• Journal of Intelligence and Information Systems
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• v.18 no.1
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• pp.109-123
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• 2012

Many kinds of the education systems are provided to students. Many kinds of the contents like School subjects, license, job training education and so on are provided through many kinds of the media like text, image, video and so on. Students will apply the knowledge they learnt and will use it when they learn other things. In the existing education system, there have been many situations that the education system isn't really helpful to the students because too hard contents are transferred to them or because too easy contents are transferred to them and they learn the contents they already know again. To solve this phenomenon, a method that transfers the most proper lecture contents to the students is suggested in the thesis. Because the difficulty is relative, the contents A can be easier than the contents B to a group of the students and the contents B can be easier than the contents A to another group of the students. Therefore, it is not easy to measure the difficulty of the lecture contents. A method considering this phenomenon to transfer the proper lecture contents is suggested in the thesis. The whole lecture contents are divided into many lecture modules. The students solve the pattern recognition questions, a kind of the prior test questions, before studying the lecture contents and the system selects and provides the most proper lecture module among many lecture modules to the students according to the score about the questions. When the system selects the lecture module and transfer it to the student, the students' answer and the difficulty of the lecture modules are considered. In the existing education system, 1 kind of the content is transferred to various students. If the same lecture contents is transferred to various students, the contents will not be transferred efficiently. The system selects the proper contents using the students' pattern recognition answers. The pattern recognition question is a kind of the prior test question that is developed on the basis of the lecture module and used to recognize whether the student knows the contents of the lecture module. Because the difficulty of the lecture module reflects the all scores of the students' answers, whenever a student submits the answer, the difficulty is changed. The suggested system measures the relative knowledge of the students using the answers and designates the difficulty. The improvement of the suggested method is only applied when the order of the lecture contents has nothing to do with the progress of the lecture. If the contents of the unit 1 should be studied before studying the contents of the unit 2, the suggested method is not applied. The suggested method is introduced on the basis of the subject "English grammar", subjects that the order is not important, in the thesis. If the suggested method is applied properly to the education environment, the students who don't know enough basic knowledge will learn the basic contents well and prepare the basis to learn the harder lecture contents. The students who already know the lecture contents will not study those again and save more time to learn more various lecture contents. Many improvement effects like these and so on will be provided to the education environment. If the suggested method that is introduced on the basis of the subject "English grammar" is applied to the various education systems like primary education, secondary education, job education and so on, more improvement effects will be provided. The direction to realize these things is suggested in the thesis. The suggested method is realized with the MySQL database and Java, JSP program. It will be very good if the suggested method is researched developmentally and become helpful to the development of the Korea education.

• Journal of Korean Society of Disaster and Security
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• v.12 no.1
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• pp.11-21
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• 2019

This study assessed the risk of disaster by using QRE(Quick Risk Estimation - UNISDR Roll Model City of Basic Evaluation Tool) tools for three natural disasters and sixteen social disasters managed by the Seoul Metropolitan Government. The criteria for selecting 19 disaster types in Seoul are limited to disasters that occur frequently in the past and cause a lot of damage to people and property if they occur. We also considered disasters that are likely to occur in the future. According to the results of the QRE tools for disaster type in Seoul, the most dangerous type of disaster among the Seoul city disasters was "suicide accident" and "deterioration of air quality". Suicide risk is high and it is not easy to take measures against the economic and psychological problems of suicide. This corresponds to the Risk ratings(Likelihood ranking score & Severity rating) "M6". In contrast, disaster types with low risk during the disaster managed by the city of Seoul were analyzed as flooding, water leakage, and water pollution accidents. In the case of floods, there is a high likelihood of disaster such as localized heavy rains and typhoons. However, the city of Seoul has established a comprehensive plan to reduce floods and water every five years. This aspect is considered to be appropriate for disaster prevention preparedness and relatively low disaster risk was analyzed. This corresponds to the disaster Risk ratings(Likelihood ranking score & Severity rating) "VL1". Finally, the QRE tool provides the city's leaders and disaster managers with a quick reference to the risk of a disaster so that decisions can be made faster. In addition, the risk assessment using the QRE tool has helped many aspects such as systematic evaluation of resilience against the city's safety risks, basic data on future investment plans, and disaster response.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.16 no.1
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• pp.71-85
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• 2021

