• Journal of the Korean Society of Food Science and Nutrition
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• v.41 no.8
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• pp.1118-1133
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• 2012

This research aimed to suggest an efficient improvement plan for school food services by investigating the operating situation and recognition of menu management in school food services for school food service dietitians (and nutrition teachers) in Chungbuk. A total of 328 questionnaires were distributed to school food service dietitians (and nutrition teachers) in Chungbuk by e-mail in September, 2010. A total of 265 questionnaires (80.8%) were used for the analysis. The highest allocation of nutrients and calories per day in school food services was 1:1.5:1.5 (breakfast : lunch : dinner) (38.5%). The reasoning for applying a flexible allocation of nutrients and calories per day was 'considering the ratio of students who do not eat breakfast' (59.2%). And the way to apply the flexible allocation for nutrients and calories per day was 'by agreement from the school operating committee in arbitrary data without situation surveys' (86 respondents, 49.4%), and 'by agreement from the school operating committee in analysis data through situation surveys' (80 respondents, 46.0%). The operational method of standardized recipes was 'cooking management site of national education information systems' (87.5%) and the items included in standardized recipes were menu name, food material name, portion size, cooking method, nutrition analysis, and critical control point in HACCP. The main reason for not utilizing all items of a cooking management site of the national education information system was 'no big trouble in menu management even though it is used partly (29.1%). In addition, the highest use of standardized recipe was for 'maintaining consistency of food production quantity' (74.0%).

• Journal of Intelligence and Information Systems
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• v.24 no.3
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• pp.1-19
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• 2018

Large amount of data is now available for research and business sectors to extract knowledge from it. This data can be in the form of unstructured data such as audio, text, and image data and can be analyzed by deep learning methodology. Deep learning is now widely used for various estimation, classification, and prediction problems. Especially, fashion business adopts deep learning techniques for apparel recognition, apparel search and retrieval engine, and automatic product recommendation. The core model of these applications is the image classification using Convolutional Neural Networks (CNN). CNN is made up of neurons which learn parameters such as weights while inputs come through and reach outputs. CNN has layer structure which is best suited for image classification as it is comprised of convolutional layer for generating feature maps, pooling layer for reducing the dimensionality of feature maps, and fully-connected layer for classifying the extracted features. However, most of the classification models have been trained using online product image, which is taken under controlled situation such as apparel image itself or professional model wearing apparel. This image may not be an effective way to train the classification model considering the situation when one might want to classify street fashion image or walking image, which is taken in uncontrolled situation and involves people's movement and unexpected pose. Therefore, we propose to train the model with runway apparel image dataset which captures mobility. This will allow the classification model to be trained with far more variable data and enhance the adaptation with diverse query image. To achieve both convergence and generalization of the model, we apply Transfer Learning on our training network. As Transfer Learning in CNN is composed of pre-training and fine-tuning stages, we divide the training step into two. First, we pre-train our architecture with large-scale dataset, ImageNet dataset, which consists of 1.2 million images with 1000 categories including animals, plants, activities, materials, instrumentations, scenes, and foods. We use GoogLeNet for our main architecture as it has achieved great accuracy with efficiency in ImageNet Large Scale Visual Recognition Challenge (ILSVRC). Second, we fine-tune the network with our own runway image dataset. For the runway image dataset, we could not find any previously and publicly made dataset, so we collect the dataset from Google Image Search attaining 2426 images of 32 major fashion brands including Anna Molinari, Balenciaga, Balmain, Brioni, Burberry, Celine, Chanel, Chloe, Christian Dior, Cividini, Dolce and Gabbana, Emilio Pucci, Ermenegildo, Fendi, Giuliana Teso, Gucci, Issey Miyake, Kenzo, Leonard, Louis Vuitton, Marc Jacobs, Marni, Max Mara, Missoni, Moschino, Ralph Lauren, Roberto Cavalli, Sonia Rykiel, Stella McCartney, Valentino, Versace, and Yve Saint Laurent. We perform 10-folded experiments to consider the random generation of training data, and our proposed model has achieved accuracy of 67.2% on final test. Our research suggests several advantages over previous related studies as to our best knowledge, there haven't been any previous studies which trained the network for apparel image classification based on runway image dataset. We suggest the idea of training model with image capturing all the possible postures, which is denoted as mobility, by using our own runway apparel image dataset. Moreover, by applying Transfer Learning and using checkpoint and parameters provided by Tensorflow Slim, we could save time spent on training the classification model as taking 6 minutes per experiment to train the classifier. This model can be used in many business applications where the query image can be runway image, product image, or street fashion image. To be specific, runway query image can be used for mobile application service during fashion week to facilitate brand search, street style query image can be classified during fashion editorial task to classify and label the brand or style, and website query image can be processed by e-commerce multi-complex service providing item information or recommending similar item.

