• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.15 no.1
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• pp.95-112
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• 2020

This paper is to investigate how cognitive bias of college students and entrepreneurs relates to perceived risks and entrepreneurial opportunities that represent uncertainty, and how various cognitive bias and entrepreneurial efficacy In the same way. The purpose of this study is to find improvement points of entrepreneurship education for college students and to suggest problems and improvement possibilities in the decision making process of current entrepreneurs. This empirical study is a necessary to improve the decision-making of individuals who want to start a business at the time when various attempts are made to activate the start-up business and increase the sustainability of the existing SME management. And understanding of the difference in opportunity evaluation, and suggests that it is necessary to provide good opportunities together with the upbringing of entrepreneurs. In order to achieve the purpose of the study, questionnaires were conducted for college students and entrepreneurs. A total of 363 questionnaire data were obtained and demonstrated through structural equation modeling. This study confirms that there is some relationship between perceived risk and cognitive bias. Overconfidence and control illusions among cognitive bias have a significant relationship between perceived risk and wealth. Especially, it is confirmed that control illusion of college students has a significant relationship with perceived risk. Second, cognitive bias demonstrated some significant relationship with opportunity evaluation. Although we did not find evidence that excess self-confidence is related to opportunity evaluation, we have verified that control illusions and current status bias are related to opportunity evaluation. Control illusions were significant in both college students and entrepreneurs. Third, perceived risk has a negative relationship with opportunity evaluation. All students, regardless of whether they are college students or entrepreneurs, judge opportunities positively if they perceive low risk. Fourth, it can be seen from the college students 'group that entrepreneurial efficacy has a moderating effect between perceived risk and opportunity evaluation, but no significant results were found in the entrepreneurs' group. Fifth, the college students and entrepreneurs have different cognitive bias, and they have proved that there is a different relationship between entrepreneurial opportunity evaluation and perceived risk. On the whole, there are various cognitive biases that are caused by time pressure or stress on college students and entrepreneurs who have to make judgments in uncertain opportunities, and in this respect, they can improve their judgment in the future. At the same time, university students can have a positive view of new opportunities based on high entrepreneurial efficacy, but if they fully understand the intrinsic risks of entrepreneurship through entrepreneurial education and fully understand the cognitive bias present in direct entrepreneurial experience, You will get a better opportunity assessment. This study has limitations in that it is based on the fact that university students and entrepreneurs are integrated, and that the survey respondents are selected by the limited random sampling method. It is necessary to conduct more systematic research based on more faithful data in the absence of the accumulation of entrepreneurial research data. Second, the translation tools used in the previous studies were translated and the meaning of the measurement tools might not be conveyed due to language differences. Therefore, it is necessary to construct a more precise scale for the accuracy of the study. Finally, complementary research should be done to identify what competitive opportunities are and what opportunities are appropriate for entrepreneurs.

• KOREAN JOURNAL OF PACKAGING SCIENCE & TECHNOLOGY
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• v.20 no.3
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• pp.113-120
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• 2014

Packaging has played important function on marketing as a silent salesman. As an interface of consumer and products, packaging fulfills several functions such as protection, sales promotion, communication and convenience during the distribution process. For the appearance of self-service sales method, packaging could be regarded as important salesman influencing consumers' preference on shelf in the shop. In this study, Vitamin water was selected as the proper target product for lower impact of prices and brands. With previous studies, Vitamin water packaging elements were classified as 'packaging material', 'packaging shape', 'label color', 'logo layout', then each packaging element was consist of details. To measure the influence of each packaging element on consumers' preference quantitatively and to minimize respondent's subjective judgment, Analytic Hierarchy Process (AHP) was used as a tool. Through AHP result, packaging element of the most influence on consumers' preference is 'label color (0.370)', and 'container shape (0.246)', 'container material (0.230)', 'logo layout (0.154)' was in order. Among the detail packaging element, 'plastic (0.405)' has the greatest influence in 'container material' and 'cylinder (0.423)' in 'container shape', 'magenta (0.329)' in 'label color', 'vertical layout (0.572)' in 'logo layout'.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.10 no.6
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• pp.74-83
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• 2011