Representative domestic start-up support organizations include the Business Incubator(BI), Korea Institute of Startup & Entrepreneurship Development(KISED), Techno Park(TP), and Center of Creative Economy Innovation(CCEI), and there are about 260 Business incubator nationwide. The Business incubator is operated by universities, research institutes, and private foundations or associations. The organization consists of the center director and the incubating professionals (hereinafter referred to as "manager"), etc., and performs tasks such as center operation management and incubation support services for tenant companies. Until now, research on the operation of Business Incubator has been mainly focused on the performance of tenant companies. Studies on whether the manager's competency characteristics directly or indirectly affect the performance of the tenant companies through psychological mediators such as self-efficacy and organizational commitment were very scarce. The purpose of this study is to explore various factors influencing organizational commitment and job performance by the competence characteristics of Business incubator managers, and to explain the causal relationship among those factors. In particular, the difference in perception was investigated by a manager's survey that influences organizational commitment and work performance at the Business incubator. Through this, we intend to present practical implications for the role of managers in the operation of Business incubators. This study is an exploratory study, and the subject of the study was a survey of about 600 managers working at Business incubator nationwide, of which 116 responses were analyzed. Data analysis included descriptive statistics, exploratory factor analysis, and reliability. Structural equation model analysis was performed for hypothesis tests. As a result of the analysis, it was found that the cognitive characteristics of the Business incubator manager, communication, and situational response as the behavioral characteristics had a positive effect on the manager's self-efficacy, and the behavioral characteristics had a greater effect on the self-efficacy. It was also found that the manager's cognitive and behavioral characteristics, and self-efficacy had a positive effect on organizational commitment and work performance. In particular, a manager's self-efficacy has a positive effect on organizational commitment and work performance. This result showed that the manager's competency characteristics increase the manager's self-efficacy as a mediating factor rather than directly affecting organizational commitment and work performance. This study explains that the manager's competency characteristics are transferred to organizational commitment and work performance. The results of the study are expected to reflect the job standard of the National Competency Standards (NCS) and basic vocational competency to the job competency of managers, and it also provides a guideline for the effective business incubator operation in terms of human resource management. In practice, it is expected that the results of the study can reflect the vocational basic skills of the Business Incubator manager's job competency in the National Competency Standards(NCS) section, and suggest directions for the operation of the Business Incubator and the manager's education and training.

• 한국노년학
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• v.39 no.3
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• pp.517-529
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• 2019

The study was conducted on the impact of employment types middle and old age group of wage earner on life satisfaction and analyzed by dividing it into variables in the employment types and demographic characteristics. Based on the data for the 12th year of the Korea Welfare Panel Study, 1,244 respondents who answered that the main types of economic activities were 'full-time, temporary, daily wage earners' or 'self-help labor, public labor, and elderly empolyment program in public sector.' among 4,341 people over 55 years of age under the age of 75 as of 2017 standard. The survey covered 1,244 people. By age group, 826 people aged 55-64 (middle-age group) and 418 people aged 65-74(old-age group). Middle age group showed that education level, spouse, health condition, beneficiaries of basic livelihood and average monthly income variables were the factors that influence the satisfaction of life. But The type of employment did not significantly affect. Old age group showed that the higher education level, in spouse with-living or spouse death, the better health condition is perceived, the less experience of beneficiaries of basic livelihood, the higher average monthly income, the more satisfied life is. The survey also found that old-aged people who participate in "self-help labor, public labor, and elderly employment program in public sector" are also found to be more satisfied with their lives. According to these results, policy for the old age group should be focused on hunting and expanding of employment program in public sector for the elderly. In order to boost life satisfaction of the elderly, more intensive vocational education and employment training should be provided.

