• Journal of the Korean BIBLIA Society for library and Information Science
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• v.20 no.4
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• pp.191-204
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• 2009

It is essential to estimate and evaluate for user satisfaction and quality management of database system, understanding of user needs and quality characteristics. Based on ISO 25000 series, it was suggested, the first research, that 5 main quality characteristics, 21 sub quality characteristics and 48 internal quality characteristics. There are comparative significance methods of main quality characteristics, sub quality characteristics and internal quality characteristics but it is not easy to use directly quality model in database system industry field. Also, Considering time and cost in quality evaluation, it is impossible to evaluate 48 internal quality characteristics and its level of quality evaluation is not equal in accordance with integrity level of database system. By using AHP, this study presents selection method of quality characteristics in weight and possibility of application quality model.

• Journal of the Korea Society of Computer and Information
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• v.28 no.11
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• pp.147-154
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• 2023

In this paper, we propose a barrier-free course route navigation service named "Theme Road" aimed at improving the mobility and convenience for elderly electric wheelchair users with walking disabilities. To achieve this goal, we conducted a user survey through shadowing and in-depth interviews to gather insights on the challenges experienced by elderly electric wheelchair users. We identified potential solutions for each inconvenience through co-creation workshops, resulting in a set of design considerations and app functionalities. Using persona development and service scenarios, we designed and implemented the "Theme Road" service as a dedicated navigation application for barrier-free course navigation. Unlike conventional route navigation and mapping services, our study stands out by offering a unique approach that combines recommended destinations and safe routes based on experiential analysis from elderly electric wheelchair users.

• Journal of Information Processing Systems
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• v.20 no.3
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• pp.375-390
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• 2024

Edge computing architecture has effectively alleviated the computing pressure on cloud platforms, reduced network bandwidth consumption, and improved the quality of service for user experience; however, it has also introduced new security issues. Existing anomaly detection methods in big data scenarios with cloud-edge computing collaboration face several challenges, such as sample imbalance, difficulty in dealing with complex network traffic attacks, and difficulty in effectively training large-scale data or overly complex deep-learning network models. A lightweight deep-learning model was proposed to address these challenges. First, normalization on the user side was used to preprocess the traffic data. On the edge side, a trained Wasserstein generative adversarial network (WGAN) was used to supplement the data samples, which effectively alleviates the imbalance issue of a few types of samples while occupying a small amount of edge-computing resources. Finally, a trained lightweight deep learning network model is deployed on the edge side, and the preprocessed and expanded local data are used to fine-tune the trained model. This ensures that the data of each edge node are more consistent with the local characteristics, effectively improving the system's detection ability. In the designed lightweight deep learning network model, two sets of convolutional pooling layers of convolutional neural networks (CNN) were used to extract spatial features. The bidirectional long short-term memory network (BiLSTM) was used to collect time sequence features, and the weight of traffic features was adjusted through the attention mechanism, improving the model's ability to identify abnormal traffic features. The proposed model was experimentally demonstrated using the NSL-KDD, UNSW-NB15, and CIC-ISD2018 datasets. The accuracies of the proposed model on the three datasets were as high as 0.974, 0.925, and 0.953, respectively, showing superior accuracy to other comparative models. The proposed lightweight deep learning network model has good application prospects for anomaly traffic detection in cloud-edge collaborative computing architectures.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.18 no.5
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• pp.1224-1230
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• 2014

Because Twitter provides an easy way to reweet and reply to other user's tweets, it is used to delivery our opinion to others and get useful information from followers as a useful tool. Recently, there have been many attempts to use Twitter in many application area. Especially, Twitter has been tried to use in education area. Twitter service can be used in educational environments as a communication tool between professor and students and among students without restriction on space and time. Twitter service has good possibility of applying, but there have not been many studies that prove the effectiveness and possibility of the tool as a useful educational tool through experimental studies. In this study, Twitter is used as a tool of the question-and- answer session of the university students during a semester. And the activities are investigated and analyzed. As the results of the analysis, if we do not force the use of Twitter, Twitter utilization of students is low. Thus, we show that Twitter has the potential for educational utilizing, but the aggressive efforts between professor and students are needed to show such effects.

