• Journal of Intelligence and Information Systems
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• v.24 no.1
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• pp.227-252
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• 2018

The evolution of instant communication has mirrored the development of the Internet and messenger applications are among the most representative manifestations of instant communication technologies. In messenger applications, senders use emoticons to supplement the emotions conveyed in the text of their messages. The fact that communication via messenger applications is not face-to-face makes it difficult for senders to communicate their emotions to message recipients. Emoticons have long been used as symbols that indicate the moods of speakers. However, at present, emoticon-use is evolving into a means of conveying the psychological states of consumers who want to express individual characteristics and personality quirks while communicating their emotions to others. The fact that companies like KakaoTalk, Line, Apple, etc. have begun conducting emoticon business and sales of related content are expected to gradually increase testifies to the significance of this phenomenon. Nevertheless, despite the development of emoticons themselves and the growth of the emoticon market, no suitable emoticon recommendation system has yet been developed. Even KakaoTalk, a messenger application that commands more than 90% of domestic market share in South Korea, just grouped in to popularity, most recent, or brief category. This means consumers face the inconvenience of constantly scrolling around to locate the emoticons they want. The creation of an emoticon recommendation system would improve consumer convenience and satisfaction and increase the sales revenue of companies the sell emoticons. To recommend appropriate emoticons, it is necessary to quantify the emotions that the consumer sees and emotions. Such quantification will enable us to analyze the characteristics and emotions felt by consumers who used similar emoticons, which, in turn, will facilitate our emoticon recommendations for consumers. One way to quantify emoticons use is metadata-ization. Metadata-ization is a means of structuring or organizing unstructured and semi-structured data to extract meaning. By structuring unstructured emoticon data through metadata-ization, we can easily classify emoticons based on the emotions consumers want to express. To determine emoticons' precise emotions, we had to consider sub-detail expressions-not only the seven common emotional adjectives but also the metaphorical expressions that appear only in South Korean proved by previous studies related to emotion focusing on the emoticon's characteristics. We therefore collected the sub-detail expressions of emotion based on the "Shape", "Color" and "Adumbration". Moreover, to design a highly accurate recommendation system, we considered both emotion-technical indexes and emoticon-emotional indexes. We then identified 14 features of emoticon-technical indexes and selected 36 emotional adjectives. The 36 emotional adjectives consisted of contrasting adjectives, which we reduced to 18, and we measured the 18 emotional adjectives using 40 emoticon sets randomly selected from the top-ranked emoticons in the KakaoTalk shop. We surveyed 277 consumers in their mid-twenties who had experience purchasing emoticons; we recruited them online and asked them to evaluate five different emoticon sets. After data acquisition, we conducted a factor analysis of emoticon-emotional factors. We extracted four factors that we named "Comic", Softness", "Modernity" and "Transparency". We analyzed both the relationship between indexes and consumer attitude and the relationship between emoticon-technical indexes and emoticon-emotional factors. Through this process, we confirmed that the emoticon-technical indexes did not directly affect consumer attitudes but had a mediating effect on consumer attitudes through emoticon-emotional factors. The results of the analysis revealed the mechanism consumers use to evaluate emoticons; the results also showed that consumers' emoticon-technical indexes affected emoticon-emotional factors and that the emoticon-emotional factors affected consumer satisfaction. We therefore designed the emoticon recommendation system using only four emoticon-emotional factors; we created a recommendation method to calculate the Euclidean distance from each factors' emotion. In an attempt to increase the accuracy of the emoticon recommendation system, we compared the emotional patterns of selected emoticons with the recommended emoticons. The emotional patterns corresponded in principle. We verified the emoticon recommendation system by testing prediction accuracy; the predictions were 81.02% accurate in the first result, 76.64% accurate in the second, and 81.63% accurate in the third. This study developed a methodology that can be used in various fields academically and practically. We expect that the novel emoticon recommendation system we designed will increase emoticon sales for companies who conduct business in this domain and make consumer experiences more convenient. In addition, this study served as an important first step in the development of an intelligent emoticon recommendation system. The emotional factors proposed in this study could be collected in an emotional library that could serve as an emotion index for evaluation when new emoticons are released. Moreover, by combining the accumulated emotional library with company sales data, sales information, and consumer data, companies could develop hybrid recommendation systems that would bolster convenience for consumers and serve as intellectual assets that companies could strategically deploy.