• Journal of Environmental Impact Assessment
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• v.32 no.6
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• pp.533-544
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• 2023

The Ministry of Agriculture, Food and Rural Affairs has been promoting policies to strengthen the functions of rural centers (culture, welfare, economy, education, etc.) and to ensure that services from the centers are delivered to and connected to hinterland villages. For this policy purpose, the rural center revitalization project and the basic living base creation project within the rural development projects are being promoted. However, in the process of carrying out the actual project, as the focus is on strengthening the functions of rural centers, service delivery and connection with hinterland villages are not being actively promoted. therefore, in this study, we analyze the projects previously carried out in Jeoksang-myeon, Muju-gun and the regional status, analyze the reasons why hinterland village services were not connected and activated, and propose a direction for the second phase of the basic living base creation project to be carried out in the future. As a result of analyzing the reasons for the failure of hinterland village services to be activated, problems such as disadvantages in accessing services due to dispersed residence in rural areas and limitations in topographical structure, and the lack of a service delivery system to develop demand in hinterland areas were found to be problems. Improvement measures were derived as follows. First, it is a stepping stone construction plan proposed to overcome topographical limitations. Establish a stepping base that will function as a service intermediate terminal to ensure efficient service delivery. Second, for a rational decision-making structure, we proposed a plan for deploying communication channels that could closely collect local opinions by operating various small-scale communities along with the efficient composition of a resident committee that includes residents of the central and hinterland villages and various classes. Third, it is a virtuous cycle of local manpower training plans that train local residents into professional instructors. We aim to complete a sustainable, resident-led service supply system by nurturing the most important service deliverers, that is, activists, in service delivery.

• Korean Journal of Health Education and Promotion
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• v.2 no.1
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• pp.3-50
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• 1984

