• Archives of design research
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• v.15 no.4
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• pp.121-128
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• 2002

It makes an appearance that multi-media of Avatar, Cyber-Character, Cyber-Pet, Emoticon caused by Web-Environment advancement. Internet-User was fascinated by anonymous name of Web in the past but a desire goes on increasing to express oneself using the multi-media characters. Therefore, this study investigates that the feature of avatar character different from the general characters as making a survey of preference of avatar characters type in the various multi-media characters and presenting an efficient method at the making avatar characters. Consequently, the most efficient avatar characters type have to be concerned about functional factors rather than feature, feeling. exactly, it must be make conspicuous to personality of user and must make suitableness type of personality.

• International journal of advanced smart convergence
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• v.12 no.3
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• pp.200-210
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• 2023

Until now, it is popular to use question-and-answer-based for human personality. The current inspection of representative personality types includes Myers-Briggs Type Indicator (MBTI) and job suitability evaluations. The problem of these inspection methods is influenced by the user's environment and psychological status during MBTI inspection. To solve this problem, we proposed MBTI Identification Model based on measuring bioelectricity patterns. We adapt traditional Korean medicine, the Eight Constitution, to this model. We develop an automatic MBTI identification algorithm that maps the Eight Constitution via biological current patterns to identify MBTI personality types. By utilizing the algorithm proposed in this research, it is anticipated that users will be able to measure MBTI more easily and accurately.

• Journal of information and communication convergence engineering
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• v.18 no.1
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• pp.55-60
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• 2020

As personalized customer services create a society that emphasizes the personality of an individual, the number of product reviews and quantity of user data generated by users on the internet in mobile shopping apps and sites are increasing. Such product review data are classified as unstructured data. Unstructured data have the potential to be transformed into information that companies and users can employ, using appropriate processing and analyses. However, existing systems do not reflect the detailed information they collect, such as user characteristics, purchase preference, or purchase priority while analyzing review data. Thus, it is challenging to provide customized recommendations for various users. Therefore, in this study, we have developed a product recommendation system that takes into account the user's priority, which they select, when searching for and purchasing a product. The recommendation system then displays the results to the user by processing and analyzing their preferences. Since the user's preference is considered, the user can obtain results that are more relevant.

• Journal of the Korean Society for information Management
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• v.29 no.3
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• pp.169-186
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• 2012

This study examined the relation between personality types and users' searching trait and satisfaction when interacting with OPAC system. In this study, personality type was measured by the KEPTI Enneagram tools. Data was collected through four questionnaires, pre-test, TaskA, TaskB, and post-test survey. The results indicated that there was a statistically significant difference in perceptions on the expected ease of search, completion time, adequacy of search time, usefulness of search results, and performed ease of search within the Three Triads of Enneagram. Also a statistically significant difference was found on familiarity and interest in the selected queries within the Hornivian group.

• Journal of the Korea Society of Computer and Information
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• v.28 no.1
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• pp.9-16
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• 2023

In the IoT environment, various objects mutually interactive, and various services can be composed based on this environment. In the previous study, we have developed a resource collaboration system to provide services by substituting limited resources in the user's personal device using resource collaboration. However, in the preceding system, when the number of resources and situations increases, the inference time increases exponentially. To solve this problem, this study proposes a method of classifying users and resources by applying the BIG5 user type classification model. In this paper, we propose a method to reduce the inference time by filtering the user's preferred resources through BIG5 type-based preprocessing and using the filtered resources as an input to the recommendation system. We implement the proposed method as a prototype system and show the validation of our approach through performance and user satisfaction evaluation.

