• Journal of Communications and Networks
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• v.12 no.3
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• pp.253-265
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• 2010

The problem of pricing for a telecommunication network is investigated with respect to the users' sensitivity to the pricing structure. A functional optimization problem is formulated, in order to compute price reallocations as functions of data collected in real time during the network evolution. No a-priori knowledge about the users' utility functions and the traffic demands is required, since adaptive reactions to the network conditions are sought in real time. To this aim, a neural approximation technique is studied to exploit an optimal pricing control law, able to counteract traffic changes with a small on-line computational effort. Owing to the generality of the mathematical framework under investigation, our control methodology can be generalized for other decision variables and cost functionals.

• Journal of Satellite, Information and Communications
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• v.5 no.1
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• pp.94-99
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• 2010

In this paper, we discuss a proposed two hop relay network with PB/MC-CDMA(partial block MC-CDMA) technique. The main advantages of PB/MC-CDMA system are the increased cell capacity and the high quality of performances. In the system, we employ relay scheme to focus on the coverage reduction and hotspot problem, hotspot is a location where a cluster of users are blocked or dropped for the reason of insufficient frequency resources. Frequency resource allocation scheme is put forward in a three cells system according to each problem. The simulation result shows the performance of the two hop transmission is better than the direct transmission and the proposed network can support much more users to relief hotspot effect compared to the conventional one.

• Journal of Information Processing Systems
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• v.17 no.2
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• pp.426-439
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• 2021

To alleviate the cold-start problem and data sparsity in web service recommendation and meet the personalized needs of users, this paper proposes a personalized web service recommendation method based on a hybrid social network and multi-objective immune optimization. The network adds the element of the service provider, which can provide more real information and help alleviate the cold-start problem. Then, according to the proposed service recommendation framework, multi-objective immune optimization is used to fuse multiple attributes and provide personalized web services for users without adjusting any weight coefficients. Experiments were conducted on real data sets, and the results show that the proposed method has high accuracy and a low recall rate, which is helpful to improving personalized recommendation.

• Journal of KIISE
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• v.44 no.3
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• pp.314-322
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• 2017

In MMORPG (Massively Multiplayer Online Role-Playing Game), users advance their own characters to get to the maximum (max) level by performing given tasks in the game scenario. Although it is crucial to retain users with high levels for running online games successfully, little efforts have been paid to investigate them. In this study, by analyzing approximately 60 million in-game logs of over 50,000 users, we aimed to investigate the process through which users achieve the max level and churn of such users since the moment of achieving the max level, and determine possible indicators related to churn after the max level. Based on the result, we can predict churn of the max level users by employing behavioral patterns before the max level. Moreover, we found users who are socially active and communicate with many people before the max level are less likely to leave the service (p<0.05). This study supports that communication patterns are important factors for persistent usage of the users who achieve the max level, which has practical implications to guide elite users on enjoying online games in the long run.

• Journal of the Korean Society for information Management
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• v.22 no.1 s.55
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• pp.209-228
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• 2005

This study is a preliminary work in examining how to manage resources for collaboratively interactive help systems. The purpose of this article is to describe significant patterns of behaviors and cognitive state in collaborative problem-solving situation, and further to explore the relationship between the behavior and the perception of service evaluation. Based on the concept of 'cognitive motion' in Dervin's Sense-Making theory, this study conducted a time-line interview. The sample of this study consists of 22 IT personnel helping other person solve IT problems and 36 users being helped for a IT problem-solving. This study presents a model of collaborative problem-solving behaviors and discusses some implications for designing help systems which collaborative interactions can happen.

• Journal of Intelligence and Information Systems
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• v.20 no.4
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• pp.107-120
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• 2014