• Journal of Intelligence and Information Systems
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• v.22 no.1
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• pp.139-157
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• 2016

Bankruptcy involves considerable costs, so it can have significant effects on a country's economy. Thus, bankruptcy prediction is an important issue. Over the past several decades, many researchers have addressed topics associated with bankruptcy prediction. Early research on bankruptcy prediction employed conventional statistical methods such as univariate analysis, discriminant analysis, multiple regression, and logistic regression. Later on, many studies began utilizing artificial intelligence techniques such as inductive learning, neural networks, and case-based reasoning. Currently, ensemble models are being utilized to enhance the accuracy of bankruptcy prediction. Ensemble classification involves combining multiple classifiers to obtain more accurate predictions than those obtained using individual models. Ensemble learning techniques are known to be very useful for improving the generalization ability of the classifier. Base classifiers in the ensemble must be as accurate and diverse as possible in order to enhance the generalization ability of an ensemble model. Commonly used methods for constructing ensemble classifiers include bagging, boosting, and random subspace. The random subspace method selects a random feature subset for each classifier from the original feature space to diversify the base classifiers of an ensemble. Each ensemble member is trained by a randomly chosen feature subspace from the original feature set, and predictions from each ensemble member are combined by an aggregation method. The k-nearest neighbors (KNN) classifier is robust with respect to variations in the dataset but is very sensitive to changes in the feature space. For this reason, KNN is a good classifier for the random subspace method. The KNN random subspace ensemble model has been shown to be very effective for improving an individual KNN model. The k parameter of KNN base classifiers and selected feature subsets for base classifiers play an important role in determining the performance of the KNN ensemble model. However, few studies have focused on optimizing the k parameter and feature subsets of base classifiers in the ensemble. This study proposed a new ensemble method that improves upon the performance KNN ensemble model by optimizing both k parameters and feature subsets of base classifiers. A genetic algorithm was used to optimize the KNN ensemble model and improve the prediction accuracy of the ensemble model. The proposed model was applied to a bankruptcy prediction problem by using a real dataset from Korean companies. The research data included 1800 externally non-audited firms that filed for bankruptcy (900 cases) or non-bankruptcy (900 cases). Initially, the dataset consisted of 134 financial ratios. Prior to the experiments, 75 financial ratios were selected based on an independent sample t-test of each financial ratio as an input variable and bankruptcy or non-bankruptcy as an output variable. Of these, 24 financial ratios were selected by using a logistic regression backward feature selection method. The complete dataset was separated into two parts: training and validation. The training dataset was further divided into two portions: one for the training model and the other to avoid overfitting. The prediction accuracy against this dataset was used to determine the fitness value in order to avoid overfitting. The validation dataset was used to evaluate the effectiveness of the final model. A 10-fold cross-validation was implemented to compare the performances of the proposed model and other models. To evaluate the effectiveness of the proposed model, the classification accuracy of the proposed model was compared with that of other models. The Q-statistic values and average classification accuracies of base classifiers were investigated. The experimental results showed that the proposed model outperformed other models, such as the single model and random subspace ensemble model.

• The Journal of Society for e-Business Studies
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• v.25 no.3
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• pp.41-61
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• 2020