The levels of health knowledge, attitude and practice of housewives considerably effect to the health of households, communities and the nation. This study was designed to grasp the levels of health knowledge, attitude and practice of houswives and analyse the various factors effecting to health in order to provide health education services as well as materials for effective formulation and implementation of health policy to improve the health of the nation. This study has been conducted through interviews by trained surveyers for 4,281 housewives selected from 4,500 households throughout the country for 40 days during July 11-August 20, 1983. The results of survey were analysed by stepwise multiple regression and path analysis are summarized as follows; 1. Based on the measurement instrument applied to this study, the levels of health knowledge, attitude and practice of housewives were extremely low with 54.5 points out of 100 points in full. Higher level with 72 points and above was approximately 21 percent and lower level with 39 points and below was approx. 24 percent. The middle level was approx. 55 percent. In order to implement health programs successively, health education should be more strengthened and to improve the level of health knowledge, attitude and practice (KAP) of the nation, political consideration as a part of spiritual reformation must be concentrated on health. 2. The level of health knowledge indicated the highest points with 57.3 the level of attitude was the second with 55.0 points and the practice level was the lowest with 50.0 point. Therefore, planning and implementation of health education program must be based on the persuasion and motivation that health knowledge turn into practice. 3. Housewives who had higher level of health knowledge, showed their practice level was relatively lower and those who had middle or low level of it practice level was the reverse. 4. Correlations among health knowledge, attitude and practice (KAP) were generally higher and statistically significant at 0.1 percent level. Correlation between total health KAP level and health knowledge was the highest with r=.8092. 5. Health KAP levels showed significant differences according to the age, number of children, marital status, self-assessed health status and concern on health of the housewives interviewed (p<0.001) 6. Health KAP levels also showed significant differences according to the education level, economic status, employment before marriage and grown-up area of the housewives interviewed. (p<0.001) 7. Heath KAP levels showed significant differences according to health insurance benificiary and the existence of patients in the family. (p<0.001). 8. Health KAP levels showed significant differences according to distance to government organizations, schools, distance to health facilities, telephone possession rate, television possession rate, newspaper reading rate and activities of Ban meeting and Women's club. (p<0.001) 9. Health KAP levels showed significant differences according to electric mass communication media such as television, radio and village broadcasting etc. and printed media such as newspaper, magazine and booklets etc., IEC variables such as individual consultation and husband-wife communication, however, there was no significance with group training. 10. Health KAP of the housewives showed close correlation with personal characteristics variables, i.e., education level (r=.5302), age (r=-.3694) grown-up area (r=.3357) and employment before marriage. In general, correlation of health knowledge level was higher than the levels of attitude or practice. In case of health concern and health insurance, correlation of practice level was higher than health knowledge level. 11. Health KAP levels showed higher correlation with community environmental characteristics, Ban meeting and activity of Women's club, however, no correlation with New-village movement. 12. Among IEC variables, husband-wife communication showed the highest correlation with health KAP levels and printed media, electric mas communication media and health consultation in order. Therefore, encouragement of husband-wife communication and development of training program for men should be included in health education program. 13. Mass media such as electric mass com. and printed media were effective for knowledge transmission and husband-wife communication and individual consultation were effective for health practice. Group training was significant for knowledge transmission, however, but not significant for attitude formation or turning to health practice. To improve health KAP levels, health knowledge should be transmitted via mass media and health consultation with health professionals and field health workers should be strengthened. 14. Correlation of health KAP levels showed that knowledge level was generally higher than that of practice and recognized that knowledge was not linked with attitude or practice. 15. The twenty-five variables effecting health KAP levels of housewives had 41 per cent explanation variances among which education level had great contribution (β=.2309) and electric mass com. media (β=.1778), husband-wife communication (β=.1482), printed media, grown-up area, and distance to government organizations in order. Variances explained (R²) of health KAP were 31%, 15%, and 30% respectively. 16. Principal variables contributed to health KAP were education level (β=.12320, β=.1465), electric mass comm. media (β=.1762, β=.1839), printed media, (β=.1383, β=.1420) husband-wife communication (β=.1004, β=.1067), grown-up area and distance to government organizations, in order. Since education level contributes greatly to health KAP of the housewives, health education including curriculum development in primary, middle and high schools must be emphasized and health science must be selected as one of the basic liberal arts subject in universities. 17. Variences explained of IEC variables to health KAP were 19% in total, 14% in knowledge, 9% in attitude, and 10% in health practice. Contributions of IEC variables to health KAP levels were printed media (β=.3882), electric mass comm media (β=.3165), husb-band wife com. (β=.2095,) and consultation on health (β=.0841) in order, however, group training showed negative effect (β=-.0402). National fund must be invested for the development of Health Program through mass media such as TV and radio etc. and for printed materials such as newspaper, magazines, phamplet etc. needed for transmission of health knowledge. 18. Variables contributed to health KAP levels through IEC variables with indirect effects were education level (Ind E=0.0410), health concern (Ind E=.0161), newspaper reading rate (Ind E=.0137), TV possession rate and activity of Ban meeting in order, however, health facility showed negative effect (Ind E=-.0232) and other variables showed direct effect but not indirect effect. 19. Among the variables effecting health KAP level, education level showed the highest in total effect (TE=.2693) then IEC (TE=.1972), grown-up city (TE=.1237), newspaper reading rate (TE=.1020), distance to government organization (TE=.095) in order. 20. Variables indicating indirect effects to health KAP levels were; at knowledge level with R²=30%, education level (Ind E=.0344), newspaper reading rate (Ind E=.0112), TV possession rate (Ind E=.0689), activity of Ban meeting (Ind E=.0079) in order and at attitude level with R²=13%, education level (Ind E=. 0338), activity of Ban meeting (Ind E=.0079), and at practice level with R²=29%. education level (Ind E=.0268), health facility (Ind E=.0830) and concern on health (Ind E=.0105). 21. Total effect to health KAP levels and IEC by variable characteristics, personal characteristics variables indicated larger than community characteristics variables. 22. Multiple Correlation Coefficient (MCC) expressed by the Personal Characteristic Variable was .5049 and explained approximately 25% of variances. MCC expressed by total Community environment variable was .4283 and explained approx. 18% of variances. MCC expressed by IEC Variables was .4380 and explained approx. 19% of variances. The most important variable effected to health KAP levels was personal characteristic and then IEC variable, Community Environment variable in order. When the IEC effected with personal characteristic or community characteristic, the MCC or the variances were relatively higher than effecting alone. Therefore it was identified that the IEC was one of the important intermediate variable.

