• Journal of the Korea Society of Computer and Information
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• v.28 no.12
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• pp.57-66
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• 2023

In this study, we propose a novel research framework for the recommendation system that can estimate the user's emotional state and reflect it in the recommendation process by applying deep learning techniques and emotion AI (artificial intelligence). To this end, we build an emotion classification model that classifies each of the seven emotions of angry, disgust, fear, happy, sad, surprise, and neutral, respectively, and propose a model that can reflect this result in the recommendation process. However, in the general emotion classification data, the difference in distribution ratio between each label is large, so it may be difficult to expect generalized classification results. In this study, since the number of emotion data such as disgust in emotion image data is often insufficient, correction is made through augmentation. Lastly, we propose a method to reflect the emotion prediction model based on data through image augmentation in the recommendation systems.

• Proceedings of the IEEK Conference
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• 2003.07d
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• pp.1243-1246
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• 2003

It is known that structure of Human's brain information system is controlled by cerebral cortex mainly. Cerebral cortex is divided by sensory area, motor area and associated area largely. Sensory area takes part in information from environment and motor area is actuation by decision as associated area determined. It is possible to copy brain information system by input-output pattern. but there is difficulty in modeling of memorizing new information. Such action is performed by Limbic Lobe and Papez circuit which is controlled by intrinsic emotion. So we need of definition of emotion's role in decision. In this paper, we define roles of emotion in intrinsic decision using Dynamic Cognitive Maps(DCMs). The emotion is evaluated by outside information then intrinsic decision performed as how much emotion variated. The dynamic cognitive maps take part in emotion evaluating process.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.4 no.1
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• pp.18-22
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• 2004

It is difficult to understand a person's emotion, since it is subjective and vague. Therefore, we are proposing a method by which will effectively classify human emotions into two types (that is, single emotion and composition emotion). To verify validity of te proposed method, we conducted two experiments based on general inference and $\alpha$-cut, and compared the experimental results. In the first experiment emotions were classified according to fuzzy inference. On the other hand in the second experiment emotions were classified according to $\alpha$-cut. Our experimental results showed that the classification of emotion based on a- cut was more definite that that based on fuzzy inference.

• The Korean Journal of Coaching Psychology
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• v.7 no.1
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• pp.1-31
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• 2023

The purpose of this study is to verify the mediating effect of adaptive cognitive emotion regulation and the moderating effect of supervisor's emotional regulation in the relationship between the emotion recognition and negative feedback acceptance of employees. The data was collected from 273 non-managerial workers in various domestic companies. Confirmatory factor analysis was conducted with AMOS 22 to verify the reliability and validity of the measurement tool, and the mediating and moderating effects were examined using SPSS Process Macro to verify the hypothesis. The results of this study are summarized as follows. First, emotion recognition of employees indirectly affects the acceptance of negative feedback through adaptive cognitive emotional regulation. Second, the effect of emotion recognition on negative feedback acceptance is moderated by supervisor's emotion regulation. Specifically, it was confirmed that when the supervisor's emotional control is low, the relationship between emotional recognition and negative feedback acceptance becomes stronger. Based on the results of the study, it was confirmed that the level of awareness of oneself and others' emotions was psychological process of accepting performance-related feedback, and the importance of supervisor's emotional regulation in positively accepting negative feedback. Finally, based on the research results, the academic significance of this study, implications in coaching practice, limitations, and future research were discussed.

• Proceedings of the Korean Society for Emotion and Sensibility Conference
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• 2011.05a
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• pp.43-44
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• 2011

• Science of Emotion and Sensibility
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• v.14 no.2
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• pp.257-268
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• 2011

We define a 'dominant emotion' as acting dominantly for unit time, and propose methodology to extract dominant emotion in a literature automatically. Due to the nature of the Korean language, it is able to be changed or reversed owns meanings as desinence. But it might be possible to extract a dominant emotion in a text has a small quantity like a fiction or an essay. A process to extract a dominant emotion in a literature is as follows. At first, extract morphemes in a whole text. And dispart words having emotional meaning as matching emotion terms database. Map disported terms to a affective circumplex model and matching it with basic emotion. Finally, analyze dominant emotion according to matched basic emotion. And we adjust our methodology to two literature; modem fiction 'A lucky day' by Jingeon, Hyun and essay 'An old man who shave a bat' by Woyoung, Yun. As a result, it was possible to grasp flows of dominant emotion.