The high-pass transportation information system directly collects section information by using probe cars and therefore can offer more reliable information to drivers. However, because the running condition and features of probe cars and statistical processing methods affect the reliability of the information and particularly because the section travel time is greatly influenced by whether there has been delay by signals on urban roads or not, there can be much deviation among the collected individual probe data. Accordingly, researches in multilateral directions are necessary in order to enhance the credibility of the section information. Yet, the precedent studies related to high-pass information provision have been conducted on the highway sections with the feature of continuous flow, which has a limit to be applied to the urban roads with the transportational feature of an interrupted flow. Therefore, this research aims at analyzing the features of high-pass transportation data on urban roads and finding a proper processing method. When the characteristics of the high-pass data on urban roads collected from RSE were analyzed by using a time-space diagram, the collected data was proved to have a certain pattern according to the arriving cars' waiting for signals with the period of the signaling cycle of the finish node. Moreover, the number of waiting for signals and the time of waiting caused the deviation in the collected data, and it was bigger in traffic jam. The analysis result showed that it was because the increased number of waiting for signals in traffic jam caused the deviation to be offset partially. The analysis result shows that it is appropriate to use the mean of this collected data of high-pass on urban roads as its representative value to reflect the transportational features by waiting for signals, and the standard of judgment of delay and congestion needs to be changed depending on the features of signals and roads. The results of this research are expected to be the foundation stone to improve the reliability of high-pass information on urban roads.

• Journal of Intelligence and Information Systems
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• v.18 no.1
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• pp.125-141
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• 2012

These days, the malicious attacks and hacks on the networked systems are dramatically increasing, and the patterns of them are changing rapidly. Consequently, it becomes more important to appropriately handle these malicious attacks and hacks, and there exist sufficient interests and demand in effective network security systems just like intrusion detection systems. Intrusion detection systems are the network security systems for detecting, identifying and responding to unauthorized or abnormal activities appropriately. Conventional intrusion detection systems have generally been designed using the experts' implicit knowledge on the network intrusions or the hackers' abnormal behaviors. However, they cannot handle new or unknown patterns of the network attacks, although they perform very well under the normal situation. As a result, recent studies on intrusion detection systems use artificial intelligence techniques, which can proactively respond to the unknown threats. For a long time, researchers have adopted and tested various kinds of artificial intelligence techniques such as artificial neural networks, decision trees, and support vector machines to detect intrusions on the network. However, most of them have just applied these techniques singularly, even though combining the techniques may lead to better detection. With this reason, we propose a new integrated model for intrusion detection. Our model is designed to combine prediction results of four different binary classification models-logistic regression (LOGIT), decision trees (DT), artificial neural networks (ANN), and support vector machines (SVM), which may be complementary to each other. As a tool for finding optimal combining weights, genetic algorithms (GA) are used. Our proposed model is designed to be built in two steps. At the first step, the optimal integration model whose prediction error (i.e. erroneous classification rate) is the least is generated. After that, in the second step, it explores the optimal classification threshold for determining intrusions, which minimizes the total misclassification cost. To calculate the total misclassification cost of intrusion detection system, we need to understand its asymmetric error cost scheme. Generally, there are two common forms of errors in intrusion detection. The first error type is the False-Positive Error (FPE). In the case of FPE, the wrong judgment on it may result in the unnecessary fixation. The second error type is the False-Negative Error (FNE) that mainly misjudges the malware of the program as normal. Compared to FPE, FNE is more fatal. Thus, total misclassification cost is more affected by FNE rather than FPE. To validate the practical applicability of our model, we applied it to the real-world dataset for network intrusion detection. The experimental dataset was collected from the IDS sensor of an official institution in Korea from January to June 2010. We collected 15,000 log data in total, and selected 10,000 samples from them by using random sampling method. Also, we compared the results from our model with the results from single techniques to confirm the superiority of the proposed model. LOGIT and DT was experimented using PASW Statistics v18.0, and ANN was experimented using Neuroshell R4.0. For SVM, LIBSVM v2.90-a freeware for training SVM classifier-was used. Empirical results showed that our proposed model based on GA outperformed all the other comparative models in detecting network intrusions from the accuracy perspective. They also showed that the proposed model outperformed all the other comparative models in the total misclassification cost perspective. Consequently, it is expected that our study may contribute to build cost-effective intelligent intrusion detection systems.