China's rapid development and commercialization of high-tech technologies in the fourth industrial revolution has led to effective technology exchanges between Korean and Chinese firms becoming more important to Korea's mid-term and long-term industrial development. However, there is still a lack of empirical research on how technology exchanges between Korean and Chinese firms proceed and their effectiveness. In response, this study conducted a social network analysis based on text mining data of Korea-China business technology exchange and cooperation articles introduced in the news from 2018 to March 2020 on the current status and effects of Korea-China technology exchanges related to the fourth industrial revolution, and conducted a regression analysis how network centrality effect on the firm performance. According to the results, most of the Korean major electronic firms are actively networking with Chinese firms and institutions, showing high centrality in the centrality index. Korean telecommunication firms showed high betweenness centrality and subgraph centrality, and Korean Internet service providers and broadcasting contents firms showed high eigenvector centrality. In addition, Chinese firms showed higher betweenness centrality than Korean firms, and Chinese service firms showed higher closeness centrality than manufacturing firms. As a result of regression analysis, this network centrality had a positive effect on firm performance. To the best of our knowledge, this is the first to analyze the impact of the technical cooperation between Korean and Chinese firms under the fourth industrial revolution context. This study has theoretical implications that suggested the direction of social network analysis-based empirical research in global firm cooperation. Also, this study has practical implications that the guidelines for network analysis in setting the direction of technical cooperation between Korea and China by firms or governments.

• Journal of Korean Home Economics Education Association
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• v.17 no.2
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• pp.221-238
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• 2005

This study analyzed the contents of the milk-related nutrition education currently found in elementary and secondary school textbooks. An attempt was made to develop the basic data needed to in the future provide students with pertinent in formation regarding the nutritional attributes of milk, as well as the desired consumption behavior, within the school education system. To attain the objectives of this study, the researcher analyzed the contents of the milk-related nutrition education described in elementary and secondary school textbooks(1st-10th grades). Based on the results of this analysis, measures were developed to organize the contents of the milk-related nutrition education that should be taught within the school education system. At the elementary school level, milk-related nutrition education was included in the textbooks for the integrated curriculum for the lower grades, as well as in the science, practical arts, and physical education textbooks for every grade, except the End and the 6th. The practical arts textbook, which contained basic knowledge related to the nutritional attributes of milk and the proper method in which to intake milk, was found to be the one which dealt with milk-related nutrition education in the most detail. At the secondary school level. milk-related nutrition education was included in the 7th-10th grade textbooks for the science, technology and home economics, and physical education courses. In this instance. the technology and home economics textbooks were the ones which were found to contain the most milk-related nutrition education covering such aspects as the nutritional attributes of milk, the special characteristics of milk as a food. how to select and store milk. as well as how to use milk as part of a balanced diet in everyday life. However, as was the case at the elementary school levet the repetitious nature of the milk-related contents found in the textbooks for various school subjects and at different school levels, as well as the inefficient hierarchical structure in which the knowledge is presented, were identified as key problems. There is a need to establish the appropriate milk-related nutrition education for each school level. The need to develop education programs, which could be linked to the school subjects and special milk programs, was also emphasized.

• Journal of Korean Home Economics Education Association
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• v.29 no.2
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• pp.23-39
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• 2017

The Purpose of this study is to present the basic data for selecting and improving the safety education contents which help practically middle school students through analysis of contents of safety education in 'field of home life' of 2009 revised middle school textbooks. The subjects of analysis are 12 types of middle school textbooks: in total 24 books written by 12 publishers in terms of the revised curriculum in 2009. The analysis criteria is developed by the researcher referring to preceding studies regarding safety education based on the seventh safety education standard presented by the Ministry of Education (2015). With such analysis criteria, all words related to the contents of the safety education of analysis criteria were extracted from each textbook, such as words directly mentioned as 'safety', words mean as 'psychological safety' and 'happy life', words related to 'attention', 'note', 'stability' etc. Under the analytic frame of safety education contents according to a home economics textbook, content analysis method was used for producing the frequency and percent of those words. The textbook analysis shows that the number of pages regarding safety education is 336.3 pages, as 9.8% in total 3,412 pages of 12 types of technology and home economics textbooks. As following the analysis of each textbook volume of the proportion in the contents related to safety education, 224.9 pages are on the first volume and 111.9 pages are on the second volume. As grades increase from year one to year three, the proportion of safety education in home economics textbooks is decreased. The highest number of safety education contents unit is 'Self-management of youth' which includes three parts of safety education. In the case of a unit for emphasizing practice, experience and practical exercise such as 'Life of youth' and 'Practice of eco-living', safety education content in the area of 'life safety' are mostly contained. Safety accidents related to the most student experienced, Household accidents (1.4%) and experiment or practice accidents (0.3%) are presented in a low figure. The contents of universal housing and school violence are duplicated on first and second volume of text. The most presented safety education content in the 12 types of textbooks are proper sexual attitude, dietary problems, family conflict and food choice. The least common contents are dangerous drugs, family welfare, internet addiction and industrial accident compensation insurance. As this study is to analyze 12 textbooks developed in 2009 revision curriculum, it is necessary to compare it with the textbook written by the revised curriculum in 2015 and to clarify the contents system of safety education and to avoid duplication of contents. In addition, it is necessary to develop and distribute a safety education program that can support textbooks.