• Journal of Intelligence and Information Systems
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• v.24 no.2
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• pp.125-148
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• 2018

Recently, as the demand for big data analysis increases, cases of analyzing unstructured data and using the results are also increasing. Among the various types of unstructured data, text is used as a means of communicating information in almost all fields. In addition, many analysts are interested in the amount of data is very large and relatively easy to collect compared to other unstructured and structured data. Among the various text analysis applications, document classification which classifies documents into predetermined categories, topic modeling which extracts major topics from a large number of documents, sentimental analysis or opinion mining that identifies emotions or opinions contained in texts, and Text Summarization which summarize the main contents from one document or several documents have been actively studied. Especially, the text summarization technique is actively applied in the business through the news summary service, the privacy policy summary service, ect. In addition, much research has been done in academia in accordance with the extraction approach which provides the main elements of the document selectively and the abstraction approach which extracts the elements of the document and composes new sentences by combining them. However, the technique of evaluating the quality of automatically summarized documents has not made much progress compared to the technique of automatic text summarization. Most of existing studies dealing with the quality evaluation of summarization were carried out manual summarization of document, using them as reference documents, and measuring the similarity between the automatic summary and reference document. Specifically, automatic summarization is performed through various techniques from full text, and comparison with reference document, which is an ideal summary document, is performed for measuring the quality of automatic summarization. Reference documents are provided in two major ways, the most common way is manual summarization, in which a person creates an ideal summary by hand. Since this method requires human intervention in the process of preparing the summary, it takes a lot of time and cost to write the summary, and there is a limitation that the evaluation result may be different depending on the subject of the summarizer. Therefore, in order to overcome these limitations, attempts have been made to measure the quality of summary documents without human intervention. On the other hand, as a representative attempt to overcome these limitations, a method has been recently devised to reduce the size of the full text and to measure the similarity of the reduced full text and the automatic summary. In this method, the more frequent term in the full text appears in the summary, the better the quality of the summary. However, since summarization essentially means minimizing a lot of content while minimizing content omissions, it is unreasonable to say that a "good summary" based on only frequency always means a "good summary" in its essential meaning. In order to overcome the limitations of this previous study of summarization evaluation, this study proposes an automatic quality evaluation for text summarization method based on the essential meaning of summarization. Specifically, the concept of succinctness is defined as an element indicating how few duplicated contents among the sentences of the summary, and completeness is defined as an element that indicating how few of the contents are not included in the summary. In this paper, we propose a method for automatic quality evaluation of text summarization based on the concepts of succinctness and completeness. In order to evaluate the practical applicability of the proposed methodology, 29,671 sentences were extracted from TripAdvisor 's hotel reviews, summarized the reviews by each hotel and presented the results of the experiments conducted on evaluation of the quality of summaries in accordance to the proposed methodology. It also provides a way to integrate the completeness and succinctness in the trade-off relationship into the F-Score, and propose a method to perform the optimal summarization by changing the threshold of the sentence similarity.