• The Journal of Korean Philosophical History
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• no.43
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• pp.107-139
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• 2014

Tasan Chong Yak-yong has criticized Zhu Xi's metaphysical viewpoints of human being. Therefore he revealed his viewpoint of human being and the theory of moral practice through his thoughts about the Lord of Heaven and human nature with spiritual inclination toward goodness. He has drawn the Lord of Heaven into Confucianism again. Heaven as the Lord endows human being with a nature that enjoys virtues and detests vices. It watches human being's good and evil. Here we can say Heaven is a outer efficient cause of moral behavior. According to Tasan, human being has its own 'self directed weight'自主之權 so that he can make a judgment and decision about what to do. Therefore we have to do manifest this moral inclination which is a inner efficient cause of moral behavior. That is to say, we must follow the order of daoxin道心 inside our mind. If we did go against it, our mind would be uncomfortable. Now through the method of so-called shu恕 we need to put filial piety孝 fraternal respect弟 compassion慈 into practice. These three moral practices represent the spirit of reciprocity in Confucianism. These lead us to make an achievement of ren仁, representative virtue in the theory of moral practice. Our moral practice means the fulfillment of humanity. This is the way to serve Heaven. Tasan insists that theses are the core thoughts of Confucius and Mencius.

• Journal of Intelligence and Information Systems
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• v.23 no.1
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• pp.47-67
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• 2017

Steel plate faults is one of important factors to affect the quality and price of the steel plates. So far many steelmakers generally have used visual inspection method that could be based on an inspector's intuition or experience. Specifically, the inspector checks the steel plate faults by looking the surface of the steel plates. However, the accuracy of this method is critically low that it can cause errors above 30% in judgment. Therefore, accurate steel plate faults diagnosis system has been continuously required in the industry. In order to meet the needs, this study proposed a new steel plate faults diagnosis system using Simultaneous MTS (S-MTS), which is an advanced Mahalanobis Taguchi System (MTS) algorithm, to classify various surface defects of the steel plates. MTS has generally been used to solve binary classification problems in various fields, but MTS was not used for multiclass classification due to its low accuracy. The reason is that only one mahalanobis space is established in the MTS. In contrast, S-MTS is suitable for multi-class classification. That is, S-MTS establishes individual mahalanobis space for each class. 'Simultaneous' implies comparing mahalanobis distances at the same time. The proposed steel plate faults diagnosis system was developed in four main stages. In the first stage, after various reference groups and related variables are defined, data of the steel plate faults is collected and used to establish the individual mahalanobis space per the reference groups and construct the full measurement scale. In the second stage, the mahalanobis distances of test groups is calculated based on the established mahalanobis spaces of the reference groups. Then, appropriateness of the spaces is verified by examining the separability of the mahalanobis diatances. In the third stage, orthogonal arrays and Signal-to-Noise (SN) ratio of dynamic type are applied for variable optimization. Also, Overall SN ratio gain is derived from the SN ratio and SN ratio gain. If the derived overall SN ratio gain is negative, it means that the variable should be removed. However, the variable with the positive gain may be considered as worth keeping. Finally, in the fourth stage, the measurement scale that is composed of selected useful variables is reconstructed. Next, an experimental test should be implemented to verify the ability of multi-class classification and thus the accuracy of the classification is acquired. If the accuracy is acceptable, this diagnosis system can be used for future applications. Also, this study compared the accuracy of the proposed steel plate faults diagnosis system with that of other popular classification algorithms including Decision Tree, Multi Perception Neural Network (MLPNN), Logistic Regression (LR), Support Vector Machine (SVM), Tree Bagger Random Forest, Grid Search (GS), Genetic Algorithm (GA) and Particle Swarm Optimization (PSO). The steel plates faults dataset used in the study is taken from the University of California at Irvine (UCI) machine learning repository. As a result, the proposed steel plate faults diagnosis system based on S-MTS shows 90.79% of classification accuracy. The accuracy of the proposed diagnosis system is 6-27% higher than MLPNN, LR, GS, GA and PSO. Based on the fact that the accuracy of commercial systems is only about 75-80%, it means that the proposed system has enough classification performance to be applied in the industry. In addition, the proposed system can reduce the number of measurement sensors that are installed in the fields because of variable optimization process. These results show that the proposed system not only can have a good ability on the steel plate faults diagnosis but also reduce operation and maintenance cost. For our future work, it will be applied in the fields to validate actual effectiveness of the proposed system and plan to improve the accuracy based on the results.

