starbucks' brand community, we extracted terms that belong to each lexicon. We conducted an experiment to examine whether the existence, frequency and strength of terms with negative emotions in each category affect the adoption of customer opinions for organizational innovation. In the experiment, we statistically verified that there is a positive relationship between customer ideas containing negative emotions and their adoption for innovation. Especially, Frustration and Sadness out of the five emotions are significantly influential to organizational innovation.

• The Journal of the Korea Contents Association
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• v.16 no.3
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• pp.137-148
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• 2016

The purpose of this study is to examine viewers' intentions to watch movies after viewing online banner advertisements of movies, and verify the mediation effect of flow and association to research how the interactivity of movie banner advertisements influences viewers. For the study, trailer and advergame banners for three genres of movies were made, and an online survey was conducted with 146 adults. As a result, based on 5 hypothesis tests, the study enables us to conclude that the interactivity of the advergame banners results in a higher viewer intention of watching movies compared to trailer banners by inducing a flow experience among banner users not an association experience.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.19 no.8
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• pp.1628-1639
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• 1994

In order to increase the utilization of the computing resources, universities connect a variety of computing resources such as mainframes, workstations, and personal computers via LAN. However, due to management and security reasons, most administrative applications are concentrated on mainframes which is the main cause of large work overload on mainframes for such applications as on-line course registration system where the entire student body must have access to the system during a short period of time. In this study, using a university system as the model and choosing on-line course registration system as the targeted distributed computing. APPC through IBM SNALU 6.2 link is proposed as the most appropriate means of distributed computing for the environment of the model university. In addition, the on-line course registration system is redesigned as client-server model where a mainframe serves as the file server responsible for file input and output and workstations becomes the client. Actual implementation and experiments have shown that the proposed distributed computing system yields a significant reduction in processing time.

• Journal of KIISE
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• v.44 no.11
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• pp.1231-1235
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• 2017

Given the network structure in online social network, it is important to determine a way to distinguish spam accounts from the network features. In online social network, the service provider attempts to detect social spamming to maintain their service quality. However the spammer group changes their strategies to avoid being detected. Even though the spammer attempts to act as legitimate users, certain distinguishable structural features are not easily changed. In this paper, we investigate a way to generate meaningful network structure features, and suggest spammer detection method using recursive structural features. From a result of real-world dataset experiment, we found that the proposed algorithm could improve the classification performance by about 8%.

• The Journal of the Korea Contents Association
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• v.12 no.9
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• pp.9-15
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• 2012

A conventional event sentence extraction research doesn't learn the 3W features in the learning step and applies the rule on whether the 3W feature exists in the extraction step. This paper presents a sentence weight based event sentence extraction method that calculates the weight of the 3W features in the learning step and applies the weight of the 3W features in the extraction step. In the experimental result, we show that top 30% features by the $TF{\times}IDF$ weighting method is good in the feature filtering. In the real estate domain of the public issue, the performance of sentence weight based event sentence extraction method is improved by who and when of 3W features. Moreover, In the real estate domain of the public issue, the sentence weight based event sentence extraction method is better than the other machine learning based extraction method.

• The Journal of Korean Association of Computer Education
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• v.12 no.3
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• pp.31-40
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• 2009

English education taken with native English speakers is very effective, but it is hard to obtain English education with native English speakers in rural schools. In this study, therefore, we supported English education with on-line content and video conferencing with native English speakers. This study worked with one hundred fifty students from six elementary and middle schools equally distributed by city size over three months. This study performed experimental research by T-test comparing of pre- and post-tests of the hybrid model. In our results, the upper group showed greater improvement in understanding while the lower group showed more improvement in writing. In addition, the lower group showed more improvement than the upper group in overall English accomplishment.

• Journal of Korea Game Society
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• v.14 no.5
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• pp.35-42
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• 2014

In the market of First Person Shooter (FPS) games, Massively Multi-player Online FPS games (MMOFPS) like 'PlanetSide 2' have been popular recently. Dead reckoning has been widely used in order to mitigate the network traffic overload for the game server with hundreds or thousands of people. This paper proposes the efficient analytical method to calculate the tolerable threshold angle of moving direction, which is one of the most important factors for character status updating when dead reckoning is used in MMOFPS games. The experimental results with game testers shows that the proposed method minimizes the position error for character moving and provides natural direction updates of characters.

• Journal of the Korean Institute of Intelligent Systems
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• v.18 no.6
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• pp.737-745
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• 2008

Recent developments of process and measurement technology bring much interest to the online monitoring of process operations such as milling, grinding, broaching, etc. The objective of online monitoring systems is to detect process changes as early as possible. This is helpful in protecting facilities against unexpected failures and then preventing unnecessary loss. This paper investigates, when the process monitoring data are obtained as a profile, the monitoring performances of a statistical $T^2$-statistic and a feedforward neural network by using a wavelet transform. Numerical experiments using cutting force data presented by Axinte show that the proposed wavelet based $T^2$-test has an acceptable power in detecting profile changes. However, its operating characteristic is very sensitive to autocorrelation. On the contrary, compared with $T^2$-test, the neural network has more stable performance in the presence of autocorrelation. This indicates that an adaptive feature to analyze noises should be incorporated into the wavelet based $T^2$-test.

• KIPS Transactions on Software and Data Engineering
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• v.9 no.9
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• pp.259-266
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• 2020

In this paper, we propose a novel scheme for product effect analysis, termed PEM, to find out the effectiveness of products used for improving the current condition, such as health supplements and cosmetics, by utilizing online customer reviews. The proposed technique preprocesses online customer reviews to remove advertisements automatically, constructs the word dictionary composed of symptoms, effects, increases, and decreases, and measures products' effects from online customer reviews. Using Naver Shopping Review datasets collected through crawling, we evaluated the performance of PEM compared to those of two methods using traditional sentiment dictionary and an RNN model, respectively. Our experimental results shows that the proposed technique outperforms the other two methods. In addition, by applying the proposed technique to the online customer reviews of atopic dermatitis and acne, effective treatments for them were found appeared on online social media. The proposed product effect analysis technique presented in this paper can be applied to various products and social media because it can score the effect of products from reviews of various media including blogs.

• Journal of Internet Computing and Services
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• v.16 no.5
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• pp.49-57
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• 2015

In this Paper, we introduce an efficient on-line software service using an application customized graphic offloading library. The software service based on graphic offloading provides high-end software, like a 3D graphic design tool, as an on-line software service through using a client graphic rendering. When software is executed on server, its graphic works are handled by a client's GPU, while its data works are handled by a server's CPU. To improve the performance, we apply an asynchronous transmission channel scheme to our developed basic graphic offloading engine. Also, we add optimized common module and application specific module to our engine. To do that, we introduce how to implement the application specific module using analyzing patterns of graphic related APIs and messages that are generated by an executed software process. Also, we propose how to design the optimized common module using server side information caching. Finally, through the performance comparison experiment, we show that improved offloading engine has the better performance than old basic offloading engine.