• Journal of Intelligence and Information Systems
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• v.27 no.2
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• pp.55-78
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• 2021

Tosolve complex and diverse social problems and ensure the quality of life of individuals, social robots that can interact with humans are attracting attention. In the past, robots were recognized as beings that provide labor force as they put into industrial sites on behalf of humans. However, the concept of today's robot has been extended to social robots that coexist with humans and enable social interaction with the advent of Smart technology, which is considered an important driver in most industries. Specifically, there are service robots that respond to customers, the robots that have the purpose of edutainment, and the emotionalrobots that can interact with humans intimately. However, popularization of robots is not felt despite the current information environment in the modern ICT service environment and the 4th industrial revolution. Considering social interaction with users which is an important function of social robots, not only the technology of the robots but also other factors should be considered. The design elements of the robot are more important than other factors tomake consumers purchase essentially a social robot. In fact, existing studies on social robots are at the level of proposing "robot development methodology" or testing the effects provided by social robots to users in pieces. On the other hand, consumer emotions felt from the robot's appearance has an important influence in the process of forming user's perception, reasoning, evaluation and expectation. Furthermore, it can affect attitude toward robots and good feeling and performance reasoning, etc. Therefore, this study aims to verify the effect of appearance of social robot and consumer emotions on consumer's attitude toward social robot. At this time, a social robot design evaluation model is constructed by combining heterogeneous data from different sources. Specifically, the three quantitative indicator data for the appearance of social robots from the ABOT Database is included in the model. The consumer emotions of social robot design has been collected through (1) the existing design evaluation literature and (2) online buzzsuch as product reviews and blogs, (3) qualitative interviews for social robot design. Later, we collected the score of consumer emotions and attitudes toward various social robots through a large-scale consumer survey. First, we have derived the six major dimensions of consumer emotions for 23 pieces of detailed emotions through dimension reduction methodology. Then, statistical analysis was performed to verify the effect of derived consumer emotionson attitude toward social robots. Finally, the moderated regression analysis was performed to verify the effect of quantitatively collected indicators of social robot appearance on the relationship between consumer emotions and attitudes toward social robots. Interestingly, several significant moderation effects were identified, these effects are visualized with two-way interaction effect to interpret them from multidisciplinary perspectives. This study has theoretical contributions from the perspective of empirically verifying all stages from technical properties to consumer's emotion and attitudes toward social robots by linking the data from heterogeneous sources. It has practical significance that the result helps to develop the design guidelines based on consumer emotions in the design stage of social robot development.

• Journal of Intelligence and Information Systems
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• v.27 no.4
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• pp.1-22
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• 2021

