• Proceedings of the Korean Society for Emotion and Sensibility Conference
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• 2008.10a
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• pp.94-97
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• 2008

CD Now, Video Recommender, Amazon 등과 같은 현재의 협업 기반 필터링 서비스는 일반적으로 서비스를 요구하는 사용자가 관심을 가진 아이템과 비슷한 속성의 아이템을 추천하고 있다. 하지만 영화와 같은 경우 사용자의 주관적 평가가 배제된-명시적 속성만으로는 아이템의 특징을 표현하는데 한계가 있다. 때문에 이를 이용한 방법은 서비스를 제공하는 데 있어 제한을 가지게 된다. 따라서 본 논문에서는 소셜 네트워크 서비스 사용자가 영화에 대한 자신의 감정을 간단한 선택을 통해 표현함으로써 쉽고 편하게 사용자의 영화 취향을 도출하고 이를 기반한 소셜 네트워크를 형성하는 방법에 대해 논의해 보고자 한다. 이러한 방법을 통해 일반적으로 사용되는 빈도나 인기도 기반의 추천이 아닌 실제 사용자와 유사한 취향과 특성을 가지는 사용자들은 연결해줌으로써 보다 사용자에 특화된 추천을 가능하게 할 것이다.

• Journal of Distribution Research
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• v.14 no.2
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• pp.67-95
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• 2009

The purpose of this study is to empirically examine the transference of trust process, an important factor to consumer's purchase decision-making. Even though several researchers have discussed the trust transference process, there is no research related to this concept. Specifically we have focused on the transference of trust from the retailer to low involvement private label (PL) products. PL products were chosen as transference of trust occurs under ambiguity due to lack of information about the product and their manufacturer. PL products provide relatively less information than national brand (NB) products. In addition, retailers have been rapidly expanding their PL product categories. To identify the theoretical and empirical limitations of prior studies, we discuss several theories explaining the transference of trust: 'Balance theory' and 'availability heuristic' in transference of cognitive trust; 'affective transference' and 'affect as information' in transference of affective trust. An empirical test was performed. A self completion questionnaire was developed and administered to a convenience sample of PL users. 206 usable questionnaire were received. The results show that the transference of trust plays a mediating role linking the retailer to the manufacturer and to the product. Although our model, which included the transference process of trust as a mediating effect, did not improve the competitive model, the coefficients of the respective paths were found to be better. This study confirms the transference of cognitive trust from the retailer to both the manufacturer and the product, but not for affective trust. We offer the explanation that PL products may tend to have affective trust resulting from brand familiarity but not to their PL manufacturers.

• The Journal of the Korea Contents Association
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• v.15 no.5
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• pp.1-17
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• 2015

In domestic game market, the video game market is getting smaller and also decreasing funds and high level developers. So we need the software that can help us to make more realistic and high quality contents by non-expert developer in poor environments. In this paper, we selected global studio's animations which were scored good evaluation by public and critics as a well-made emotional expression that can convey the emotion properly. We selected movements that express emotions from the animation scripts by using Ekman's 6 basic emotions and Greimas' dynamic predicate, and then we had analyzed and categorized with the data. We also analyzed the movements for which data we needed to create specific movements to express emotions by using 'Animation Layer' that used in Unity's blending process. And suggest concept of the program that to create the emotional expression movements by using those analyzed data.

• Journal of the Korean Institute of Intelligent Systems
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• v.18 no.4
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• pp.494-500
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• 2008

In the field of development of human interface technology, the interactions between human and machine are important. The research on emotion recognition helps these interactions. This paper presents an algorithm for emotion recognition based on personalized speech signals. The proposed approach is trying to extract the characteristic of speech signal for emotion recognition using PLP (perceptual linear prediction) analysis. The PLP analysis technique was originally designed to suppress speaker dependent components in features used for automatic speech recognition, but later experiments demonstrated the efficiency of their use for speaker recognition tasks. So this paper proposed an algorithm that can easily evaluate the personal emotion from speech signals in real time using personalized emotion patterns that are made by PLP analysis. The experimental results show that the maximum recognition rate for the speaker dependant system is above 90%, whereas the average recognition rate is 75%. The proposed system has a simple structure and but efficient to be used in real time.