• Korean Journal of Health Education and Promotion
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• v.14 no.1
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• pp.23-45
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• 1997

This study was conducted from March 1, 1996 through June 30, in order to provide basic data for devising a policy for school health especially students health promotion and for developing of an education program. Middle school students were 1000, high school students were 2000 and a total of 3000 students were selected randomly among the boys/girls/middle/high schools which are in Seoul, Pusan, Taegu, Pohang, Suwon, Kyungsan, Milyang and a town or subcountry. The summary and conclusion are as follows. 1. In general characteristics of respondents, 51.8% were girl students, 33.7% were middle school students, 66.3% were high school students. 37.2% were living in a medium and small city, 89.1% were middle classes, 43.6% were having no religion, 27.3% were buddhists. 2. As a result of analyzing, exercise, nutrition, personal behavior, knowledge of health education and behavior level which are the factors promotion, exercise level were 3.61 of the perfect 9(40.1/100), nutrition level were 3.71(41.1/100), personal hygiene were 6.89(76.6/100), health education level were 5.1(58.9/100), all of the them are low level. 3. Judging from characteristics, in case of exercise behavior level, It was far higher in boy students than in girl students, in middle school students than in high school students. It was respectively higher than other groups in the second graders of middle school, in the first graders of high school, in the residents who live in a big city, in the high classes in the buddhists. 4. The students level against disease was average 9.11 of the perfect score 14(65.1/100). The level of disease consciousness was high in girl students by characteristics, in the second graders of high school by grades, in high school students than middle school students. 5. In health status, 55.4% were healthy, 7.9% were unhealthy. It was respectively higher than the other groups in boy students, in middle school students, in the residents who live in a big city, in high classes of life level, in buddihists, in higher education level of parents. 6. Judging from the factors of health status and health promotion and the degree of significance, there's a significant differences between exercise and dietary life as P〈0.001, in personal hygiene as P〈0.05, in health education an P〈0.01. 7. Knowledge on disease, health promotion behavior level were average 19.42 ± 4.01 of the perfect score 50(38.8/100) this score was too low. As for characteristics, the level between variables was statistically significant in the higher life level, in the higher parents education level, in the happier family. 8. Judging from health status, knowledge on disease, health behavior level, knowledge and health promotion behavior level significantly in the better health status, in the better school record. 9. As a result of the multiplex regression analyzing the factors which were under influence on health status, the variables like exercise, school record level, the degree of family happiness, nutrition, grades, the members of family influenced much and its persuasive power was 10.2%. The factors which are under the influence on the health promotion were exercise, satisfied degree of education, health status, the degree of family happiness, knowledge on disease, the usage of physical training, sex, the number of the family members, mother's education level. It’s explained power was 21.3%. promotion were high We should develop a text book and an education program to study exercise, nutrition(dietary life), personal hygiene, knowledge on disease and health systematically. As far as health education irrespective city and locality without considering the entrance exam for high school and university we should execute it continuously. To do this, it’s important to cultivate and secure qualified men of ability who can teach things related health promotion and the related subject, that is, health or health promotion subject should be established in middle and high school curriculum necessarily.

