• The Journal of Fisheries Business Administration
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• v.41 no.2
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• pp.81-106
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• 2010

This study examines the information exploration characteristic and relative importance evaluation of island tourism web site. The survey items are developed based on the related studies and also implemented particular way so-called 'semi-online' that including both web based material and offline tutorial. The first objective of this study is verifying the characteristics of information exploration on island tourism of university students. The second is examining the peculiar properties of tourism information that exposed one's individual importance evaluation. The result of this study shows that most of the students have no difficulty in using the internet and exploring the island tourism information. And there is no significant difference in using and exploring the internet between male and female students. Based on the result of this study, most popular type of island tourism information is picture type. Personal blog or user created contents(UCC) that containing the other's experience of island tourism is mostly wanted contents. But there is a significant difference in importance of contents within the students. The community based information which including UCC, blog, and other community user's posting is evaluated the most important information for relatively less experienced students. On the other hand more experienced students have a preference on expertise information which created by tourism experts. The difference within the determinant factors that affecting island tourism also significant. With analysis of variance(ANOVA) on determinant factors, the tourism activity and social/culture resource are less important than others(eg. natural environment, accommodation and so on). The result of this study would be practically used for implementing the local government's effective tourism web site and enhancing the current island tourism operation. And also it gives a advantage to facilitate the island tourism for young generations.

• Journal of Convergence for Information Technology
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• v.8 no.3
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• pp.79-84
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• 2018

Cloud services are readily available through a variety of media, attracting a lot of attention from users. However, there are various security damages that abuse the privacy of users who use cloud services, so there is not enough technology to prevent them. In this paper, we propose a protection model to safeguard user's privacy in a cloud environment so as not to illegally exploit user's privacy. The proposed model randomly manages the user's signature to strengthen the role of the middle manager and the cloud server. In the proposed model, the user's privacy information is provided illegally by the cloud server to the user through the security function and the user signature. Also, the signature of the user can be safely used by bundling the random number of the multiplication group and the one-way hash function into the hash chain to protect the user's privacy. As a result of the performance evaluation, the proposed model achieved an average improvement of data processing time of 24.5% compared to the existing model and the efficiency of the proposed model was improved by 13.7% than the existing model because the user's privacy information was group managed.

• Journal of the Korea Convergence Society
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• v.8 no.8
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• pp.71-75
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• 2017

Due to the spread of SNS, web-based consumer-generated data is increasing exponentially. It is important in many fields to accurately extract what is appropriate for the user's interest in a large amount of data. It is especially important for business mangers to establish marketing policies to find the right customers for them in many users. In this paper, we try to obtain important information centering on customers who are interested in each account through Twitter follow - following relationship. Because Twitter's current follower relationships do not reflect the user's interests, we try to figure out the details of interest using keyword extraction methods for tweets of followers. To do this, we select two domestic commercial Twitter accounts and apply the sequential pattern evaluation index to the mining key phrase of the text data collected from the follower.

• Journal of Information Science Theory and Practice
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• v.2 no.2
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• pp.33-47
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• 2014

Mobile devices are the most important equipment for accessing various kinds of services. These services are accessed using wireless signals, the same used for mobile calls. Today mobile services provide a fast and excellent way to access all kinds of information via mobile phones. Mobile service providers are interested to know the access behavior pattern of the users from different locations at different timings. In this paper, we have introduced an associated tree for analyzing user behavior patterns while moving from one location to another. We have used four different parameters, namely user, location, dwell time, and services. These parameters provide stronger frequent accessing patterns by matching joins. These generated patterns are valuable for improving web services, recommending new services, and predicting useful services for individuals or groups of users. In addition, an experimental evaluation has been conducted on simulated data. Finally, performance of the proposed approach has been measured in terms of efficiency and scalability. The proposed approach produces excellent results.

• Journal of the Korean housing association
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• v.18 no.2
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• pp.129-136
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• 2007

This study, as a case study of four university dormitories in Gwangju, examined the situation of interior space and conducted a quantitative survey investigating importance about the interior space and assessment factors of residential environment on users. Then user satisfaction at the assessment factors of residential environment was analyzed to draw problems and explore improvement. The results showed the following problems that should be resolved: Bedrooms should increase the area of convex space; toilets and bathrooms should be changed into a cluster type at least in common use by floor; rest space should reinforce heating and cooling system; robby space should become mixed space for various user's behavior; private fitness rooms should be planned as group fitness space; private libraries should reinforce lighting facilities; and computer rooms should complement and improve HVAC.