• Phonetics and Speech Sciences
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• v.12 no.3
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• pp.25-32
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• 2020

An analysis of emotional English utterances with 7 emotions (calm, happy, sad, angry, fearful, disgust, surprised) was conducted using the measurement of prosodic distance between 672 emotional and 48 neutral utterances. Applying the technique proposed in the automatic evaluation model of English pronunciation to the present study on emotional utterances, Euclidean distance measurement of 3 prosodic elements such as F0, intensity and duration extracted from emotional and neutral utterances was utilized. This paper, furthermore, extended the analytical methods to include Euclidean distance normalization, z-score and z-score normalization resulting in 4 groups of measurement schemes (sqrF0, sqrINT, sqrDUR; norsqrF0, norsqrINT, norsqrDUR; sqrzF0, sqrzINT, sqrzDUR; norsqrzF0, norsqrzINT, norsqrzDUR). All of the results from perceptual analysis and acoustical analysis of emotional utteances consistently indicated the greater effectiveness of norsqrF0, norsqrINT and norsqrDUR, among 4 groups of measurement schemes, which normalized the Euclidean measurement. The greatest acoustical change of prosodic information influenced by emotion was shown in the values of F0 followed by duration and intensity in descending order according to the effect size based on the estimation of distance between emotional utterances and neutral counterparts. Tukey Post Hoc test revealed 4 homogeneous subsets (calm

• Journal of Intelligence and Information Systems
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• v.23 no.1
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• pp.109-126
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• 2017

In the various kinds of intelligent services, many studies for detecting emotion are in progress. Particularly, studies on emotion recognition at the particular time have been conducted in order to provide personalized experiences to the audience in the field of exhibition though facial expressions change as time passes. So, the aim of this paper is to build a model to predict the audience's emotion from the changes of facial expressions while watching an exhibit. The proposed model is based on both sequential neural network and the Valence-Arousal model. To validate the usefulness of the proposed model, we performed an experiment to compare the proposed model with the standard neural-network-based model to compare their performance. The results confirmed that the proposed model considering time sequence had better prediction accuracy.

• The Korean Journal of Franchise Management
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• v.13 no.3
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• pp.31-43
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• 2022

Purpose: Service quality is a topic of constant interest in marketing research and practitioners. Service quality is an important factor influencing performance even in the context of coffee shops, and research on service quality management strategies continues by coffee shop researchers and practitioners. The service quality of coffee shops is a source of competitive advantage and is an important factor in enhancing customer and business performance. This study aims to identify the effects of cognitive evaluation on emotional and behavioral responses using a cognitive-emotional-behavioral framework and SOR model in the coffee shop context. Cognitive evaluation (service quality) consists of tangibles, responsiveness, assurance, reliability, and empathy dimensions. Research design, data, and methodology: In the proposed model, positive and negative emotions and satisfaction mediate the relationship between service quality and money to spend and visit frequency. The data were collected from customers who visited a coffee shop within the last 1 month. The survey was conducted for about one month. Among a total of 300 distributed questionnaires 261 responses were used for data analysis. The data were analyzed using frequency analysis, measurement model analysis, and structural equation modeling analysis with SPSS 28.0 and SmartPLS 4.0. Results: Tangibles, responsiveness, assurance, and empathy had significant positive effects on positive emotion, while only reliability had a significant negative effect on negative emotion. Both positive and negative emotions had significant positive effects on customer satisfaction, but not on money to spend and visit frequency. Lastly, customer satisfaction had significant positive effects on money to spend and visit frequency. Conclusions: The study revealed the relative weight of cognitive factors on customer emotions and confirmed the validity of SOR model. The fact that tangibility is the most important factor in increasing positive emotions and reliability is the most important factor in reducing negative emotions provides a direction for emotional branding strategies using the service quality mix of coffee shops. This study confirmed the full mediating role of satisfaction between positive and negative emotions and consumer behaviors (money to spend and visit frequency). This infers that when a coffee shop increases customer satisfaction through customer emotion management, the customer's money to spend and visit frequency in the coffee shop increases.