• Korea Journal of Hospital Management
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• v.8 no.1
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• pp.135-164
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• 2003

The operating room is the major facility that costs the highest investment per unit area in a hospital. It requires commitment of hospital resources such as manpower, equipments and material. The quantity of these resources committed actually differs from one type of operation to another. Because of this, it is not an easy task to allocate the operating cost to individual clinical departments that share the operating room. A practical way to do so may be to collect and add the operating costs incurred by each clinical department and charge the net cost to the account of the corresponding clinical department. It has been customary to allocate the cost of the operating room to the account of each individual department on the basis of the ratio of the number of operations of the department or the total revenue by each operating room. In an attempt to set up more rational cost allocation method than the customary method, this study proposes a new cost allocation method that calls for itemizing the operation cost into its constituent expenses in detail and adding them up for the operating cost incurred by each individual department. For comparison of the new method with the conventional method, the operating room in the main building of hospital A near Seoul is chosen as a study object. It is selected because it is the biggest operating room in hospital A and most of operations in this hospital are conducted in this room. For this study the one-month operation record performed in January 2001 in this operating room is analyzed to allocate the per-month operation cost to six clinical departments that used this operating room; the departments of general surgery, orthopedic surgery, neuro-surgery, dental surgery, urology, and obstetrics & gynecology. In the new method(or method 1), each operation cost is categorized into three major expenses; personnel expense, material expense, and overhead expense and is allocated into the account of the clinical department that used the operating room. The method 1 shows that, among the total one-month operating cost of 814,054 thousand wons in this hospital, 163,714 thousand won is allocated to GS, 335,084 thousand won to as, 202,772 thousand won to NS, 42,265 thousand won to uno, 33,423 thousand won to OB/GY, and 36.796 thousand won to DS. The allocation of the operating cost to six departments by the new method is quite different from that by the conventional method. According to one conventional allocation method based on the ratio of the number of operations of a department to the total number of operations in the operating room(method 2 hereafter), 329,692 thousand won are allocated to GS, 262,125 thousand won to as, 87,104 thousand won to NS, 59,426 thousand won to URO, 51.285 thousand won to OB/GY, and 24,422 thousand won to DS. According to the other conventional allocation method based on the ratio of the revenue of a department(method 3 hereafter), 148,158 thousand won are allocated to GS, 272,708 thousand won to as, 268.638 thousand won to NS, 45,587 thousand won to uno, 51.285 thousand won to OB/GY, and 27.678 thousand won to DS. As can be noted from these results, the cost allocation to six departments by method 1 is strikingly different from those by method 2 and method 3. The operating cost allocated to GS by method 2 is about twice by method 1. Method 3 makes allocations of the operating cost to individual departments very similarly as method 1. However, there are still discrepancies between the two methods. In particular the cost allocations to OB/GY by the two methods have roughly 53.4% discrepancy. The conventional methods 2 and 3 fail to take into account properly the fact that the average time spent for the operation is different and dependent on the clinical department, whether or not to use expensive clinical material dictate the operating cost, and there is difference between the official operating cost and the actual operating cost. This is why the conventional methods turn out to be inappropriate as the operating cost allocation methods. In conclusion, the new method here may be laborious and cause a complexity in bookkeeping because it requires detailed bookkeeping of the operation cost by its constituent expenses and also by individual clinical department, treating each department as an independent accounting unit. But the method is worth adopting because it will allow the concerned hospital to estimate the operating cost as accurately as practicable. The cost data used in this study such as personnel expense, material cost, overhead cost may not be correct ones. Therefore, the operating cost estimated in the main text may not be the same as the actual cost. Also, the study is focused on the case of only hospital A, which is hardly claimed to represent the hospitals across the nation. In spite of these deficiencies, this study is noteworthy from the standpoint that it proposes a practical allocation method of the operating cost to each individual clinical department.

• Journal of the Korean earth science society
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• v.18 no.6
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• pp.453-463
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• 1997