Aspect Based Sentiment Analysis (ABSA), which analyzes sentiment based on aspects that appear in the text, is drawing attention because it can be used in various business industries. ABSA is a study that analyzes sentiment by aspects for multiple aspects that a text has. It is being studied in various forms depending on the purpose, such as analyzing all targets or just aspects and sentiments. Here, the aspect refers to the property of a target, and the target refers to the text that causes the sentiment. For example, for restaurant reviews, you could set the aspect into food taste, food price, quality of service, mood of the restaurant, etc. Also, if there is a review that says, "The pasta was delicious, but the salad was not," the words "steak" and "salad," which are directly mentioned in the sentence, become the "target." So far, in ABSA, most studies have analyzed sentiment only based on aspects or targets. However, even with the same aspects or targets, sentiment analysis may be inaccurate. Instances would be when aspects or sentiment are divided or when sentiment exists without a target. For example, sentences like, "Pizza and the salad were good, but the steak was disappointing." Although the aspect of this sentence is limited to "food," conflicting sentiments coexist. In addition, in the case of sentences such as "Shrimp was delicious, but the price was extravagant," although the target here is "shrimp," there are opposite sentiments coexisting that are dependent on the aspect. Finally, in sentences like "The food arrived too late and is cold now." there is no target (NULL), but it transmits a negative sentiment toward the aspect "service." Like this, failure to consider both aspects and targets - when sentiment or aspect is divided or when sentiment exists without a target - creates a dual dependency problem. To address this problem, this research analyzes sentiment by considering both aspects and targets (Target-Aspect-Sentiment Detection, hereby TASD). This study detected the limitations of existing research in the field of TASD: local contexts are not fully captured, and the number of epochs and batch size dramatically lowers the F1-score. The current model excels in spotting overall context and relations between each word. However, it struggles with phrases in the local context and is relatively slow when learning. Therefore, this study tries to improve the model's performance. To achieve the objective of this research, we additionally used auxiliary loss in aspect-sentiment classification by constructing CNN(Convolutional Neural Network) layers parallel to existing models. If existing models have analyzed aspect-sentiment through BERT encoding, Pooler, and Linear layers, this research added CNN layer-adaptive average pooling to existing models, and learning was progressed by adding additional loss values for aspect-sentiment to existing loss. In other words, when learning, the auxiliary loss, computed through CNN layers, allowed the local context to be captured more fitted. After learning, the model is designed to do aspect-sentiment analysis through the existing method. To evaluate the performance of this model, two datasets, SemEval-2015 task 12 and SemEval-2016 task 5, were used and the f1-score increased compared to the existing models. When the batch was 8 and epoch was 5, the difference was largest between the F1-score of existing models and this study with 29 and 45, respectively. Even when batch and epoch were adjusted, the F1-scores were higher than the existing models. It can be said that even when the batch and epoch numbers were small, they can be learned effectively compared to the existing models. Therefore, it can be useful in situations where resources are limited. Through this study, aspect-based sentiments can be more accurately analyzed. Through various uses in business, such as development or establishing marketing strategies, both consumers and sellers will be able to make efficient decisions. In addition, it is believed that the model can be fully learned and utilized by small businesses, those that do not have much data, given that they use a pre-training model and recorded a relatively high F1-score even with limited resources.

• Korean Journal of Environment and Ecology
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• v.37 no.4
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• pp.302-314
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• 2023

This study aims to explore the direction for Korea's effective response to Target 3 (30by30), which can be said to be the core of the Kunming-Montreal Global Biodiversity Framework (K-M GBF) of the Convention on Biological Diversity (CBD), to find the direction of systematic OECM (Other Effective area-based Conservation Measures) discovery at the national level through a survey of global conceptual review and expert perception of OECM. This study examined ① the use of Korean terms related to OECM, ② derivation of determining criteria reflecting global standards, ③ deriving types of potential OECM candidates in Korea, and ④ considerations for OECM identification and reporting to explore the direction for identifying systematic, national-level OECM that complies with global standards and reflects the Korean context. First, there was consensus for using Korean terminology that reflects the concept of OECM rather than simple translations, and it was determined that "nature coexistence area" was the most preferred term (12 people) and had the same context as CBD 2050 Vision of "a world of living in harmony with nature." This study suggests utilizing four criteria (1. No protected areas, 2. Geographic boundaries, 3. Governance/management, and 4. Biodiversity value) that reflect OECM's core characteristics in the first-stage selection process, carrying out the consensus-building process (stage 2) with the relevant agencies, and adding two criteria (3-1 Effectiveness and sustainability of governance and management and 4-1 Long-term conservation) and performing the in-depth diagnosis in stage 3 (full assessment for reporting). The 28 types examined in this study were generally compatible with OECMs (4.45-6.21/7 points, mean 5.24). In particular, the "Conservation Properties (6.21 points)" and "Conservation Agreements (6.07 points)", which are controlled by National Nature Trust, are shown to be the most in line with the OECM concept. They were followed by "Buffer zone of World Natural Heritage (5.77 points)", "Temple Forest (5.73 points)", "Green-belt (Restricted development zones, 5.63 points)", "DMZ (5.60 points)", and "Buffer zone of biosphere reserve (5.50 point)" to have high potential. In the case of "Uninhabited Islands under Absolute Conservation", the response that they conformed to the protected areas (5.83/7 points) was higher than the OECM compatibility (5.52/7 points), it is determined that in the future, it would be preferable to promote the listing of absolute unprotected islands in the Korea Database on Protected Areas (KDPA) along with their surrounding waters (1 km). Based on the results of a global OECM standard review and expert perception survey, 10 items were suggested as considerations when identifying OECM in the Korean context. In the future, continuous research is needed to identify the potential OECMs through site-level assessment regarding these considerations and establish an effective in-situ conservation system at the national level by linking existing protected area systems and identified OECMs.