• Science of Emotion and Sensibility
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• v.15 no.2
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• pp.239-248
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• 2012

This paper looks to extract personality traits from the drama characters within a drama script, and to apply it them to a character that has an artificial emotion. The method of applying the personality of a character from a drama script is as follows. First, we separate a drama script into several pieces, by the characters therin. Next, we extract emotion-related terms by matching morphemes analysis and by using an emotion terms database. Next, we analyze a dominant emotion using extracted emotion terms. Finally last, we apply the analyzed dominant emotion to an equation pertaining to artificial emotion. We made progress in developing user evaluation that features blind testing, to verify that the artificial emotion character bears the personality of a drama character. We apply three drama character personalities to artificial emotion characters bearing the same appearance. The user had to match three artificial emotion characters and drama characters according to personality. The users had a high percentage of correct answers, thus confirming the efficacy of our method of applying a personality, using information from a drama script.

• Journal of the Korea Society of Computer and Information
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• v.16 no.1
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• pp.153-161
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• 2011

Focusing upon the post-adoption stage of IS, this study reasoned that IS users' personality is one of major influencing factors of continuous IS usage intention and empirically examined how the degree of continuous IS usage intention is variable according to the IS users' personality types classified based on MBTI(Myers Briggs Type Indicator). In order to validate the research model and hypotheses, this study made a field survey of 330 IS users and statistically analysed response data. The results of empirical analyses showed that the intent of continuous IS usage was affected by self-efficacy of IS; and self-efficacy by self-leadership of IS; and self-leadership by IS user' personality type and expectation confirmation. That is, it was found that IS users' personality type and three intervening variables(expectation confirmation, self-leadership and self-efficacy) were significant predictors of the intent of continuous IS usage. This study is thought to be contributive to providing the theoretical basis of finding IS success factors in the post-adoption stage and the practical guideline for effective personnel management relevant to IS implementation.

• Journal of Korean Library and Information Science Society
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• v.35 no.4
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• pp.229-250
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• 2004

The purpose of this study is to investigate the correlation between users' preferences of Personality types and their attitude towards patterns of Web OPAC use mainly focus on their search behaviour and their preferences for the interface. Data res collected through the MBTI test and self-designed online questionnaire. The original MBTI personality types were re-coded into 4 categories of preferences of personality types, that is, E(Extraversion), I(Introversion), S(Sensing), N(iNtuition), T(Thinking)-F(Feeling), and J(Judging)-P(Perception) and then analysed their correlation with patterns of Web OPAC use by Person's correlation coefficient (r) in SPSS Windows Ver. 11.0. It is noteworthy that 9 out of 28 factors of Web OPAC search behaviour and preferences for interfaces show statistically significant correlation with users' MBTI preferences of personality types.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2013.10a
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• pp.569-572
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• 2013

Using flow theory as our foundation, we empirically tested the impact of three personality traits on the level of flow state experience and three user-generated content (UGC) usage types. Findings indicate that extroversion is positively related to the use of UGCs for entertainment, and negatively related to the use of UGCs for communication and information; neuroticism is positively related to the use of UGCs for entertainment and communication; and psychoticism is negatively related to the use of UGCs for information. In addition, only extroversion has an influence on flow, which is positive, and flow has a positive influence on UGC usage for entertainment and communication. This study extends flow theory by exploring antecedents and outcomes of the flow state experience.

• IEMEK Journal of Embedded Systems and Applications
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• v.3 no.2
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• pp.91-101
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• 2008

For a friendly interaction between human and robot, emotional interchange has recently been more important. So many researchers who are investigating the emotion generation model tried to naturalize the robot's emotional state and to improve the usability of the model for the designer of the robot. And also the various emotion generation of the robot is needed to increase the believability of the robot. So in this paper we used the hybrid emotion generation architecture, and defined the generalized context input of emotion generation model for the designer to easily implement it to the robot. And we developed the personality and loyalty model based on the psychology for various emotion generation. Robot's personality is implemented with the emotional stability from Big-Five, and loyalty is made of familiarity generation, expression, and learning procedure which are based on the human-human social relationship such as balance theory and social exchange theory. We verify this emotion generation model by implementing it to the 'user calling and scheduling' scenario.