• Journal of Global Scholars of Marketing Science
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• v.18 no.4
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• pp.61-118
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• 2008

The purpose of this research is to construct research framework for international franchising based on existing literature and to identify research components in the framework. Franchise can be defined as management styles that allow franchisee use various management assets of franchisor in order to make or sell product or service. It can be divided into product distribution franchise that is designed to sell products and business format franchise that is designed for running it as business whatever its form is. International franchising can be defined as a way of internationalization of franchisor to foreign country by providing its business format or package to franchisee of host country. International franchising is growing fast for last four decades but academic research on this is quite limited. Especially in Korea, research about international franchising is carried out on by case study format with single case or empirical study format with survey based on domestic franchise theory. Therefore, this paper tries to review existing literature on international franchising research, providing research framework, and then stimulating new research on this field. International franchising research components include motives and environmental factors for decision of expanding to international franchising, entrance modes and development plan for international franchising, contracts and management strategy of international franchising, and various performance measures from different perspectives. First, motives of international franchising are fee collection from franchisee. Also it provides easier way to expanding to foreign country. The other motives including increase total sales volume, occupying better strategic position, getting quality resources, and improving efficiency. Environmental factors that facilitating international franchising encompasses economic condition, trend, and legal or political factors in host and/or home countries. In addition, control power and risk management capability of franchisor plays critical role in successful franchising contract. Final decision to enter foreign country via franchising is determined by numerous factors like history, size, growth, competitiveness, management system, bonding capability, industry characteristics of franchisor. After deciding to enter into foreign country, franchisor needs to set entrance modes of international franchising. Within contractual mode, there are master franchising and area developing franchising, licensing, direct franchising, and joint venture. Theories about entrance mode selection contain concepts of efficiency, knowledge-based approach, competence-based approach, agent theory, and governance cost. The next step after entrance decision is operation strategy. Operation strategy starts with selecting a target city and a target country for franchising. In order to finding, screening targets, franchisor needs to collect information about candidates. Critical information includes brand patent, commercial laws, regulations, market conditions, country risk, and industry analysis. After selecting a target city in target country, franchisor needs to select franchisee, in other word, partner. The first important criteria for selecting partners are financial credibility and capability, possession of real estate. And cultural similarity and knowledge about franchisor and/or home country are also recognized as critical criteria. The most important element in operating strategy is legal document between franchisor and franchisee with home and host countries. Terms and conditions in legal documents give objective information about characteristics of franchising agreement for academic research. Legal documents have definitions of terminology, territory and exclusivity, agreement of term, initial fee, continuing fees, clearing currency, and rights about sub-franchising. Also, legal documents could have terms about softer elements like training program and operation manual. And harder elements like law competent court and terms of expiration. Next element in operating strategy is about product and service. Especially for business format franchising, product/service deliverable, benefit communicators, system identifiers (architectural features), and format facilitators are listed for product/service strategic elements. Another important decision on product/service is standardization vs. customization. The rationale behind standardization is cost