• Journal of Intelligence and Information Systems
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• v.23 no.2
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• pp.123-138
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• 2017

Since the stock market is driven by the expectation of traders, studies have been conducted to predict stock price movements through analysis of various sources of text data. In order to predict stock price movements, research has been conducted not only on the relationship between text data and fluctuations in stock prices, but also on the trading stocks based on news articles and social media responses. Studies that predict the movements of stock prices have also applied classification algorithms with constructing term-document matrix in the same way as other text mining approaches. Because the document contains a lot of words, it is better to select words that contribute more for building a term-document matrix. Based on the frequency of words, words that show too little frequency or importance are removed. It also selects words according to their contribution by measuring the degree to which a word contributes to correctly classifying a document. The basic idea of constructing a term-document matrix was to collect all the documents to be analyzed and to select and use the words that have an influence on the classification. In this study, we analyze the documents for each individual item and select the words that are irrelevant for all categories as neutral words. We extract the words around the selected neutral word and use it to generate the term-document matrix. The neutral word itself starts with the idea that the stock movement is less related to the existence of the neutral words, and that the surrounding words of the neutral word are more likely to affect the stock price movements. And apply it to the algorithm that classifies the stock price fluctuations with the generated term-document matrix. In this study, we firstly removed stop words and selected neutral words for each stock. And we used a method to exclude words that are included in news articles for other stocks among the selected words. Through the online news portal, we collected four months of news articles on the top 10 market cap stocks. We split the news articles into 3 month news data as training data and apply the remaining one month news articles to the model to predict the stock price movements of the next day. We used SVM, Boosting and Random Forest for building models and predicting the movements of stock prices. The stock market opened for four months (2016/02/01 ~ 2016/05/31) for a total of 80 days, using the initial 60 days as a training set and the remaining 20 days as a test set. The proposed word - based algorithm in this study showed better classification performance than the word selection method based on sparsity. This study predicted stock price volatility by collecting and analyzing news articles of the top 10 stocks in market cap. We used the term - document matrix based classification model to estimate the stock price fluctuations and compared the performance of the existing sparse - based word extraction method and the suggested method of removing words from the term - document matrix. The suggested method differs from the word extraction method in that it uses not only the news articles for the corresponding stock but also other news items to determine the words to extract. In other words, it removed not only the words that appeared in all the increase and decrease but also the words that appeared common in the news for other stocks. When the prediction accuracy was compared, the suggested method showed higher accuracy. The limitation of this study is that the stock price prediction was set up to classify the rise and fall, and the experiment was conducted only for the top ten stocks. The 10 stocks used in the experiment do not represent the entire stock market. In addition, it is difficult to show the investment performance because stock price fluctuation and profit rate may be different. Therefore, it is necessary to study the research using more stocks and the yield prediction through trading simulation.

• Journal of Intelligence and Information Systems
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• v.26 no.1
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• pp.1-21
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• 2020

With the rapid development of artificial intelligence technology, various techniques have been developed to extract meaningful information from unstructured text data which constitutes a large portion of big data. Over the past decades, text mining technologies have been utilized in various industries for practical applications. In the field of business intelligence, it has been employed to discover new market and/or technology opportunities and support rational decision making of business participants. The market information such as market size, market growth rate, and market share is essential for setting companies' business strategies. There has been a continuous demand in various fields for specific product level-market information. However, the information has been generally provided at industry level or broad categories based on classification standards, making it difficult to obtain specific and proper information. In this regard, we propose a new methodology that can estimate the market sizes of product groups at more detailed levels than that of previously offered. We applied Word2Vec algorithm, a neural network based semantic word embedding model, to enable automatic market size estimation from individual companies' product information in a bottom-up manner. The overall process is as follows: First, the data related to product information is collected, refined, and restructured into suitable form for applying Word2Vec model. Next, the preprocessed data is embedded into vector space by Word2Vec and then the product groups are derived by extracting similar products names based on cosine similarity calculation. Finally, the sales data on the extracted products is summated to estimate the market size of the product groups. As an experimental data, text data of product names from Statistics Korea's microdata (345,103 cases) were mapped in multidimensional vector space by Word2Vec training. We performed parameters optimization for training and then applied vector dimension of 300 and window size of 15 as optimized parameters for further experiments. We employed index words of Korean Standard Industry Classification (KSIC) as a product name dataset to more efficiently cluster product groups. The product names which are similar to KSIC indexes were extracted based on cosine similarity. The market size of extracted products as one product category was calculated from individual companies' sales data. The market sizes of 11,654 specific product lines were automatically estimated by the proposed model. For the performance verification, the results were compared with actual market size of some items. The Pearson's correlation coefficient was 0.513. Our approach has several advantages differing from the previous studies. First, text mining and machine learning techniques were applied for the first time on market size estimation, overcoming the limitations of traditional sampling based- or multiple assumption required-methods. In addition, the level of market category can be easily and efficiently adjusted according to the purpose of information use by changing cosine similarity threshold. Furthermore, it has a high potential of practical applications since it can resolve unmet needs for detailed market size information in public and private sectors. Specifically, it can be utilized in technology evaluation and technology commercialization support program conducted by governmental institutions, as well as business strategies consulting and market analysis report publishing by private firms. The limitation of our study is that the presented model needs to be improved in terms of accuracy and reliability. The semantic-based word embedding module can be advanced by giving a proper order in the preprocessed dataset or by combining another algorithm such as Jaccard similarity with Word2Vec. Also, the methods of product group clustering can be changed to other types of unsupervised machine learning algorithm. Our group is currently working on subsequent studies and we expect that it can further improve the performance of the conceptually proposed basic model in this study.

