• KIPS Transactions on Software and Data Engineering
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• v.11 no.11
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• pp.447-454
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• 2022

In the era of the 4th industrial revolution, we are living in a flood of information. It is very difficult and complicated to find the information people need in such an environment. Therefore, in the flood of information, a recommendation system is essential. Among these recommendation systems, many studies have been conducted on each recommendation system for movies, music, food, and clothes. To date, most personalized recommendation systems have recommended clothes, books, or movies by checking individual tendencies such as age, genre, region, and gender. Future generations will want to be recommended clothes, books, and movies at once by checking age, genre, region, and gender. In this paper, we propose a recommendation system that recommends personalized clothes and food at once according to the user's emotions and weather. We obtained user data from Twitter of social media and analyzed this data as user's basic emotion according to Paul Eckman's theory. The basic emotions obtained in this way were converted into colors by applying Hayashi's Quantification Method III, and these colors were expressed as recommended clothes colors. Also, the type of clothing is recommended using the weather information of the visualcrossing.com API. In addition, various foods are recommended according to the contents of comfort food according to emotions.

• The Journal of the Korea Contents Association
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• v.18 no.7
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• pp.165-176
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• 2018

With the development of information and communication technology, the possibility of utilizing 3D virtual reality in education has been sought. Especially, the screen composition in the virtual reality has the possibility of inducing the emotion of the user which may affect the learning. However, there is little research on what aspects of the screen can cause emotions. The purpose of this study is to analyze the user's perception of screen components inducing emotion in virtual reality learning environment. Using Multi Dimensional Scaling (MDS), the user's perception of the main screen in a representative virtual reality learning environment platform was investigated. As a result, the dimension of depth on the screen and the dynamics of the avatar related to the movement were confirmed. This study is meaningful to explore technical variables that can induce emotions among screen elements in virtual reality contents.

• Journal of Korea Multimedia Society
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• v.10 no.4
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• pp.506-515
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• 2007

In this paper, we propose a Real-time Interactive Shadow Avatar(RISA) which can express facial emotions changing as response of user's gestures. The avatar's shape is a virtual Shadow constructed from the real-time sampled picture of user's shape. Several predefined facial animations overlap on the face area of the virtual Shadow, according to the types of hand gestures. We use the background subtraction method to separate the virtual Shadow, and a simplified region-based tracking method is adopted for tracking hand positions and detecting hand gestures. In order to express smooth change of emotions, we use a refined morphing method which uses many more frames in contrast with traditional dynamic emoticons. RISA can be directly applied to the area of interface media arts and we expect the detecting scheme of RISA would be utilized as an alternative media interface for DMB and camera phones which need simple input devices, in the near future.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.48 no.2
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• pp.102-108
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• 2011

The existing vessels lighting control system has several problems, which are complexity of construction and high cost of establishment and maintenance. In this paper, We designed low cost and high performance lighting control system at digital vessel environment. We proposed a system which recognize the user's emotions after obtaining the biological informations about user's bio information(pulse sensor, blood pressure sensor, blood sugar sensor etc) through wireless sensors controls the LED Lights. This system classified emotions using backpropagation algorithm. We chose 3,000 data sets to train the backpropagation algorithm. As a result, obtained about 88.7% accuracy. And the classified emotions find the most appropriate point in the method of controlling the waves or frequencies to the red, green, blue LED Lamp comparing with the 20-color-emotion models in the HP's 'The meaning of color' and control the brightness or contrast of the LED Lamp. In this method, the system saved about 20% of the electricity consumed.