reduction, efficiency, consistency, image congruence, brand awareness, and competitiveness on price. Also standardization enables large scale R&D and innovative change in management style. Another element in operating strategy is control management. The simple way to control franchise contract is relying on legal terms, contractual control system. There are other control systems, administrative control system and ethical control system. Contractual control system is a coercive source of power, but franchisor usually doesn't want to use legal power since it doesn't help to build up positive relationship. Instead, self-regulation is widely used. Administrative control system uses control mechanism from ordinary work relationship. Its main component is supporting activities to franchisee and communication method. For example, franchisor provides advertising, training, manual, and delivery, then franchisee follows franchisor's direction. Another component is building franchisor's brand power. The last research element is performance factor of international franchising. Performance elements can be divided into franchisor's performance and franchisee's performance. The conceptual performance measures of franchisor are simple but not easy to obtain objectively. They are profit, sale, cost, experience, and brand power. The performance measures of franchisee are mostly about benefits of host country. They contain small business development, promotion of employment, introduction of new business model, and level up technology status. There are indirect benefits, like increase of tax, refinement of corporate citizenship, regional economic clustering, and improvement of international balance. In addition to those, host country gets socio-cultural change other than economic effects. It includes demographic change, social trend, customer value change, social communication, and social globalization. Sometimes it is called as westernization or McDonaldization of society. In addition, the paper reviews on theories that have been frequently applied to international franchising research, such as agent theory, resource-based view, transaction cost theory, organizational learning theory, and international expansion theories. Resource based theory is used in strategic decision based on resources, like decision about entrance and cooperation depending on resources of franchisee and franchisor. Transaction cost theory can be applied in determination of mutual trust or satisfaction of franchising players. Agent theory tries to explain strategic decision for reducing problem caused by utilizing agent, for example research on control system in franchising agreements. Organizational Learning theory is relatively new in franchising research. It assumes organization tries to maximize performance and learning of organization. In addition, Internalization theory advocates strategic decision of direct investment for removing inefficiency of market transaction and is applied in research on terms of contract. And oligopolistic competition theory is used to explain various entry modes for international expansion. Competency theory support strategic decision of utilizing key competitive advantage. Furthermore, research methodologies including qualitative and quantitative methodologies are suggested for more rigorous international franchising research. Quantitative research needs more real data other than survey data which is usually respondent's judgment. In order to verify theory more rigorously, research based on real data is essential. However, real quantitative data is quite hard to get. The qualitative research other than single case study is also highly recommended. Since international franchising has limited number of applications, scientific research based on grounded theory and ethnography study can be used. Scientific case study is differentiated with single case study on its data collection method and analysis method. The key concept is triangulation in measurement, logical coding and comparison. Finally, it provides overall research direction for international franchising after summarizing research trend in Korea. International franchising research in Korea has two different types, one is for studying Korean franchisor going overseas and the other is for Korean franchisee of foreign franchisor. Among research on Korean franchisor, two common patterns are observed. First of all, they usually deal with success story of one franchisor. The other common pattern is that they focus on same industry and country. Therefore, international franchise research needs to extend their focus to broader subjects with scientific research methodology as well as development of new theory.