• Journal of KIISE:Software and Applications
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• v.32 no.3
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• pp.141-152
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• 2005

A new emotion-based image retrieval method is proposed in this paper. Query emotion descriptors called query color code and query gray code are designed based on the human evaluation on 13 emotions('like', 'beautiful', 'natural', 'dynamic', 'warm', 'gay', 'cheerful', 'unstable', 'light' 'strong', 'gaudy' 'hard', 'heavy') when 30 random patterns with different color, intensity, and dot sizes are presented. For emotion image retrieval, once a query emotion is selected, associated query color code and query gray code are selected. Next, DB color code and DB gray code that capture color and, intensify and dot size are extracted in each database image and a matching process between two color codes and between two gray codes are peformed to retrieve relevant emotion images. Also, a new relevance feedback method is proposed. The method incorporates human intention in the retrieval process by dynamically updating weights of the query and DB color codes and weights of an intra query color code. For the experiments over 450 images, the number of positive images was higher than that of negative images at the initial query and increased according to the relevance feedback.

• Science of Emotion and Sensibility
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• v.6 no.2
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• pp.1-7
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• 2003

The objectives of this study is to develop an adaptable digital wall model whose color can be changed dynamically according to the identified emotional state of a user. This study addresses how to capture a specific user's emotion through the web and use it for modifying VR model mainly for color adaptation. This adaptation process of a VR model consists of three phases: 1) identification of the user's emotional state projected onto the list of emotional keywords 2) translation of those captured emotional keywords into a pertinent set of color coordinations, and finally, 3) automated color adaptation process for the given model. This process derives an on-line viewer's emotional state, which can be utilized to find a new color scheme reflecting the identified emotion.

• Science of Emotion and Sensibility
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• v.21 no.3
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• pp.83-102
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• 2018

The process model of emotion regulation suggests that cognitive reappraisal and expressive suppression engage at different time points in the regulation process. Although multiple brain regions and networks have been identified for each strategy, no articles have explored changes in network characteristics or network connectivity over time. The present study examined (a) the whole-brain network and six other resting-state networks, (b) their modularity and global efficiency, which is an index of the efficiency of information exchange across the network, (c) the degree and betweenness centrality for 160 brain regions to identify the hub nodes with the most control over the entire network, and (d) the intra-network and inter-network functional connectivity (FC). Such investigations were performed using a traditional large-scale FC analysis and a relatively recent sliding window correlation analysis. The results showed that the right inferior orbitofrontal cortex was the hub region of the whole-brain network for both strategies. The present findings of temporally altering functional activity of the networks revealed that the default mode network (DMN) activated at the early stage of reappraisal, followed by the task-positive networks (cingulo-opercular network and fronto-parietal network), emotion-processing networks (the cerebellar network and DMN), and sensorimotor network (SMN) that activated at the early stage of suppression, followed by the greater recruitment of task-positive networks and their functional connection with the emotional response-related networks (SMN and occipital network). This is the first study that provides neuroimaging evidence supporting the process model of emotion regulation by revealing the temporally varying network efficiency and intra- and inter-network functional connections of reappraisal and suppression.

• Science of Emotion and Sensibility
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• v.6 no.3
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• pp.29-43
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• 2003

This study examined the difference in memories for emotional stimuli. After giving participants the memory task instruction that they should remember the given stimuli, the emotion-induced photographs and the neutral photographs were presented. To minimize the possibility to regulate the expressions of their mood which induced by emotional stimuli and to find out whether the antecedent-focused emotion regulation process would damaged the memory of emotional stimuli in men, participant's memory was measured directly after the presentation of each photograph by free reflection method. Also Sex differences in memories about emotional and neutral stimuli were measured and compared. Women memorized stimuli more than men, and as expected, women remembered more about the emotional stimuli than neutral ones. The analysis of sex difference about central and peripheral features indicated that women remembered central features of emotional stimulus more than those of neutral ones, but that men had no difference between central features of emotional stimuli and those of neutral ones. These results showed that men's damaged memories of emotional stimuli were caused by the antecedent-focused emotion regulation process.