• Journal of the Korea Institute of Information Security & Cryptology
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• v.26 no.6
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• pp.1493-1504
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• 2016

As cyber threats have been increased over the Internet, the invasions of personal information are constantly occurring. A malicious user can access the Web site as a normal user using leaked personal information and does illegal activities. This paper proposes an effective method which authenticates a genuine user with real-time. The method use the user's profile which is a record of user's behavior created by Membership Analysis(MA) and Markov Chain Model(MCM). In addition to, user's profile is augmented by a Time Weight(TW) which reflects the user's tendency. This method can detect a malicious user who camouflage normal user. Even if it is a genuine user, it can be determined as an abnomal user if the user acts beyond the record profile. The result of experiment showed a high accuracy, 96%, for the correct user.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2001.04a
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• pp.833-836
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• 2001

The thermomechanical behaviors of the shape memory alloy were conducted through the finite element analysis of ABAQUS with UMAT user subroutine. The unified thermomechanical constitutive equation suggested by Lagoudas was adapted into the UMAT user subroutine to investigate the characteristics of the shape memory alloy. The three cases were solved to investigate the thermomechanical characteristics of the shape memory alloy. The material properties for the analysis were obtained by DSC and DMA techniques. According to the results, the thermomechanical characteristics, such as a shape memory effect and a pseudoelastic effect, could be obtained through the finite element analysis and the analysis results were revealed to agree well with the experimental results. Therefore, the finite element analysis using UMAT user subroutine is one of prominent analysis techniques to investigate the thermomechnical behaviors of the shape memory alloy quantitatively.

• Journal of the Korean Society for Library and Information Science
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• v.23
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• pp.107-125
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• 1992

The purpose of this study is to investigate the research trend of information user studies. The following findings are made. The literature on information user studies during 1980-1990 reveals 120 titles. The faculty members of university tend to publish their results in scientific journals and university publication while non-faculty members are more likely to represent their research papers in unpublished master thesis and bulletin. Subject distribution of research were classified into ten: user studies, material use studies, information needs and uses, user education, library use pattern, citation analysis, journal use, catalog use, information system, non-use study. Survey research, literature research, survey reserch and literature research use jointly, experimental research and citation analysis were employed for information user studies.

• Proceedings of the ESK Conference
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• 1994.04a
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• pp.7-18
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• 1994

Many office tasks have been automated by using computers to increase task productivity. The productivity of performing office tasks is dependent not only upon automating the task procedures, but also upon the usability of user interfaces. However, the literature lacks human factors research on evaluating the usability of user interface styles when they are used for performing different office tasks. This study evalu- ated the usability of user interfaces styles when performing various office tasks. User interface styles considered include menu-selection, command language, form fill-in, iconic styles, etc. A task analysis was conducted toclassify representative office tasks. A variety of analysis techniques such as brainstorming, analytic hierarchy process, prototyping, and expert opinions were used to evaluate the usability of the interfaces. The analysis procedures and results are described along with guidelines for selecting user interfaces in terms of subjective preferences and performance measures.

• Archives of design research
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• v.15 no.4
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• pp.399-408
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• 2002

According to the improvement in quality of life and the progress of user's taste in this modern society, people great deal with the symbolic meaning of product which express user's self-concept(image). Therefore, this kind of information of users' image is needed to deal importantly for the product design development processes, particularly, the early stage of design development such as the concept design development stage. But, there is not much analysis tools which deal qualitative data of users for the design development. From this reason, the supply of information of user's image through the development of verbal analysis method of user's self-concept will help a designer. For this purpose, this study not only developed the twenty-one factors in order to evaluate user's self-concept, but also suggested that the new approach method that can classify user's group within the same characteristic of user's image using the twenty-one developed verbal measurement items with tools of statistical analysis for the design direction of product. The developed this verbal analysis tool was testified through the case study in this research work.

• Journal of Korea Society of Digital Industry and Information Management
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• v.19 no.1
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• pp.91-107
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• 2023

With the recent expansion of the commerce ecosystem, a large number of user evaluations have been produced. Accordingly, attempts to create business insights using user evaluation data have been actively made. However, since user evaluation can change after the user experiences the product, it is difficult to say that the analysis based only on reviews immediately after purchase fully reflects the user's evaluation of the product. Moreover, studies conducted so far on user evaluation have overlooked the fact that the length of time a user has used a product can affect the user's product evaluation. Therefore, in this study, we build a model that predicts the direction of change in the user's rating after use from the user's rating and reviews immediately after purchase. In particular, the proposed model reflects the product's period of use in predicting the change direction of the star rating. However, since the posterior information on the duration of product use cannot be used as input in the inference process, we propose a structure that utilizes information about the product's period of use using an auxiliary classifier. As a result of an experiment using 599,889 user evaluation data collected from the shopping platform 'N' company, we confirmed that the proposed model performed better than the existing model in terms of accuracy.

• The Journal of Information Systems
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• v.32 no.3
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• pp.19-39
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• 2023

Purpose This study aims to identify user experience factors that can enhance both metaverse utilization and satisfaction based on the honeycomb model. For this we presented two research questions: first, what are the experience factors of metaverse users? Second, do metaverse user experience factors impact satisfaction? Design/methodology/approach To address these questions, a mixed-methodology approach is employed, including text mining techniques to analyze online reviews and quantitative econometric analysis to reveal the relationship between user experience factors and satisfaction. A total of 69,880 reviews and ratings data were collected. Findings The analysis revealed eight metaverse user experience factors: entertainment, operability, virtual reality, immersion, economic activity, visual performance, avatar, and sociality, all of which were found to have a positive impact on user satisfaction.

• Journal of the Korean Society for information Management
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• v.37 no.2
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• pp.353-379
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• 2020

This study developed a user experience factors for the evaluation of knowledge and information resource system from the user experience perspectives, which is emerging as a new analysis standard in the field of information media and information service research. Based on the analysis criteria selected through literature analysis, 'system perception factor' and 'user experience factor' were derived as factors influencing the use of information systems through an experimental study based on the user experience sampling method. As a result, the user experience factors of final knowledge and information resource system includes nine user experience factors, 55 detailed user experience factors, and 138 system perception factors. This study is significant in that the abstract concept 'user experience' was derived and presented as a practical, concrete, measurable factor through experiments. The derived user experience factors should serve as a basis for measuring user experience perceived by users of the knowledge and information resource system.

• Management Science and Financial Engineering
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• v.12 no.2
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• pp.71-85
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• 2006

Collaborative filtering, among other recommender systems, has been known as the most successful recommendation technique. However, it requires the user-item rating data, which may not be easily available. As an alternative, some collaborative filtering algorithms have been developed recently by utilizing the market basket data in the form of the binary user-item matrix. Viewing the recommendation scheme as a two-class classification problem, we proposed a new collaborative filtering scheme using a regularized discriminant analysis applied to the binary user-item data. The proposed discriminant model was built in terms of the major principal components and was used for predicting the probability of purchasing a particular item by an active user. The proposed scheme was illustrated with two modified real data sets and its performance was compared with the existing user-based approach in terms of the recommendation precision.

• Journal of the military operations research society of Korea
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• v.35 no.3
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• pp.101-117
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• 2009

The objective of this study is to find relations between success factors of project management and user satisfaction and usage for analysis report. According to emprical study, the main factors that affect user satisfaction are requirement and proper planning. And the main factors that affect usage are expert of analysis, proper planning and user satisfaction.