• Journal of Intelligence and Information Systems
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• v.24 no.1
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• pp.183-203
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• 2018

News articles are the most suitable medium for examining the events occurring at home and abroad. Especially, as the development of information and communication technology has brought various kinds of online news media, the news about the events occurring in society has increased greatly. So automatically summarizing key events from massive amounts of news data will help users to look at many of the events at a glance. In addition, if we build and provide an event network based on the relevance of events, it will be able to greatly help the reader in understanding the current events. In this study, we propose a method for extracting event networks from large news text data. To this end, we first collected Korean political and social articles from March 2016 to March 2017, and integrated the synonyms by leaving only meaningful words through preprocessing using NPMI and Word2Vec. Latent Dirichlet allocation (LDA) topic modeling was used to calculate the subject distribution by date and to find the peak of the subject distribution and to detect the event. A total of 32 topics were extracted from the topic modeling, and the point of occurrence of the event was deduced by looking at the point at which each subject distribution surged. As a result, a total of 85 events were detected, but the final 16 events were filtered and presented using the Gaussian smoothing technique. We also calculated the relevance score between events detected to construct the event network. Using the cosine coefficient between the co-occurred events, we calculated the relevance between the events and connected the events to construct the event network. Finally, we set up the event network by setting each event to each vertex and the relevance score between events to the vertices connecting the vertices. The event network constructed in our methods helped us to sort out major events in the political and social fields in Korea that occurred in the last one year in chronological order and at the same time identify which events are related to certain events. Our approach differs from existing event detection methods in that LDA topic modeling makes it possible to easily analyze large amounts of data and to identify the relevance of events that were difficult to detect in existing event detection. We applied various text mining techniques and Word2vec technique in the text preprocessing to improve the accuracy of the extraction of proper nouns and synthetic nouns, which have been difficult in analyzing existing Korean texts, can be found. In this study, the detection and network configuration techniques of the event have the following advantages in practical application. First, LDA topic modeling, which is unsupervised learning, can easily analyze subject and topic words and distribution from huge amount of data. Also, by using the date information of the collected news articles, it is possible to express the distribution by topic in a time series. Second, we can find out the connection of events in the form of present and summarized form by calculating relevance score and constructing event network by using simultaneous occurrence of topics that are difficult to grasp in existing event detection. It can be seen from the fact that the inter-event relevance-based event network proposed in this study was actually constructed in order of occurrence time. It is also possible to identify what happened as a starting point for a series of events through the event network. The limitation of this study is that the characteristics of LDA topic modeling have different results according to the initial parameters and the number of subjects, and the subject and event name of the analysis result should be given by the subjective judgment of the researcher. Also, since each topic is assumed to be exclusive and independent, it does not take into account the relevance between themes. Subsequent studies need to calculate the relevance between events that are not covered in this study or those that belong to the same subject.

• Journal of Intelligence and Information Systems
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• v.19 no.1
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• pp.79-94
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• 2013

Recently, the high value added business is steadily growing in the culture and art area. To generated high value from a performance, the satisfaction of audience is necessary. The flow in a critical factor for satisfaction, and it should be induced from audience and measures. To evaluate interest and emotion of audience on contents, producers or investors need a kind of index for the measurement of the flow. But it is neither easy to define the flow quantitatively, nor to collect audience's reaction immediately. The previous studies of the group flow were evaluated by the sum of the average value of each person's reaction. The flow or "good feeling" from each audience was extracted from his face, especially, the change of his (or her) expression and body movement. But it was not easy to handle the large amount of real-time data from each sensor signals. And also it was difficult to set experimental devices, in terms of economic and environmental problems. Because, all participants should have their own personal sensor to check their physical signal. Also each camera should be located in front of their head to catch their looks. Therefore we need more simple system to analyze group flow. This study provides the method for measurement of audiences flow with group synchronization at same time and place. To measure the synchronization, we made real-time processing system using the Differential Image and Group Emotion Analysis (GEA) system. Differential Image was obtained from camera and by the previous frame was subtracted from present frame. So the movement variation on audience's reaction was obtained. And then we developed a program, GEX(Group Emotion Analysis), for flow judgment model. After the measurement of the audience's reaction, the synchronization is divided as Dynamic State Synchronization and Static State Synchronization. The Dynamic State Synchronization accompanies audience's active reaction, while the Static State Synchronization means to movement of audience. The Dynamic State Synchronization can be caused by the audience's surprise action such as scary, creepy or reversal scene. And the Static State Synchronization was triggered by impressed or sad scene. Therefore we showed them several short movies containing various scenes mentioned previously. And these kind of scenes made them sad, clap, and creepy, etc. To check the movement of audience, we defined the critical point, ${\alpha}$and ${\beta}$. Dynamic State Synchronization was meaningful when the movement value was over critical point ${\beta}$, while Static State Synchronization was effective under critical point ${\alpha}$. ${\beta}$ is made by audience' clapping movement of 10 teams in stead of using average number of movement. After checking the reactive movement of audience, the percentage(%) ratio was calculated from the division of "people having reaction" by "total people". Total 37 teams were made in "2012 Seoul DMC Culture Open" and they involved the experiments. First, they followed induction to clap by staff. Second, basic scene for neutralize emotion of audience. Third, flow scene was displayed to audience. Forth, the reversal scene was introduced. And then 24 teams of them were provided with amuse and creepy scenes. And the other 10 teams were exposed with the sad scene. There were clapping and laughing action of audience on the amuse scene with shaking their head or hid with closing eyes. And also the sad or touching scene made them silent. If the results were over about 80%, the group could be judged as the synchronization and the flow were achieved. As a result, the audience showed similar reactions about similar stimulation at same time and place. Once we get an additional normalization and experiment, we can obtain find the flow factor through the synchronization on a much bigger group and this should be useful for planning contents.