• The Korean Journal of Nuclear Medicine Technology
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• v.15 no.2
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• pp.3-12
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• 2011

Purpose: With increasing medical use of radiation and radioactive isotopes, there is a need to better manage the risk of radiation exposure. This study aims to grasp and analyze the individual radiation exposure situations of radiation-related workers in a medical facility by specific job, in order to instill awareness of radiation danger and to assist in safety and radiation exposure management for such workers. Materials and Methods: From January 1, 2010 December 31, 2010, medical practitioners working in the radiation is classified as a regular personal radiation dosimetry, and subsequently one year 540 people managed investigation department to target workers, dose sectional area, working period, identify the job function-related tasks for a deep dose, respectively, the annual average radiation dose were analyzed. Frequency analysis methods include ANOVA was performed. Results: Medical radiation workers in the department an annual radiation dose of Nuclear and 4.57 mSv a was highest, dose zone-specific distribution of nuclear medicine and in the 5.01~19.05 mSv in the high dose area distribution showed departmental radiation four of the annual radiation dose of Nuclear and 7.14 mSv showed the highest radiation dose. More work an average annual radiation dose according to the job function related to the synthesis of Cyclotron to 17.47 mSv work showed the highest radiation dose, Gamma camera Cinema Room 7.24 mSv, PET/CT Cinema Room service is 7.60 mSv, 2.04 mSv in order of intervention high, were analyzed. Working period, according to domain-specific average annual dose of radiation dose from 10 to 14 in oral and maxillofacial radiology practitioners as high as 1.01~3.00 mSv average dose showed the Department of Radiology, 1-4 years, 5-9 years, respectively, 1.01 workers~8.00 mSv in the range of the most high-dose region showed the distribution, nuclear medicine, and the 1-4 years, 5-9 years 3.01~19.05 mSv, respectively, workers of the highest dose showed the distribution of the area in the range of 10 to 14 years, Workers at 15-19 3.01~15.00 mSv, respectively in the range of the high-dose region were distributed. Conclusion: These results suggest that medical radiation workers working in Nuclear Medicine radiation safety management of the majority of the current were carried out in the effectiveness, depending on job characteristics has been found that many differences. However, this requires efforts to minimize radiation exposure, and systematic training for them and for reasonable radiation exposure management system is needed.

• Journal of Intelligence and Information Systems
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• v.18 no.3
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• pp.153-169
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• 2012