• Proceedings of the KOR-KST Conference
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• 2002.02a
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• pp.97-139
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• 2002

The aim of the present study is to find a good quality user equilibrium assignments under time varying condition. For this purpose, this study introduces a dynamic network loading method that can maintain correct flow propagation as well as flow conservation, and it develops a novel solution algorithm that does not need evaluation of the objective function by modifying the Schittenhelm (1990)'s algorithm. This novel algorithm turns out to be efficient and convenient compared to the conventional Frank-Wolfe (1956) algorithm because the former finds solutions based on routes rather than links so that it can maintain correct flow propagation intrinsically in the time-varying network conditions. The application of dynamic user equilibrium (DUE) assignment model with this novel solution algorithm to test networks including medium-sized one shows that the present DUE assignment model gives rise to high quality discrete time solutions when we adopt the deterministic queuing model for a link performance function, and we associate flows and costs in a proper way.

• Journal of the Korean Society for Library and Information Science
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• v.32 no.3
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• pp.265-280
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• 1998

The Current measures of library service quality do not adequately capture user's perceptions of service quality for libraries and information centers. The purposes of this study are (1) to develop a user-based concepts to measuring the quality of library service (2) to introduce a user-based service quality model and SERVQUAL instrument from service marketing areas and (3) to assess applicability of this model and instrument to libraries and information centers. The concluding section suggests several considerations for implementation of their applicability and future research.

• International Journal of Internet, Broadcasting and Communication
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• v.14 no.3
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• pp.143-148
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• 2022

In this paper, we employ deep neural network (DNN) to discern Android user interaction data distribution from artificial data distribution. We utilize real Android user interaction trace dataset collected from [1] to evaluate our DNN design. In particular, we use sequential model with 4 dense hidden layers and 1 dense output layer in TensorFlow and Keras. We also deploy sigmoid activation function for a dense output layer with 1 neuron and ReLU activation function for each dense hidden layer with 32 neurons. Our evaluation shows that our DNN design fulfills high test accuracy of at least 0.9955 and low test loss of at most 0.0116 in all cases of artificial data distributions.

• Journal of Korea Multimedia Society
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• v.25 no.8
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• pp.1242-1250
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• 2022

When recommending cold items that do not have user-item interactions to users, even we adopt state-of-the-arts algorithms, the predicted information of cold items tends to have lower accuracy compared to warm items which have enough user-item interactions. The lack of information makes for recommender systems to recommend monotonic items which have a few top popular contents matched to user preferences. As a result, under-diversified items have a negative impact on not only recommendation diversity but also on recommendation accuracy when recommending cold items. To address the problem, we adopt a diversification algorithm which tries to make distributions of accumulated contents embedding of the two items groups, recommended items and the items in the target user's already interacted items, similar. Evaluation on a real world data set CiteULike shows that the proposed method improves not only the diversity but also the accuracy of cold item recommendation.

• Journal of Information Technology Services
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• v.13 no.2
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• pp.113-131
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• 2014

Smartphone security threat has become an important issue in Information Science field following the wide distribution of smartphones. However, there are few studies related to such. Therefore, this study examined the factors affecting the intention of smartphone users to use the mobile vaccine against malware with the Protection Motivation Theory. To secure the reliability of the study, a surveying agency was commissioned. A total of 263 respondents, excluding 37 respondents who are users of iOS, which does not have mobile vaccine in the smart phone, or who gave invalid responses, were surveyed. The results showed that perception of the installed mobile vaccine significantly affected the Response Efficacy and Self-efficacy, and that the Perceived Severity, Perceived Vulnerability, Response Efficacy, and Self-efficacy significantly influenced the intention to use the mobile vaccine. On the other hand, Installation Perception of mobile vaccine itself did not affect the Perceived Severity and Perceived Vulnerability. This study is significant since it presented the new evaluation model of threat evaluation and response evaluation in the Protection Motivation Theory in accepting the security technology and raised the need for the promotion and exposure of mobile vaccine, since perception of mobile vaccine installation affects the response evaluation. It also found that the promotion must consider the seriousness of smartphone security, outstanding attribute of mobile vaccine, and user-friendliness of mobile vaccine above all.