• Journal of Korean Library and Information Science Society
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• v.39 no.2
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• pp.169-186
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• 2008

Social Network has been known as friendship basis human relation service in online network. But a broad sense of Social Network can be explained as a mechanism which makes web evolve to information-ecosystem by human relation and network data which has been generated by the mass of people's cooperation and interchange. Social Network has been expanding their domain from friendship basis relation service to broad social relationship focus of matter of concern. It has been applied to diverse domain. Library community begins to take an interest in Social Network concept to apply user's interchange for information. This paper considers the concept of Social network and it's appliance to a library service. For the more, suggest basic element for vitalizing library user's Social network.

• IEMEK Journal of Embedded Systems and Applications
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• v.1 no.2
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• pp.73-81
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• 2006

The home network is generally separated from the Internet, as it is made up of a private network due to security issues and the lack of IPv4 addresses space. Also, a user may want to move from a terminal to another terminal connected in the home network during communicating with people outside the home. In this case, people connected in the Internet, or another home network could not communicate the user at the home. These limitations prevent a SIP-capable device connected in the home network from communicating with another SIP-capable device connected in the Internet or the outside of the home network. To overcome the limitations, This paper proposes the Adaptive SIP Application Server System as a software architecture that a user inside of the home can communicate with people outside of the home when the home is composed of a private IP-based network. Moreover, the proposed architecture provides the session mobility that allows the user to maintain a media session even if changing the terminal inside of the home during the session established. The proposed system was implemented over a home server device which acts functionality as a connection point for transmitting IP packets between a home network and the Internet.

• Proceedings of the KIEE Conference
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• 2004.11c
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• pp.240-242
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• 2004

A channel allocation algorithm of multi-user OFDM(orthogonal frequency division multiplexing) system is presented. The proposed algorithm is to reduce the complexity of the system, using the GNN(gradual neural network) with gradual expansion scheme and the algorithm attempts to allocate channel with good channel gain to each user. The method has lower computational complexity and less iteration than other algorithms.

• Journal of Intelligence and Information Systems
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• v.20 no.2
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• pp.93-107
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• 2014

In this paper, we report what we have observed with regard to user-perspective issue clustering based on multi-layered two-mode network analysis. This work is significant in the context of data collection by companies about customer needs. Most companies have failed to uncover such needs for products or services properly in terms of demographic data such as age, income levels, and purchase history. Because of excessive reliance on limited internal data, most recommendation systems do not provide decision makers with appropriate business information for current business circumstances. However, part of the problem is the increasing regulation of personal data gathering and privacy. This makes demographic or transaction data collection more difficult, and is a significant hurdle for traditional recommendation approaches because these systems demand a great deal of personal data or transaction logs. Our motivation for presenting this paper to academia is our strong belief, and evidence, that most customers' requirements for products can be effectively and efficiently analyzed from unstructured textual data such as Internet news text. In order to derive users' requirements from textual data obtained online, the proposed approach in this paper attempts to construct double two-mode networks, such as a user-news network and news-issue network, and to integrate these into one quasi-network as the input for issue clustering. One of the contributions of this research is the development of a methodology utilizing enormous amounts of unstructured textual data for user-oriented issue clustering by leveraging existing text mining and social network analysis. In order to build multi-layered two-mode networks of news logs, we need some tools such as text mining and topic analysis. We used not only SAS Enterprise Miner 12.1, which provides a text miner module and cluster module for textual data analysis, but also NetMiner 4 for network visualization and analysis. Our approach for user-perspective issue clustering is composed of six main phases: crawling, topic analysis, access pattern analysis, network merging, network conversion, and clustering. In the first phase, we collect visit logs for news sites by crawler. After gathering unstructured news article data, the topic analysis phase extracts issues from each news article in order to build an article-news network. For simplicity, 100 topics are extracted from 13,652 articles. In the third phase, a user-article network is constructed with access patterns derived from web transaction logs. The double two-mode networks are then merged into a quasi-network of user-issue. Finally, in the user-oriented issue-clustering phase, we classify issues through structural equivalence, and compare these with the clustering results from statistical tools and network analysis. An experiment with a large dataset was performed to build a multi-layer two-mode network. After that, we compared the results of issue clustering from SAS with that of network analysis. The experimental dataset was from a web site ranking site, and the biggest portal site in Korea. The sample dataset contains 150 million transaction logs and 13,652 news articles of 5,000 panels over one year. User-article and article-issue networks are constructed and merged into a user-issue quasi-network using Netminer. Our issue-clustering results applied the Partitioning Around Medoids (PAM) algorithm and Multidimensional Scaling (MDS), and are consistent with the results from SAS clustering. In spite of extensive efforts to provide user information with recommendation systems, most projects are successful only when companies have sufficient data about users and transactions. Our proposed methodology, user-perspective issue clustering, can provide practical support to decision-making in companies because it enhances user-related data from unstructured textual data. To overcome the problem of insufficient data from traditional approaches, our methodology infers customers' real interests by utilizing web transaction logs. In addition, we suggest topic analysis and issue clustering as a practical means of issue identification.