• Journal of Intelligence and Information Systems
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• v.24 no.2
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• pp.59-83
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• 2018

With the increasing importance of sentiment analysis to grasp the needs of customers and the public, various types of deep learning models have been actively applied to English texts. In the sentiment analysis of English texts by deep learning, natural language sentences included in training and test datasets are usually converted into sequences of word vectors before being entered into the deep learning models. In this case, word vectors generally refer to vector representations of words obtained through splitting a sentence by space characters. There are several ways to derive word vectors, one of which is Word2Vec used for producing the 300 dimensional Google word vectors from about 100 billion words of Google News data. They have been widely used in the studies of sentiment analysis of reviews from various fields such as restaurants, movies, laptops, cameras, etc. Unlike English, morpheme plays an essential role in sentiment analysis and sentence structure analysis in Korean, which is a typical agglutinative language with developed postpositions and endings. A morpheme can be defined as the smallest meaningful unit of a language, and a word consists of one or more morphemes. For example, for a word '예쁘고', the morphemes are '예쁘(= adjective)' and '고(=connective ending)'. Reflecting the significance of Korean morphemes, it seems reasonable to adopt the morphemes as a basic unit in Korean sentiment analysis. Therefore, in this study, we use 'morpheme vector' as an input to a deep learning model rather than 'word vector' which is mainly used in English text. The morpheme vector refers to a vector representation for the morpheme and can be derived by applying an existent word vector derivation mechanism to the sentences divided into constituent morphemes. By the way, here come some questions as follows. What is the desirable range of POS(Part-Of-Speech) tags when deriving morpheme vectors for improving the classification accuracy of a deep learning model? Is it proper to apply a typical word vector model which primarily relies on the form of words to Korean with a high homonym ratio? Will the text preprocessing such as correcting spelling or spacing errors affect the classification accuracy, especially when drawing morpheme vectors from Korean product reviews with a lot of grammatical mistakes and variations? We seek to find empirical answers to these fundamental issues, which may be encountered first when applying various deep learning models to Korean texts. As a starting point, we summarized these issues as three central research questions as follows. First, which is better effective, to use morpheme vectors from grammatically correct texts of other domain than the analysis target, or to use morpheme vectors from considerably ungrammatical texts of the same domain, as the initial input of a deep learning model? Second, what is an appropriate morpheme vector derivation method for Korean regarding the range of POS tags, homonym, text preprocessing, minimum frequency? Third, can we get a satisfactory level of classification accuracy when applying deep learning to Korean sentiment analysis? As an approach to these research questions, we generate various types of morpheme vectors reflecting the research questions and then compare the classification accuracy through a non-static CNN(Convolutional Neural Network) model taking in the morpheme vectors. As for training and test datasets, Naver Shopping's 17,260 cosmetics product reviews are used. To derive morpheme vectors, we use data from the same domain as the target one and data from other domain; Naver shopping's about 2 million cosmetics product reviews and 520,000 Naver News data arguably corresponding to Google's News data. The six primary sets of morpheme vectors constructed in this study differ in terms of the following three criteria. First, they come from two types of data source; Naver news of high grammatical correctness and Naver shopping's cosmetics product reviews of low grammatical correctness. Second, they are distinguished in the degree of data preprocessing, namely, only splitting sentences or up to additional spelling and spacing corrections after sentence separation. Third, they vary concerning the form of input fed into a word vector model; whether the morphemes themselves are entered into a word vector model or with their POS tags attached. The morpheme vectors further vary depending on the consideration range of POS tags, the minimum frequency of morphemes included, and the random initialization range. All morpheme vectors are derived through CBOW(Continuous Bag-Of-Words) model with the context window 5 and the vector dimension 300. It seems that utilizing the same domain text even with a lower degree of grammatical correctness, performing spelling and spacing corrections as well as sentence splitting, and incorporating morphemes of any POS tags including incomprehensible category lead to the better classification accuracy. The POS tag attachment, which is devised for the high proportion of homonyms in Korean, and the minimum frequency standard for the morpheme to be included seem not to have any definite influence on the classification accuracy.