The contents of high school 'Common science' textbooks was analyzed qualitatively and quantitatively. Seven common science textbooks were selected and its contents, structure, inquiry, activities, appendix and its characteristics were investigated, and analyzed using the Goal Clusters of Project Synthesis and Romey's indices of text evaluation were calculated. The contents of each unit are not much different among textbooks because they are written according to the curriculum ordinance and textbook guidelines of the Ministry of Education. The textbooks was consist of $471{\sim}519$ pages. It was distribute similarly among the chapter of 'materials', 'forces', lives' and 'earth'. The chapter of 'energy' and 'environment' was treat significantly. The contents and structure of common science is a mere physical consolidation. I make an alternative plan that a topic form. Inquiry activities used in the textbooks are 11 type, however most of that is interpretation of data, experiment, survey and discussion. Ninety six percents of the experiment, belong to the 1st level, four percents of that belong to the 2nd level of the Schwab's inquiry level and there are no activities of the 3rd level. Little attention is given to Goal Cluster I, II, IV in the common science textbooks currently employed. Its content should be broadened to include all Goal Clusters of Project Synthesis. Homey's indices representing the degrees of student involvement. are $0.57{\sim}1.14$ for sentence analysis, $0.60{\sim}1.67$ for figure and diagram analysis, $0.67{\sim}1.50$ for analysis of questions at chapter ends, respectively, student activity per page investigated being $0.6{\sim}0.9$. But chapter summaries cease to repeats the conclusions of the chapter also it be rather formally and inattentively written.

• Science of Emotion and Sensibility
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• v.13 no.1
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• pp.47-60
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• 2010

Most of the researches about classification usually have used kNN(k-Nearest Neighbor), SVM(Support Vector Machine), which are known as learn-based model, and Bayesian classifier, NNA(Neural Network Algorithm), which are known as statistics-based methods. However, there are some limitations of space and time when classifying so many web pages in recent internet. Moreover, most studies of classification are using uni-gram feature representation which is not good to represent real meaning of words. In case of Korean web page classification, there are some problems because of korean words property that the words have multiple meanings(polysemy). For these reasons, LSA(Latent Semantic Analysis) is proposed to classify well in these environment(large data set and words' polysemy). LSA uses SVD(Singular Value Decomposition) which decomposes the original term-document matrix to three different matrices and reduces their dimension. From this SVD's work, it is possible to create new low-level semantic space for representing vectors, which can make classification efficient and analyze latent meaning of words or document(or web pages). Although LSA is good at classification, it has some drawbacks in classification. As SVD reduces dimensions of matrix and creates new semantic space, it doesn't consider which dimensions discriminate vectors well but it does consider which dimensions represent vectors well. It is a reason why LSA doesn't improve performance of classification as expectation. In this paper, we propose new LSA which selects optimal dimensions to discriminate and represent vectors well as minimizing drawbacks and improving performance. This method that we propose shows better and more stable performance than other LSAs' in low-dimension space. In addition, we derive more improvement in classification as creating and selecting features by reducing stopwords and weighting specific values to them statistically.

• Journal of Korean Society of Transportation
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• v.35 no.4
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• pp.360-373
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• 2017

The BTO-a projects is the types, which has a demand risk among the type of PPP projects in Korea. When demand risk is realized, private investor encounters financial difficulties due to lower revenue than its expectation and the government may also have a problem in stable infrastructure operation. In this regards, the government has applied various risk sharing policies in response to demand risk. However, the amount of government's risk sharing is the government's contingent liabilities as a result of demand uncertainty, and it fails to be quantified by the conventional NPV method of expressing in the text of the concession agreement. The purpose of this study is to estimate the value of investment risk sharing by the government considering the demand risk in the profit sharing system (BTO-a) introduced in 2015 as one of the demand risk sharing policy. The investment risk sharing will take the form of options in finance. Private investors have the right to claim subsidies from the government when their revenue declines, while the government has the obligation to pay subsidies under certain conditions. In this study, we have established a methodology for estimating the value of investment risk sharing by using the Black - Scholes option pricing model and examined the appropriateness of the results through case studies. As a result of the analysis, the value of investment risk sharing is estimated to be 12 billion won, which is about 4% of the investment cost of the private investment. In other words, it can be seen that the government will invest 12 billion won in financial support by sharing the investment risk. The option value when assuming the traffic volume risk as a random variable from the case studies is derived as an average of 12.2 billion won and a standard deviation of 3.67 billion won. As a result of the cumulative distribution, the option value of the 90% probability interval will be determined within the range of 6.9 to 18.8 billion won. The method proposed in this study is expected to help government and private investors understand the better risk analysis and economic value of better for investment risk sharing under the uncertainty of future demand.