• Journal of Korea Game Society
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• v.19 no.5
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• pp.151-164
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• 2019

In this study, we developed a visual novel game as one of the donation campaign strategies. In study 1, we developed a visual novel game for the elderly who live alone. In study 2, we also examine how game affects personal distress and empathic concern, the emotions that trigger help behavior. The results showed that game can promote both emotions effectively. Moreover, empathic concern completely mediated between game and donation intention. This result suggests that visual novel games can be an effective tool for stimulating user's altruistic motivation to do donation behavior.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.67 no.7
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• pp.954-961
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• 2018

In this paper, a chatbot for emotional stress recognition and management using rule-based method and NLP is designed and developed to tackle various emotional stresses of people through questionnaire. For this, Dialogflow as open chatbot development platform and Facebook messenger as chatting platform are used. We can build natural and resourceful conversational experiences through predefined questions by using powerful tools of Dialogflow, and can use developed chatbot on the Facebook page messenger. Developed chatbot perceives emotional stresses of user by user-input which is either text or choice of predefined answer. It also gives user questions according to the user's feeling, and assess the strength of the emotional stresses, and provide a solution to the user. Further research can improve the developed chatbot by using open Korean NLP library and database of emotions and stresses.

• Proceedings of the KAIS Fall Conference
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• 2003.11a
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• pp.10-15
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• 2003

In computer graphics, most animations of characters have been created using the traditional and often highly labor intensive key-framing technique. Recently, character animation is demanded increasingly automated techniques for animation according to interaction with the user or environment of the user. In this paper, we will propose a new method which can animate characters automatical/y with user interactions. The character's behavior is determined as a result of understanding the emotional condition of the user. Psychology and cognitive AI provide some ideas about how to approach this problem. Our study is based mostly on the theories of Ortony, Clore and Collins, which were designed to be implemented computationally. In our system, we can make 22 emotion types and some more behavior features and we apply to some characters.

• Journal of Information Technology Applications and Management
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• v.30 no.5
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• pp.1-19
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• 2023

This study examines Korean users' attitudes and emotions toward Melon and Spotify, which lead the music streaming market. We used Text Mining, Semantic Network Analysis, TF-IDF, Centrality, CONCOR, and Word2Vec analysis. As a result of the study, MelOn was used in a user's daily life. Based on Melon's advantages of providing various contents, the advantage is judged to have considerable competitiveness beyond the limits of the streaming app. However, the MelOn users had negative emotions such as anger, repulsion, and pressure. On the contrary, in the case of Spotify, users were highly interested in the music content. In particular, interest in foreign music was high, and users were also interested in stock investment. In addition, positive emotions such as interest and pleasure were higher than MelOn users, which could be interpreted as providing attractive services to Korean users. While previous studies have mainly focused on technical or personal factors, this study focuses on consumer reactions (online reviews) according to corporate strategies, and this point is the differentiation from others.

• The Journal of the Korea Contents Association
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• v.10 no.12
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• pp.352-365
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• 2010

Most of studies concerned with on-line Brand community show that it makes users to increase their brand loyalty and brand attachment. But it wouldn't be explained that on-line brand community could be the field of consumer's public complaining in service failure. So, this study tried to focus the dimensions of negative emotions and customer characteristics that may cause relationship dissolutions in on-line brand community. The findings of the present study following as, high relationship quality of on-line brand community user directly effects negative emotions, especially, disappointment and betrayal. second, disappointment and betrayal influences the desire of revenge. Third, customer's negative reactions (for example, negative replies about the brand or public complaining in community) are mediated by customer's desire of revenge. The analysis was held with brand community customers who has been experienced service recently by using SPSS14K and Smart PLS 2.0. The study verified the structural equation model hypothesizing the between emotional factors and negative reactions. In conclusion, this article provides implications into understanding of customer's negative emotions and user's characteristics that cause negative reactions in on-line brand community. thus, this may allow marketers to have managerial insights on handling of on-line brand community independently operated by consumers.

• KIISE Transactions on Computing Practices
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• v.21 no.2
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• pp.160-165
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• 2015

Traditional speech emotion recognition techniques recognize emotions using a general training model based on the voices of various people. These techniques can not consider personalized speech character exactly. Therefore, the recognized results are very different to each person. This paper proposes an adaptive speech emotion recognition framework made from user's' immediate feedback data using a prompted labeling technique for building a personal adaptive recognition model and applying it to each user in a mobile device environment. The proposed framework can recognize emotions from the building of a personalized recognition model. The proposed framework was evaluated to be better than the traditional research techniques from three comparative experiment. The proposed framework can be applied to healthcare, emotion monitoring and personalized service.