• KSII Transactions on Internet and Information Systems (TIIS)
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• v.15 no.1
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• pp.1-19
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• 2021

The graph-based tag recommendation algorithm FolkRank can effectively utilize the relationships between three entities, namely users, items and tags, and achieve better tag recommendation performance. However, FolkRank does not consider the internal relationships of user-user, item-item and tag-tag. This leads to the failure of FolkRank to effectively map the tagging behavior which contains user neighbors and item neighbors to a tripartite graph. For item-item relationships, we can dig out items that are very similar to the target item, even though the target item may not have a strong connection to these similar items in the user-item-tag graph of FolkRank. Hence this paper proposes an improved FolkRank algorithm named FolkRank++, which fully considers the user-user and item-item internal relationships in tag recommendation by adding the correlation information between users or items. Based on the traditional FolkRank algorithm, an initial weight is also given to target user and target item's neighbors to supply the user-user and item-item relationships. The above work is mainly completed from two aspects: (1) Finding items similar to target item according to the attribute information, and obtaining similar users of the target user according to the history behavior of the user tagging items. (2) Calculating the weighted degree of items and users to evaluate their importance, then assigning initial weights to similar items and users. Experimental results show that this method has better recommendation performance.

• Science of Emotion and Sensibility
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• v.19 no.4
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• pp.13-20
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• 2016

Recently, life-logging service which has expanded to measure and record the daily life of the users and to share with others are increasing. In particular, as life-logging services based on the application has become popular with the development of wearable-devices and smart-phones, the contents of this service are produced by user behavior and are provided in infographic menu form. The purpose of this paper is to extract user behavior and classify for making contents items of life-logging service. For this paper, the first of all, we discuss the definition and characteristics of life-logging and research the contents based on user behavior related to life-logging by the publications including thesis, articles, and books. Secondly, we extract and classify the user behavior to build the contents for life-logging service. We gather users' action words from publication materials, researches, and contents of existing life-logging service. And then collected words are analyzed by FGI (Focus Group Interview) and survey. As the result, 39 words which suit for contents of life-logging service are extracted by verify suitability. Finally, the extracted 39 words are classified for 19 categories -'Eat', 'Keep house', 'Diet', 'Travel', 'Work out', 'Transit', 'Shoot', 'Meet', 'Feel', 'Talk', 'Care for', 'Drive', 'Listen', 'Go online', 'Sleep', 'Go', 'Work', 'Learn', 'Watch' - which are suggested by the surveys, statistical analysis, and FGI. We will discuss the role and limitations of this results to build contents configuration based on life-logging application in this study.

• Journal of the Korea Convergence Society
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• v.11 no.7
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• pp.1-7
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• 2020

As the performance of mobile devices has dramatically improved, users can perform many tasks in a mobile environment. This means that the use of behavior information stored in the mobile device can tell a lot of users. For example, a user's text message and frequently used application information (behavioral information) can be utilized to create useful information, such as whether the user is interested in parenting(profile prediction). In this study, I investigate the behavior information of the user that can be collected in the mobile device and propose the item that can profile the user. And I also suggest ideas about how to utilize profiling information.

• Journal of the Korean Society for Library and Information Science
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• v.37 no.4
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• pp.295-310
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• 2003

This study used content analysis to examine research methods and trends of the user study articles from 1991 to 2003. Analysis measured research subjects, research method, data collection methods, data analysis methods, hypotheses. The average yearly papers in the case of scholarly journal - 2.8 pieces. The year published the largest number of papers is 2001. The order of the number of papers information behavior, user study, user interface, user education, OPAC use. Used research methods are literature search and survey research, data analysis methods are $X^2$, correlation and T-test.