Exhibitions have played a key role of effective marketing activity which directly informs services and products to current and potential customers. Through participating in exhibitions, exhibitors have got the opportunity to make face-to-face contact so that they can secure the market share and improve their corporate images. According to this economic importance of exhibitions, show organizers try to adopt a new IT technology for improving their performance, and researchers have also studied services which can improve the satisfaction of visitors through analyzing visit patterns of visitors. Especially, as smart technologies make them monitor activities of visitors in real-time, they have considered booth recommender systems which infer preference of visitors and recommender proper service to them like on-line environment. However, while there are many studies which can improve their performance in the side of new technological development, they have not considered the choice factor of visitors for booth recommender systems. That is, studies for factors which can influence the development direction and effective diffusion of these systems are insufficient. Most of prior studies for the acceptance of new technologies and the continuous intention of use have adopted Technology Acceptance Model (TAM) and Extended Technology Acceptance Model (ETAM). Booth recommender systems may not be new technology because they are similar with commercial recommender systems such as book recommender systems, in the smart exhibition environment, they can be considered new technology. However, for considering the smart exhibition environment beyond TAM, measurements for the intention of reuse should focus on how booth recommender systems can provide correct information to visitors. In this study, through literature reviews, we draw factors which can influence the satisfaction and reuse intention of visitors for booth recommender systems, and design a model to forecast adaptation of visitors for booth recommendation in the exhibition environment. For these purposes, we conduct a survey for visitors who attended DMC Culture Open in November 2011 and experienced booth recommender systems using own smart phone, and examine hypothesis by regression analysis. As a result, factors which can influence the satisfaction of visitors for booth recommender systems are the effectiveness, perceived ease of use, argument quality, serendipity, and so on. Moreover, the satisfaction for booth recommender systems has a positive relationship with the development of reuse intention. For these results, we have some insights for booth recommender systems in the smart exhibition environment. First, this study gives shape to important factors which are considered when they establish strategies which induce visitors to consistently use booth recommender systems. Recently, although show organizers try to improve their performances using new IT technologies, their visitors have not felt the satisfaction from these efforts. At this point, this study can help them to provide services which can improve the satisfaction of visitors and make them last relationship with visitors. On the other hands, this study suggests that they managers along the using time of booth recommender systems. For example, in the early stage of the adoption, they should focus on the argument quality, perceived ease of use, and serendipity, so that improve the acceptance of booth recommender systems. After these stages, they should bridge the differences between expectation and perception for booth recommender systems, and lead continuous uses of visitors. However, this study has some limitations. We only use four factors which can influence the satisfaction of visitors. Therefore, we should development our model to consider important additional factors. And the exhibition in our experiments has small number of booths so that visitors may not need to booth recommender systems. In the future study, we will conduct experiments in the exhibition environment which has a larger scale.

• Journal of Yeungnam Medical Science
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• v.12 no.2
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• pp.347-365
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• 1995

A survey was conducted to study perception and attitudes of health workers towards health center's activities and organization of health services, from August 15 to September 30, 1994. The study population was 310 health workers engaged in seven urban health centers in Taegu City area. A questionnaire method was used to collect data and response rate was 81.3 percent or 252 respondents. The following are summaries of findings: Profiles of study population: Health workers were predominantly female(62.3%); had college education(60.3%); and held medical and nursing positions(39.6%), technicians(30.6%) and public health/administrative positions(29.8%). Perceptions on health center's resources: Slightly more than a half(51.1%) of respondents expressed that physical facilities of the centers are inadequate; equipments needed are short(39.0%); human resource is inadequate(44.8%); and health budget allocated is insufficient(38.5%) to support the performance of health center's activities. Decentralization and health services: The majority revealed that the decentralization of government system would affect the future activities of health centers(51.9%) which may have to change. However, only one quarter of respondents(25.4%) seemed to view the decentralization positively as they expect that it would help perform health activities more effectively. The majority of the respondents(78.6%) insisted that the function and organization of the urban health centers should be changed. Target workload and job satisfaction: A large proportion (43.3%) of respondents felt that present target setting systems for various health activities are unrealistic in terms of community needs and health center's situation while only 11.1 percent responded it positively; the majority(57.5%) revealed that they need further training in professional fields to perform their job more effectively; more than one third(35.7%) expressed that they enjoy their professional autonomy in their job performance; and a considerable proportion (39.3%) said they are satisfied with their present work. Regarding the personnel management, more worker(47.3%) perceived it negatively than positive(11.5%) as most of workers seemed to think the personnel management practiced at the health centers is not fair or justly done. Health services rendered: Among health services rendered, health workers perceived the following services are most successfully delivered; they are, in order of importance, Tb control, curative services, and maternal and child health care. Such areas as health education, oral health, environmental sanitation, and integrated health services are needed to be strengthening. Regarding the community attitudes towards health workers, 41.3 percent of respondents think they are trusted by the community they serve. New areas of concern identified which must be included in future activities of health centers are, in order of priority, health care of elderly population, home health care, rehabilitation services, and such chronic diseases control programs as diabetes, hypertension, school health and mental health care. In conclusion, the study revealed that health workers seemed to have more negative perceptions and attitudes than positive ones towards organization and management of health services and activities performed by the urban health centers where they are engaged. More specifically, the majority of health workers studied revealed to have the following areas of health center's organization and management inadequate or insufficient to support effective performance of their health activities: Namely, physical facilities and equipments required are inadequate; human and financial resources are insufficient; personnel management is unsatisfactory; setting of service target system is unrealistic in terms of the community needs. However, respondents displayed a number of positive perceptions, particularly to those areas as further training needs and implementation of decentralization of government system which will bring more autonomy of local government as they perceived these change would bring the necessary changes to future activities of the health center. They also displayed positive perceptions in their job autonomy and have job satisfactions.