• Journal of Intelligence and Information Systems
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• v.25 no.1
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• pp.179-196
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• 2019

Recently, the "Smart Consumer" has been emerging. He or she is increasingly inclined to search for and purchase products by taking into account personal judgment or expert reviews rather than by relying on information delivered through manufacturers' advertising. This is especially true when purchasing cosmetics. Because cosmetics act directly on the skin, consumers respond seriously to dangerous chemical elements they contain or to skin problems they may cause. Above all, cosmetics should fit well with the purchaser's skin type. In addition, changes in global cosmetics consumer trends make it necessary to study this field. The desire to find one's own individualized cosmetics is being revealed to consumers around the world and is known as "Finding the Holy Grail." Many consumers show a deep interest in customized cosmetics with the cultural boom known as "K-Beauty" (an aspect of "Han-Ryu"), the growth of personal grooming, and the emergence of "self-culture" that includes "self-beauty" and "self-interior." These trends have led to the explosive popularity of cosmetics made in Korea in the Chinese and Southeast Asian markets. In order to meet the customized cosmetics needs of consumers, cosmetics manufacturers and related companies are responding by concentrating on delivering premium services through the convergence of ICT(Information, Communication and Technology). Despite the evolution of companies' responses regarding market trends toward customized cosmetics, there is no "Intelligent Data Platform" that deals holistically with consumers' skin condition experience and thus attaches emotions to products and services. To find the Holy Grail of customized cosmetics, it is important to acquire and analyze consumer data on what they want in order to address their experiences and emotions. The emotions consumers are addressing when purchasing cosmetics varies by their age, sex, skin type, and specific skin issues and influences what price is considered reasonable. Therefore, it is necessary to classify emotions regarding cosmetics by individual consumer. Because of its importance, consumer emotion analysis has been used for both services and products. Given the trends identified above, we judge that consumer emotion analysis can be used in our study. Therefore, we collected and indexed data on consumers' emotions regarding their cosmetics experiences focusing on consumers' language. We crawled the cosmetics emotion data from SNS (blog and Twitter) according to sales ranking ($1^{st}$ to $99^{th}$), focusing on the ample/serum category. A total of 357 emotional adjectives were collected, and we combined and abstracted similar or duplicate emotional adjectives. We conducted a "Consumer Sentiment Journey" workshop to build a "Consumer Sentiment Dictionary," and this resulted in a total of 76 emotional adjectives regarding cosmetics consumer experience. Using these 76 emotional adjectives, we performed clustering with the Self-Organizing Map (SOM) method. As a result of the analysis, we derived eight final clusters of cosmetics consumer sentiments. Using the vector values of each node for each cluster, the characteristics of each cluster were derived based on the top ten most frequently appearing consumer sentiments. Different characteristics were found in consumer sentiments in each cluster. We also developed a cosmetics experience pattern map. The study results confirmed that recommendation and classification systems that consider consumer emotions and sentiments are needed because each consumer differs in what he or she pursues and prefers. Furthermore, this study reaffirms that the application of emotion and sentiment analysis can be extended to various fields other than cosmetics, and it implies that consumer insights can be derived using these methods. They can be used not only to build a specialized sentiment dictionary using scientific processes and "Design Thinking Methodology," but we also expect that these methods can help us to understand consumers' psychological reactions and cognitive behaviors. If this study is further developed, we believe that it will be able to provide solutions based on consumer experience, and therefore that it can be developed as an aspect of marketing intelligence.