• Proceedings of the Korean Institute Of Construction Engineering and Management
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• autumn
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• pp.261-266
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• 2001

Recently, remodeling has been introduced in the domestic construction industry as an alternative new construction. Its economic evaluation is the essential part of remodeling business. Therefore, this study has the purpose of presenting the method that is able to evaluate the actual value in the market. And this method can compare before & after value of remodeling in feasibility study. For this, this study reviews economic evaluation methods in construction and real estate fields and analysis their problem and merits & faults. With those facts, this study makes a mixed economic evaluation method that can be used in construction and real estate fields.

• Science of Emotion and Sensibility
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• v.14 no.3
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• pp.403-414
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• 2011

The current study examined brain regions associated with aesthetic experience to fractal images using functional MRI. The aesthetic estimations of the images showed that there is a general consensus regarding the perception of beautiful images. Out of 270 fractal images, fifty images rated highest(beautiful images) and fifty images rated lowest(non-beautiful images) were selected and presented to the participants. The two conditions were presented using the block design. Frontal lobes, cingulate gyri, and insula, the areas related to the cognitive and emotional processing in aesthetic experience, were activated when beautiful images were presented. In contrast, the middle occipital gyri and precuneus, the areas associated with experience of negative emotions, were activated when non-beautiful images were presented. The conjunction analysis showed activations in temporal areas in response to beautiful images and activations in parietal areas in response to non-beautiful images. These results indicate that beautiful images elicit semantic interpretations whereas non-beautiful images facilitate abstract processes.

• Korean Journal of Psychosomatic Medicine
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• v.15 no.2
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• pp.100-106
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• 2007

Objectives : The objective of the present study was to investigate alexithymia in major depressive disorder(MDD) and subclinical depression(SCD). Methods : Three hundred eighty-six community-dwelling adults(238 females and 148 males, age 19-79; mean age $43.0{\pm}13.9$) were recruited. Structured clinical Interview for DSM-IV(SCID) was conducted for the diagnosis of MDD or other Axis I psychiatric disorders. The Center for Epidemiological Studies for Depression Scale(CES-D) and the Totonto Alexithymia Scale(TAS) were administered to assess depressive symptom and alexithymia, respectively. Among subjects without MDD, those who had minor depressive disorder on the SCID or high scores(i.e. over 16) on the CES-D were defined as subjects with SCD. TAS total score and factor I, II, III scores of TAS in MDD, SCD, and non-depressive controls were compared. Results : Among 386 subjects, 38 subjects(9.8%) were diagnosed as MDD by DSM-IV criteria, while 57 subjects(14.8%) were classified into SCD group. There were significant differences between 3 groups(MDD, SCD and non-depressive controls) in total score($F_{2,383}=14.0$, p<0.01), factor I(difficulty in identifying feeling)($F_{2,383}=23.4$, p<0.01) and factor II(difficulty in describing feeling)($F_{2,383}=7.8$, p<0.01), but not factor III(external oriented thinking)($F_{2,383}=1.8$, p=0.16) of TAS. In post-hoc analysis, both MDD subjects and SCD subjects had higher scores in TAS total, factor I and factor II, compared to non-depressive controls(all p<0.01). In contrast, there were no significant differences between MDD subjects and SCD subjects in any TAS factor. Conclusion : In this study, both MDD subjects and SCD subjects were more alexithymic than non-depressive control subjects. These findings suggest that SCD, as well as MDD, is also related to alexithymia.