• Journal of Intelligence and Information Systems
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• v.22 no.4
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• pp.157-176
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• 2016

For a long time, mobile phone had a sole function of communication. Recently however, abrupt innovations in technology allowed extension of the sphere in mobile phone activities. Development of technology enabled realization of almost computer-like environment even on a very small device. Such advancement yielded several forms of new high-tech devices such as smartphone and tablet PC, which quickly proliferated. Simultaneously with the diffusion of the mobile devices, mobile applications for those devices also prospered and soon became deeply penetrated in consumers' daily lives. Numerous mobile applications have been released in app stores yielding trillions of cumulative downloads. However, a big majority of the applications are disregarded from consumers. Even after the applications are purchased, they do not survive long in consumers' mobile devices and are soon abandoned. Nevertheless, it is imperative for both app developers and app-store operators to understand consumer behaviors and to develop marketing strategies aiming to make sustainable business by first increasing sales of mobile applications and by also designing surviving strategy for applications. Therefore, this research analyzes consumers' mobile application usage behavior in a frame of substitution/supplementary of application categories and several explanatory variables. Considering that consumers of mobile devices use multiple apps simultaneously, this research adopts multivariate probit models to explain mobile application usage behavior and to derive correlation between categories of applications for observing substitution/supplementary of application use. The research adopts several explanatory variables including sociodemographic data, user experiences of purchased applications that reflect future purchasing behavior of paid applications as well as consumer attitudes toward marketing efforts, variables representing consumer attitudes toward rating of the app and those representing consumer attitudes toward app-store promotion efforts (i.e., top developer badge and editor's choice badge). Results of this study can be explained in hedonic and utilitarian framework. Consumers who use hedonic applications, such as those of game and entertainment-related, are of young age with low education level. However, consumers who are old and have received higher education level prefer utilitarian application category such as life, information etc. There are disputable arguments over whether the users of SNS are hedonic or utilitarian. In our results, consumers who are younger and those with higher education level prefer using SNS category applications, which is in a middle of utilitarian and hedonic results. Also, applications that are directly related to tangible assets, such as banking, stock and mobile shopping, are only negatively related to experience of purchasing of paid app, meaning that consumers who put weights on tangible assets do not prefer buying paid application. Regarding categories, most correlations among categories are significantly positive. This is because someone who spend more time on mobile devices tends to use more applications. Game and entertainment category shows significant and positive correlation; however, there exists significantly negative correlation between game and information, as well as game and e-commerce categories of applications. Meanwhile, categories of game and SNS as well as game and finance have shown no significant correlations. This result clearly shows that mobile application usage behavior is quite clearly distinguishable - that the purpose of using mobile devices are polarized into utilitarian and hedonic purpose. This research proves several arguments that can only be explained by second-hand real data, not by survey data, and offers behavioral explanations of mobile application usage in consumers' perspectives. This research also shows substitution/supplementary patterns of consumer application usage, which then explain consumers' mobile application usage behaviors. However, this research has limitations in some points. Classification of categories itself is disputable, for classification is diverged among several studies. Therefore, there is a possibility of change in results depending on the classification. Lastly, although the data are collected in an individual application level, we reduce its observation into an individual level. Further research will be done to resolve these limitations.

• Proceedings of the Korea Contents Association Conference
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• 2009.05a
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• pp.1191-1194
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• 2009

Scholarly information service is compared with internet portal services for object of use, information attributes and target users. It is not popular service, so scholarly information service providers need to have distinguished marketing strategy. KISTI service development team has performed on-site training for end users in major customer institutions in 2008. This study shows the effect of scholarly information service on-site training and user's preference of service promotion in specialized information service field.

• Archives of design research
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• v.17 no.1
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• pp.63-76
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• 2004

Although information design principles had originated from the graphic design field including publishing design in 1970s, information design have taken one of the most important positions in multimedia design fields as the present since Richard Saul Wurmn started his researches on information design and its practical application on internet environments. However, relatively little researches have been performed for building identity of information design in multimedia design fields so far and moreover in some cases, information design is likely to be narrowly viewed as 'the representation of a piece of information and its visualization' which was defined in traditional graphic design field. This research circumstance leads the study to investigate characteristics of information design in current multimedia design with contingent perspective which is compared to the traditional information design. The study results suggest 5 characteristics of information design including 'suggesting context & finding out information hierarchy', 'access of integrated consideration & share of information control', 'using of multi-dimensional media & content first', 'stabilization of information quality & combinational understanding of meaning', 'bilateral information representation & user's knowledge expansion'. Future researches, based on the results of the study, are expected to be expanded to a degree with argument for inter-dependent and/or exclusive characteristics of adjacent fields of information design such as interface design, interaction design and experience design.

