• KIISE Transactions on Computing Practices
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• v.22 no.10
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• pp.504-512
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• 2016

In this paper, we propose a personalized event recommendation scheme using user's activity analysis and collaborative filtering in social network environments. The proposed scheme predicts un-evaluated attribute values through analysis of user activities, relationships, and collaborative filtering. The proposed scheme also incorporates a user's recent preferences by considering the recent history for the user or context-aware information to precisely grasp the user's preferences. As a result, the proposed scheme can recommend events to users with a high possibility to participate in new events, preventing indiscriminate recommendations. In order to show the superiority of the proposed scheme, we compare it with the existing scheme through performance evaluation.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2013.05a
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• pp.911-913
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• 2013

The user's context awareness is important to the reliability of sensors data. The sensor data is constantly change to external temp, internal& external environment and vibration. This noise environment is affecting that the data collected information from sensors. Of course this method of digital filter and inference algorithm specifically request for the use of ripple noise and action inference. In this paper, experiment was a comparison of the KF(Kalman Filter) and WMAF(Weight Moving Average Filter) for noise decrease and distortion prevention according to user behavior. And, we compared the EWDF(Extended Weight Dual Filter) with several filer. In an experiment, in contrast to other filter, the proposed filter is robust in a noise-environment.

• Journal of KIISE:Information Networking
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• v.32 no.3
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• pp.291-300
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• 2005

The Ubiquitous computer environment is thing which invisible computer that is not shown linked mutually through network so that user may use computer always is been pervasive. Intend computing environment that can use easily as user wants and it is the smart environment that user provides context awareness that is wanting computing environment. This Ubiquitous computing contains much specially weak side in security. Masquerade attack of that crawl that is quoted to user or server among device that is around user by that discrete various computing devices exist everywhere among them become possible. Hereupon, in this paper, proposed method that have following characteristic. Present authentication model through transfer or device. Suggest two method that realize authentication through device in case of moved to method(MD: Multi Domain) and user ownself space(SD: Single Domain) that realize authentication through device in case of moved user's direct path who device differs.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.20 no.1
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• pp.11-18
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• 2020

This study aims to complement the poor performance of existing context-aware authentication techniques in the mobile environment. The data used are GPS, Call Detail Record(CDR) and app usage. locational classification according to GPS density was implemented in order to distinguish other people in populated areas in the processing of GPS. It also handles missing values that may occur in data collection. The authentication model consists of two long-short term memory(LSTM) and one Artificial Neural Network(ANN) that aggregates the results, which produces authentication scores. In this paper, we compare the accuracy of this technique with that of other studies. Then compare the number of authentication attempts required to detect someone else's authentication. As a result, we achieved an average 11.6% improvement in accuracy and faster detection of approximately 60% of the experimental data.

• Proceedings of the Korean Society for Emotion and Sensibility Conference
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• 2001.05a
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• pp.20-25
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• 2001

In recent years, the concern about a user center design in increasing, and it's needed to task a user's visual cognitive characteristics for information presentation. Then this study aims to grasp user's cognitive characteristics about the information presentation by analyzing the fixation points. In the experiment, actually subject operated a copy machine. Recorded the fixation point movement of the operation panel by the eye mark recorder. Analysis examined the screen interface of the operation panel from the field of a fixation point trace. The top down type fixation oder by experience or the context became clear as a result. Furthermore, the difference of the fixation order by skill level was also examined. In this study, it was assumed that to grasp the visual cognitive characteristics becomes the key of efficient information.

• Journal of Digital Convergence
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• v.12 no.1
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• pp.241-251
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• 2014

Mobile messenger services (MMSs), such as Kakaotalk, Wetalk, Line, and Whatsapp, are gaining popularity worldwide because of communicating with other people without any cost. We examined key antecedents of user loyalty to understand user's decision-making process in the MMS environment. To capture a long-term relationship with service providers, we posit relational commitment and user satisfaction as key predictors of user loyalty. Moreover, the effects of perceived usefulness, perceived enjoyment, and corporate image on user's decision-making processes were examined. The proposed model was tested by applying partial least squares to data from 220 experienced Kakaotalk users. The findings of this study found that both relational commitment and user satisfaction play an important role in enhancing user loyalty in the MMS context. The analysis results indicate that corporate image influences relational commitment and user loyalty through user satisfaction. The analysis results help MMS providers establish management or marketing strategies to effectively improve user loyalty.

• Journal of the Korean Institute of Intelligent Systems
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• v.21 no.4
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• pp.463-468
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• 2011

Context prediction methods have been developed in two ways - one is a prediction for discrete context and the other is for continuous context. As most of the prediction methods have been used with prediction algorithms in specific domains suitable to the environment and characteristics of contexts, it is difficult to conduct a prediction for a user's context which is based on various environments and characteristics. This study suggests a context prediction method available for both discrete and continuous contexts without being limited to the characteristics of a specific domain or context. For this, we conducted a context prediction based on sequence matching by generating sequences from contexts in consideration of association rules between context attributes and by applying variable weights according to each context attribute. Simulations for discrete and continuous contexts were conducted to evaluate proposed methods and the results showed that the methods produced a similar performance to existing prediction methods with a prediction accuracy of 80.12% in discrete context and 81.43% in continuous context.

• Journal of KIISE:Computing Practices and Letters
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• v.12 no.1
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• pp.31-42
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• 2006

Context-awareness is a technology to facilitate information acquisition and execution by supporting interoperability between users and devices based on users' context. It is one of the most important technologies in ubiquitous computing. In this paper, we propose a middleware and a context server for dealing with context-awareness in ubiquitous Computing and implement an application system using them. The middleware proposed in our work plays an important role in recognizing a moving node with mobility by using a Bluetooth wireless communication technology as well as in executing an appropriate execution module according to the context acquired from a context server. In addition, the proposed context server functions as a manager that efficiently stores into a database server context information, such as user's current status, physical environment, and resources of a computing system. Finally, our application system implemented in our work one which provides a music playing service based on context information, and it verifies the usefulness of both the middleware and the context server developed in our work.

• KIPS Transactions on Computer and Communication Systems
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• v.5 no.11
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• pp.411-418
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• 2016

Context-aware application has a lot of power consumption because it creates context by using a number of smartphone's sensors. Furthermore, only few kinds of researches have been conducted that provide information for the evaluation result of power consumption in the aspect of applications. In addition, evaluation of power consumption do not consider user's usage pattern or provide only total amount of power consumption, and inform developers power consumption of sensors undistinguishable. It makes developers hard to develop a power consumption-considered application. If developers could get information for power consumption of context-aware application in detail, a development of power-considered context-aware applications would be possible. Consequently, this paper proposes a BMT(Bench Mark Test) model which is able to inform developers useful evaluation criteria and result about power consumption of smartphone's components and sensors with usage pattern considered.

• Journal of Korea Multimedia Society
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• v.14 no.1
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• pp.112-120
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• 2011

This research aims to show that the context adaptation system can be used to develop practical context-aware applications by developing a restaurant recommendation system based on location-awareness. In this research, we have designed and implemented a location-aware restaurant recommendation system which provides a customized restaurant recommendation service based on the user's current context. The context-adaptation engine adapts the application program according to the policy file as contexts are changed, and the application provides restaurant recommendation service based on the changed context like location.