• Journal of Internet Computing and Services
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• v.16 no.6
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• pp.133-141
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• 2015

Mass multimedia contents are shared through various social media servies including social network service. As social network reveals user's current situation and interest, highly satisfactory personalized recommendation can be made when such features are applied to the recommendation system. In addition, classifying the music by emotion and using analyzed information about user's recent emotion or current situation by analyzing user's social network, it will be useful upon recommending music to the user. In this paper, we propose a music recommendation method that makes an emotion model to classify the music, classifies the music according to the emotion model, and extracts user's current emotional state represented on the social network to recommend music, and evaluates the validity of our method through experiments.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.12 no.10
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• pp.4703-4723
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• 2018

In recent years, dense small cell network has been deployed to address the challenge that has resulted from the unprecendented growth of mobile data traffic and users. It has proven to be a cost efficeient solution to offload traffic from macro-cells. Software defined heterogeneous wireless network can decouple the control plane from the data plane. The control signal goes through the macro-cell while the data traffic can be offloaded by small cells. In this paper, we propose a framework for cell virtualization and user association in order to satisfy versatile requirements of multiple tenants. In the proposed framework, we propose an interference graph partioning based virtual-cell association and customized physical-cell association for multi-homed users in a software defined small cell network. The proposed user association scheme includes 3 steps: initialization, virtual-cell association and physical-cell association. Simulation results show that the proposed virtual-cell association outperforms the other schemes. For physical-cell association, the results on resource utilization and user fairness are examined for mobile users and infrastructure providers.

• Journal of Korea Society of Digital Industry and Information Management
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• v.5 no.3
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• pp.107-115
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• 2009

Traditionally, simulation method is used to test and evaluate the performance of communication protocol or functional elements for mobile communication service. In this paper, wireless network simulator is implemented using the C++ object-oriented programming language. This simulator can simulate wireless data services, like as ad-hoc networks, by considering the user's mobility. In this paper, the simulator includes network traffic model to reflect wireless data service and traffic source model to represent a user's mobility similar to real service environment and traffic characteristics can be reflected on the simulation, and also more accurate simulation results can be got through that. In addition, by using object-oriented techniques, new service feature or environment can be easily added or changed so that the developed mobile communication simulator can reflect the real service environment all the time. This simulator can be used in adjusting the characteristics of wireless data hosts following the mobility of the user, and also can be used in building new wireless ad-hoc network routing protocols.

• Journal of Korean Society for Quality Management
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• v.42 no.3
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• pp.387-406
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• 2014

Purpose: The widespread use of social network services (SNS) has caused users concern about the disclosure of their privacy or personal information. The purpose of this study is to analyze the factors of privacy concern and self presentation that affect the user resistance in the use of social network service. Methods: This study verifies the factors that affecting the user resistance in SNS. The research model suggested in this study is tested via a survey of 260 SNS users. SPSS and Smart PLS had been used to test the suggested hypotheses. Results: This study shows that privacy experience, privacy awareness, self esteem, and social desirability significantly influence perceived risk and that privacy awareness, self esteem, self efficacy, and perceived risk significantly influence perceived trust. It also verifies that perceived risk and perceived trust positively affect user resistance. Conclusion: This paper suggests that high awareness on privacy of SNS user encourages the SNS companies to consider the privacy protection mechanism for eliminating various factors that affecting the risk. This study also shows that the privacy calculus model applies to understanding the mechanism on resistance of SNS user.

• Journal of Information Technology Services
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• v.13 no.3
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• pp.235-255
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• 2014

Social Network Service (SNS) with emergence of Web 2.0 have been developed rapidly. Unlike other games, social network game is based on the relationship with smart devices and studied for user-centered behavior as a potential factor derived from the Technical Acceptance Model (TAM). This research is conducted for finding out influencing factors on continuous intention for smart device users. Therefore, the independent variables consist of subjective norm, mobility, playfulness, self-efficacy, and ease of use. The intermediate variables also compose of flow, and user satisfaction and the dependent variables as continuous intention. The result of study shows the following: First, subjective norm, playfulness, self-efficacy and ease of use except mobility have the positive effect on user flow. Second, subjective norm, mobility, playfulness and ease of use except self-efficacy have significantly the positive effect on user satisfaction. Finally, user flow has significantly the positive effect on user satisfaction and continuance intention and a factor of user satisfaction have significantly the positive effect on continuance intention.

• The Journal of the Korea Contents Association
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• v.16 no.12
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• pp.551-561
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• 2016

A user influence discrimination scheme using big data from social networks is needed. In this thesis, we propose a user influence discrimination scheme considering reliability in social networks. The proposed scheme measures reliability scores through social activities and simplifies a social network by collecting only reliable users. It also derives user influence by considering direct and indirect influences that depends on network degree between users. As a result, the proposed scheme improves the expandability of the user influence. In order to show the superiority of the proposed scheme, we compare it with the existing scheme through performance evaluations in terms of reliability and user influence.