• Journal of Intelligence and Information Systems
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• v.19 no.1
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• pp.57-77
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• 2013

Social media has become one of the most popular media in web and mobile application. In 2011, social networks and blogs are still the top destination of online users, according to a study from Nielsen Company. In their studies, nearly 4 in 5active users visit social network and blog. Social Networks and Blogs sites rule Americans' Internet time, accounting to 23 percent of time spent online. Facebook is the main social network that the U.S internet users spend time more than the other social network services such as Yahoo, Google, AOL Media Network, Twitter, Linked In and so on. In recent trend, most of the companies promote their products in the Facebook by creating the "Facebook Page" that refers to specific product. The "Like" option allows user to subscribed and received updates their interested on from the page. The film makers which produce a lot of films around the world also take part to market and promote their films by exploiting the advantages of using the "Facebook Page". In addition, a great number of streaming service providers allows users to subscribe their service to watch and enjoy movies and TV program. They can instantly watch movies and TV program over the internet to PCs, Macs and TVs. Netflix alone as the world's leading subscription service have more than 30 million streaming members in the United States, Latin America, the United Kingdom and the Nordics. As the matter of facts, a million of movies and TV program with different of genres are offered to the subscriber. In contrast, users need spend a lot time to find the right movies which are related to their interest genre. Recent years there are many researchers who have been propose a method to improve prediction the rating or preference that would give the most related items such as books, music or movies to the garget user or the group of users that have the same interest in the particular items. One of the most popular methods to build recommendation system is traditional Collaborative Filtering (CF). The method compute the similarity of the target user and other users, which then are cluster in the same interest on items according which items that users have been rated. The method then predicts other items from the same group of users to recommend to a group of users. Moreover, There are many items that need to study for suggesting to users such as books, music, movies, news, videos and so on. However, in this paper we only focus on movie as item to recommend to users. In addition, there are many challenges for CF task. Firstly, the "sparsity problem"; it occurs when user information preference is not enough. The recommendation accuracies result is lower compared to the neighbor who composed with a large amount of ratings. The second problem is "cold-start problem"; it occurs whenever new users or items are added into the system, which each has norating or a few rating. For instance, no personalized predictions can be made for a new user without any ratings on the record. In this research we propose a clustering method according to the users' genre interest extracted from social network service (SNS) and user's movies rating information system to solve the "cold-start problem." Our proposed method will clusters the target user together with the other users by combining the user genre interest and the rating information. It is important to realize a huge amount of interesting and useful user's information from Facebook Graph, we can extract information from the "Facebook Page" which "Like" by them. Moreover, we use the Internet Movie Database(IMDb) as the main dataset. The IMDbis online databases that consist of a large amount of information related to movies, TV programs and including actors. This dataset not only used to provide movie information in our Movie Rating Systems, but also as resources to provide movie genre information which extracted from the "Facebook Page". Formerly, the user must login with their Facebook account to login to the Movie Rating System, at the same time our system will collect the genre interest from the "Facebook Page". We conduct many experiments with other methods to see how our method performs and we also compare to the other methods. First, we compared our proposed method in the case of the normal recommendation to see how our system improves the recommendation result. Then we experiment method in case of cold-start problem. Our experiment show that our method is outperform than the other methods. In these two cases of our experimentation, we see that our proposed method produces better result in case both cases.

• KIISE Transactions on Computing Practices
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• v.23 no.5
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• pp.284-292
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• 2017

With the development of Internet of Things (IoT) technology, the combination of ICT and medical services has been increasing to improve the quality of medical services. Using the IoTs, we can collect personal health information continuously in a patient's everyday life. We expect that this will improve the quality of medical service through analysis. However, the problem of ensuring the protection of personal information within the personal health information has been hampering the research, development, and application of such services. Other problems include lack of IoT devices and lack of user convenience for collecting health information about a patient's everyday life. Therefore, in this study, we construct a daily health information management service that can collect the health related information at any time and store this data in personal storage. This data is then only provided to the healthcare worker when necessary. We built a test bed for an IoT-based smart home platform and are currently conducting user experiments. Based on the results of this study, we are attempting to provide a high quality medical trial service based on daily health information through linkage with medical device manufacturers, medical clinics, insurance companies, etc. We expect the proposed health information management service will contribute to the revitalization of smart health care services via activating various health related IoT devices and analyzing daily health information.

• 한국HCI학회:학술대회논문집
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• 2008.02b
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• pp.370-375
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• 2008

When customer makes a phone call to get the necessary information, ARS (Automatic Response System) will provide them without the limitation of time and place. Therefore, the application field of ARS (Automatic Response System) has been expanded and also occupancy rates arepretty high. However, compared with the importance of ARS, there is little study regarding the closest information structure of the actual users. Therefore, this research is about the ARS information structure of Gimhea BIS (Bus Information System), and the point of this research is to analyze the problem of the ARS information structure so we can suggest an idea to improve it. As the methods of study, drawing the workflow of ARS, conducting user observation, comparing with cases another region and analysis them. As a result, by and large there was error in the structure of information so, system reformation was required. Now that, we suggested two ideas for the improvement and we conducted usability test under that problem. Usability test was conducted by Lab test with interview. As a result, we could understand merits and demerits of two ideas for improvement, and we completed final improvement to highlight only merits of two ideas for improvement. This study will be utilized as the base material to improve ARS of Gimhea BIS.