This study proposes a novel recommender system using the structural hole analysis to reflect qualitative and emotional information in recommendation process. Although collaborative filtering (CF) is known as the most popular recommendation algorithm, it has some limitations including scalability and sparsity problems. The scalability problem arises when the volume of users and items become quite large. It means that CF cannot scale up due to large computation time for finding neighbors from the user-item matrix as the number of users and items increases in real-world e-commerce sites. Sparsity is a common problem of most recommender systems due to the fact that users generally evaluate only a small portion of the whole items. In addition, the cold-start problem is the special case of the sparsity problem when users or items newly added to the system with no ratings at all. When the user's preference evaluation data is sparse, two users or items are unlikely to have common ratings, and finally, CF will predict ratings using a very limited number of similar users. Moreover, it may produces biased recommendations because similarity weights may be estimated using only a small portion of rating data. In this study, we suggest a novel limitation of the conventional CF. The limitation is that CF does not consider qualitative and emotional information about users in the recommendation process because it only utilizes user's preference scores of the user-item matrix. To address this novel limitation, this study proposes cluster-indexing CF model with the structural hole analysis for recommendations. In general, the structural hole means a location which connects two separate actors without any redundant connections in the network. The actor who occupies the structural hole can easily access to non-redundant, various and fresh information. Therefore, the actor who occupies the structural hole may be a important person in the focal network and he or she may be the representative person in the focal subgroup in the network. Thus, his or her characteristics may represent the general characteristics of the users in the focal subgroup. In this sense, we can distinguish friends and strangers of the focal user utilizing the structural hole analysis. This study uses the structural hole analysis to select structural holes in subgroups as an initial seeds for a cluster analysis. First, we gather data about users' preference ratings for items and their social network information. For gathering research data, we develop a data collection system. Then, we perform structural hole analysis and find structural holes of social network. Next, we use these structural holes as cluster centroids for the clustering algorithm. Finally, this study makes recommendations using CF within user's cluster, and compare the recommendation performances of comparative models. For implementing experiments of the proposed model, we composite the experimental results from two experiments. The first experiment is the structural hole analysis. For the first one, this study employs a software package for the analysis of social network data - UCINET version 6. The second one is for performing modified clustering, and CF using the result of the cluster analysis. We develop an experimental system using VBA (Visual Basic for Application) of Microsoft Excel 2007 for the second one. This study designs to analyzing clustering based on a novel similarity measure - Pearson correlation between user preference rating vectors for the modified clustering experiment. In addition, this study uses 'all-but-one' approach for the CF experiment. In order to validate the effectiveness of our proposed model, we apply three comparative types of CF models to the same dataset. The experimental results show that the proposed model outperforms the other comparative models. In especial, the proposed model significantly performs better than two comparative modes with the cluster analysis from the statistical significance test. However, the difference between the proposed model and the naive model does not have statistical significance.

• Journal of Communications and Networks
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• v.11 no.2
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• pp.157-165
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• 2009

In this paper, we investigate a dynamic spectrum sharing problem for the centralized uplink cognitive radio networks using orthogonal frequency division multiple access. We formulate a large-scale joint rate and power allocation as an optimization problem under quality of service constraint for secondary users and interference constraint for primary users. We also suggest admission control to nd a feasible solution to the optimization problem. To implement the resource allocation on a large-scale, we introduce a notion of using the conservative factors $\alpha$ and $\beta$ depending on the outage and violation probabilities. Since estimating instantaneous channel gains is costly and requires high complexity, the proposed algorithm pursues a practical and implementation-friendly resource allocation. Simulation results demonstrate that the large-scale joint rate and power allocation incurs a slight loss in system throughput over the instantaneous one, but it achieves lower complexity with less sensitivity to variations in shadowing statistics.

• Journal of the Korean Society for information Management
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• v.29 no.4
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• pp.25-42
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• 2012

Recently libraries are experiencing an increasing number of difficult patrons because of the increase in the unemployment rate and the problem of mental health in their communities. The problem behaviours of difficult patrons have negative influence to other users and staff in the library. This seems closely associated with the decline in the quality of library services. Therefore, in this study, we developed a how-to-do-it manual for library staff to meet the aforementioned challenges and to enhance the overall quality of library services for both general users and difficult patrons.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.15 no.4
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• pp.295-299
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• 2015

The developed security scheme for user authentication, which uses both a password and the various devices, is always open by malicious user. In order to solve that problem, a keystroke dynamics is introduced. A person's keystroke has a unique pattern. That allows the use of keystroke dynamics to authenticate users. However, it has a problem to authenticate users because it has an accuracy problem. And many people use passwords, for which most of them use a simple word such as "password" or numbers such as "1234." Despite people already perceive that a simple password is not secure enough, they still use simple password because it is easy to use and to remember. And they have to use a secure password that includes special characters such as "#!($^*$)^". In this paper, we propose the automatic fortified password generator system which uses special characters and keystroke feature. At first, the keystroke feature is measured while user key in the password. After that, the feature of user's keystroke is classified. We measure the longest or the shortest interval time as user's keystroke feature. As that result, it is possible to change a simple password to a secure one simply by adding a special character to it according to the classified feature. This system is effective even when the cyber attacker knows the password.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.11 no.4
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• pp.1301-1306
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• 2010

The protocol based on password have very important qualifications that not only satisfy against attacks cause of restricting that have, but also efficiency of reducing users' workload. It has a problem of speculative attacks for the user authentication protocol based on password with most case, because users use password that can remember easily. Song and Etc. have proposed new mechanism that improved the problem of S/KEY system. The protocol proposed by Song has a problem in registration process, and user information can be abused by the malevolent server. We propose a new authentication protocol based on efficient OPT, that improved above problems.