• Journal of Christian Education in Korea
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• v.68
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• pp.77-112
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• 2021

This study is based on the research of the first year, which is the National Research Foundation of Korea's R&D subject for middle-grade researchers. In this study, the practical curriculum development of the education for love - an according to the psychoanalytic perspectives of F. Dolto(1908-1988) - is suggested as follows. The first is 'the reconstruction of the directions of curriculum and its specific aims in accordance with such directions.' The reconstruction of the directions of curriculum aims at leading our future generation to live as a subject of desire through the mutual-communication of love. The second is 'the reconstruction of the tasks of curriculum and its specific contents in accordance with such tasks.' The reconstruction of the tasks of curriculum pursuit to help our future generation through the converting the education for love into the paradigm of desire of Agape to live as a subject of desire forming a whole personality and practicing the desire of Agape in daily life. as a source of desire. According to these aims, the reconstruction of directions of curriculum are presented as following: firstly, 'curriculum for the mutual-communication between subjects of love' and secondly, 'curriculum for the subject of desire'. The reconstruction of tasks of curriculum are like these: firstly, 'converting the education for love into the paradigm of desire of Agape', and secondly, 'forming a whole personality through the education for love'. Thus, with respect to two specific aims in accordance with the reconstruction of directions are suggested like these: Firstly, 'constructing a subject as a speaking existence' and secondly, 'realizing the subject as the autonomous source of desire'. In the two specific contents in accordance with the reconstruction of tasks are presented as following: Firstly, 'realizing the truth of the desire of Agape'.' Secondly, 'practicing the desire of Agape in daily life.' The third is 'the reconstruction of curriculum by life cycle' are suggested. They include the fetal life, infants and preschool children life, and childhood life. In further study, it is required to contain adolescent period. It will be useful to help them to recover their self-esteem with the experience of true love, especially, out-of-school young generation overcome negative perspectives and prejudice in the society, and challenges to their dreams and future through proper utilization of the study outcome. The outcome of this study, which presented practical curriculum development of the education for love based on the understanding of psychoanalytic 'desire of subject' can be used as basic teaching materials for our future generations. Furthermore, the results can be used as a resource for educating ministers and lay leaders in the religious world to build capabilities to heal their inner side as well as the society that is tainted with various forms of conflict. These include general conflicts, anger, pleasure and addiction, depression and suicide, violence and murder, etc. The study outcome can contribute to the prevention of antisocial incidents against humanity that have recently been occurring in our free-semester system implemented in all middle schools across the country to be operated effectively. For example, it is possible to provide the study results as lecture and teaching materials for 'character camp' (self-examination and self-esteem improvement training) and 'family healing camp' (solution of a communication gap between family members and love communication training), which help students participate in field trip activities and career exploration activities voluntarily, independently, and creatively. Ultimately, it can visibly present the convergent research performance by providing the study outcome as preliminary data for the development of lecture videos and materials including infant care and preschool education, parental education, family consultation education, and holistic healing education. Support from the religious world, including the central government and local governments, are urgently required in order for such educational possibilities to be fulfilled both in the society and the fields of church education and to be actively linked to follow-up studies.