• Journal of Intelligence and Information Systems
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• v.24 no.4
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• pp.171-196
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• 2018

With the development of the web, two-way communication and evaluation became possible and marketing paradigms shifted. In order to meet the needs of consumers, web design trends are continuously responding to consumer feedback. As the web becomes more and more important, both academics and businesses are studying consumer emotions and satisfaction on the web. However, some consumer characteristics are not well considered. Demographic characteristics such as age and sex have been studied extensively, but few studies consider psychological characteristics such as regulatory focus (i.e., emotional regulation). In this study, we analyze the effect of web style on consumer emotion. Many studies analyze the relationship between the web and regulatory focus, but most concentrate on the purpose of web use, particularly motivation and information search, rather than on web style and design. The web communicates with users through visual elements. Because the human brain is influenced by all five senses, both design factors and emotional responses are important in the web environment. Therefore, in this study, we examine the relationship between consumer emotion and satisfaction and web style and design. Previous studies have considered the effects of web layout, structure, and color on emotions. In this study, however, we excluded these web components, in contrast to earlier studies, and analyzed the relationship between consumer satisfaction and emotional indexes of web-style only. To perform this analysis, we collected consumer surveys presenting 40 web style themes to 204 consumers. Each consumer evaluated four themes. The emotional adjectives evaluated by consumers were composed of 18 contrast pairs, and the upper emotional indexes were extracted through factor analysis. The emotional indexes were 'softness,' 'modernity,' 'clearness,' and 'jam.' Hypotheses were established based on the assumption that emotional indexes have different effects on consumer satisfaction. After the analysis, hypotheses 1, 2, and 3 were accepted and hypothesis 4 was rejected. While hypothesis 4 was rejected, its effect on consumer satisfaction was negative, not positive. This means that emotional indexes such as 'softness,' 'modernity,' and 'clearness' have a positive effect on consumer satisfaction. In other words, consumers prefer emotions that are soft, emotional, natural, rounded, dynamic, modern, elaborate, unique, bright, pure, and clear. 'Jam' has a negative effect on consumer satisfaction. It means, consumer prefer the emotion which is empty, plain, and simple. Regulatory focus shows differences in motivation and propensity in various domains. It is important to consider organizational behavior and decision making according to the regulatory focus tendency, and it affects not only political, cultural, ethical judgments and behavior but also broad psychological problems. Regulatory focus also differs from emotional response. Promotion focus responds more strongly to positive emotional responses. On the other hand, prevention focus has a strong response to negative emotions. Web style is a type of service, and consumer satisfaction is affected not only by cognitive evaluation but also by emotion. This emotional response depends on whether the consumer will benefit or harm himself. Therefore, it is necessary to confirm the difference of the consumer's emotional response according to the regulatory focus which is one of the characteristics and viewpoint of the consumers about the web style. After MMR analysis result, hypothesis 5.3 was accepted, and hypothesis 5.4 was rejected. But hypothesis 5.4 supported in the opposite direction to the hypothesis. After validation, we confirmed the mechanism of emotional response according to the tendency of regulatory focus. Using the results, we developed the structure of web-style recommendation system and recommend methods through regulatory focus. We classified the regulatory focus group in to three categories that promotion, grey, prevention. Then, we suggest web-style recommend method along the group. If we further develop this study, we expect that the existing regulatory focus theory can be extended not only to the motivational part but also to the emotional behavioral response according to the regulatory focus tendency. Moreover, we believe that it is possible to recommend web-style according to regulatory focus and emotional desire which consumers most prefer.