• International Journal of Computer Science & Network Security
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• v.23 no.8
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• pp.63-76
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• 2023

Identity and access management in cloud computing is one of the leading significant issues that require various security countermeasures to preserve user privacy. An authentication mechanism is a leading solution to authenticate and verify the identities of cloud users while accessing cloud applications. Building a secured and flexible authentication mechanism in a cloud computing platform is challenging. Authentication techniques can be combined with other security techniques such as intrusion detection systems to maintain a verifiable layer of security. In this paper, we provide an interactive, flexible, and reliable multi-factor authentication mechanisms that are primarily based on a proposed Authentication Method Selector (AMS) technique. The basic idea of AMS is to rely on the user's previous authentication information and user behavior which can be embedded with additional authentication methods according to the organization's requirements. In AMS, the administrator has the ability to add the appropriate authentication method based on the requirements of the organization. Based on these requirements, the administrator will activate and initialize the authentication method that has been added to the authentication pool. An intrusion detection component has been added to apply the users' location and users' default web browser feature. The AMS and intrusion detection components provide a security enhancement to increase the accuracy and efficiency of cloud user identity verification.

• Proceedings of the Korea Society of Design Studies Conference
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• 1998.04a
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• pp.6-7
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• 1998

• Journal of The Korea Institute of Healthcare Architecture
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• v.21 no.2
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• pp.45-53
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• 2015

Purpose: This study is to derive the behavioral characteristics of the users appear in the outpatient department of psychiatry. Methods: By referencing John Zeisel's Tools for environment-behavior research, observation of user behavior and expert interviews as a method of the study has been carried out. Results: The results of this study are as follows. First, adjacent placement among children, youth and regular the outpatient department of psychiatry is necessary and easy access to internal medicine department and family medicine department is required in order to allow cooperated treatments. Secondly, depending on the characteristics of the outpatient department of psychiatry treatment, adjustment of space requirement or the change of kinds of necessary space is required. Third, considering the psychological and behavioral characteristics of mental illness and guardians, various search for the environment that can support this. Implications: This study is a basic research for space improvement and evaluation of the outpatient department of psychiatry, and need to be followed by further study using various perspectives and methods.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.13 no.3
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• pp.71-78
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• 2013

In this paper, we propose a method to infer the user's behavior and situation through collected data from multi-sensor equipped with a smart clothing and it was implemented as a smartphone App. User context reasoning and behavior determine is very difficult using single sensor depending on the measured value of the sensor varies from environmental noise. So, the reasoning and the digital filter algorithms to determine user behavior reducing noise and are required. In this paper, we used EWMA, Kalman Filter and SVM processing behavior for 3-axis value as a representative value of one.

• Korean Institute of Interior Design Journal
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• v.17 no.6
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• pp.188-196
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• 2008

The study aims to find out the changing aspects of contemporary Korean libraries so called public in terms of their spatial configuration. In so doing, it analysed 14 recently built libraries by investigation of user's behavior. Interview and observation were conducted as a method of investigation. The method of analysis was based on statistics by mapping spatial data. As the result, it could be said that most users have a clear goal in Korea. In some libraries, the distinct characteristics of behavior show that users visit other functional rooms including functional rooms for the purpose. It could be said that the configuration of space in recently public libraries become more public as a place. In view of domestic affairs, in terms of users need, the reading room for personal study have features of the most private room and a static activity. so that the reading room separate from the other functional rooms in floor, but it adjoin other functional rooms in the horizontal configuration. so its location make offset a role of functional rooms can be interactive with each other, except reading room.

• Journal of Information Technology Services
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• v.16 no.1
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• pp.119-138
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• 2017

Mobile easy payment is a term for using mobile devices to facilitate financial transactions. Mobile easy payment is a quickly emerging practice, supported by the dramatic increase of mobile phone or device users around the world. The purpose of this study is to classify user's group of the mobile easy payment service by their lifestyle based on I-VALS type and to investigate differences in usage behavior among the user groups. For empirical study, a questionnaire survey was carried out with users of mobile easy payment services using the Internet from June 7 to 10 in 2016. We conducted factor analysis for I-VALS, usage factors, satisfaction factors. We also performed cluster analysis for group classification, and analysis of variance, cross analysis to compare the different usage behavior among the user groups. In analysis results, first three cluster appeared including "ICT task-oriented group", ICT positive and socialities oriented group", "ICT leader-oriented group". Second, it was found significant differences among the clusters about factor of "easy of use", "securities", "universality", "satisfaction". Third, we showed that there were significant differences in time first used the service. Based on these findings, we provide practical implications. Results of our study can be expected to provide the basis of differentiated marketing strategy of mobile easy payment services.