• Journal of Internet Computing and Services
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• v.24 no.6
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• pp.119-125
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• 2023

Through the Ukraine-Russia war, the military importance of drones is being reassessed, and North Korea has completed actual verification through a drone provocation towards South Korea at 2022. Furthermore, North Korea is actively integrating artificial intelligence (AI) technology into drones, highlighting the increasing threat posed by drones. In response, the Republic of Korea military has established Drone Operations Command(DOC) and implemented various drone defense systems. However, there is a concern that the efforts to enhance capabilities are disproportionately focused on striking systems, making it challenging to effectively counter swarm drone attacks. Particularly, Air Force bases located adjacent to urban areas face significant limitations in the use of traditional air defense weapons due to concerns about civilian casualties. Therefore, this study proposes a new passive air defense method that aims at disrupting the object detection capabilities of AI models to enhance the survivability of friendly aircraft against the threat posed by AI based swarm drones. Using laser-based adversarial examples, the study seeks to degrade the recognition accuracy of object recognition AI installed on enemy drones. Experimental results using synthetic images and precision-reduced models confirmed that the proposed method decreased the recognition accuracy of object recognition AI, which was initially approximately 95%, to around 0-15% after the application of the proposed method, thereby validating the effectiveness of the proposed method.

• Information Systems Review
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• v.25 no.1
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• pp.233-255
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• 2023

The development of information technology(IT) has brought so-called "online experience" to satisfy our daily needs. The market for online experiences grew more during the COVID-19 pandemic. Therefore, this study attempted to analyze how the features of online experience services affect customer satisfaction by crawling structured and unstructured data from the online experience web site newly launched by Airbnb after COVID-19. As a result of the analysis, it was found that the structured data generated by service users on a C2C online sharing platform had a positive effect on the satisfaction of other users. In addition, unstructured text data such as experience introductions and host introductions generated by service providers turned out to have different subjectivity scores depending on the purpose of its text. It was confirmed that the subjective host introduction and the objective experience introduction affect customer satisfaction positively. The results of this study are to provide various implications to stakeholders of the online sharing economy platform and researchers interested in online experience knowledge management.

• Korean Journal of Occupational Health Nursing
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• v.6 no.2
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• pp.144-155
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• 1997

In December 1990, Occupational Safety and Health Law was amended to reinforce employer's responsibilities on employees' health and safety. Among the amended law it was important to expand the role of an occupational health nurse to the role of an occupational health manager. An occupational health manager should take charge of coordinating periodic health examination and environmental hazard evaluation, providing primary care, monitoring employees' health status, giving the workplace walk-through, selecting safe protection equipment, providing health information, counseling and health education, independently. This position of occupational health nurse is equivalent to the role of doctors or occupational hygienists. In 1991, government made a master plan to prevent occupational disease and injury. Under the plan, Korea Industrial Nursing Association (KINA) was established in 1994 with the purpose of improving health services and upgrading career opportunities for members. Therefore, this study was designed to analyze the transition of occupational health nursing education with the changes of law and policy in Korea between 1991 and 1996. In details, it was to analyze the rate of school providing occupational health nursing practice based lecture, lecture hours, lecture contents in undergraduate curriculum, program contents of graduate school, kinds of continuing education, etc. For this purpose, we conducted survey two times. In February 1991, baseline study was conducted with all nursing programs in Korea (19 BSN programs and 43 nursing departments of junior college). From April to May in 1996, the second survey was conducted with all nursing programs (38 BSN programs and 69 junior colleges). The first response rate was 66.1% and the second was 40.6%. Structured questionnaires were mailed to the deans or the community health nursing faculties. In the case of graduate school, telephone survey was conducted with 10 school of public health or environmental health area. Data from the yearbook of Industrial Safety Training Institute (ISTI), the history of Korea Industrial Health Association, and the journals of KINA were also included in the analysis. As the results, we found that there were remarkable improvement in undergraduate and graduate programs, obligatory as well as voluntary continuing education in terms of occupational health nursing expertise between 1991 and 1996. 1) The number of school providing occupational health nursing practice-based lecture was increased with the rate from 7.3% to 25.6%. The rate of school giving over 15 class-hours was increased from 33.3% to 46.6%. 2) Content areas were composed of introduction of occupational health, occupational epidemiology, industrial hygiene, occupational disease and injury, law and policy, health education, concept of occupational health nursing, role of occupational health nurse, occupational health nursing process, etc. Of content areas, occupational health nursing process was more emphasized with the increased rate from 43.9% to 88.4%. 3) In the case of graduate school, occupational health programs were increased from 4 to 10. One of them has developed occupational health nursing program as an independent course since 1991. 4) The law increased educational hours from 28 hours to 36 hours for introductory course at the time of appointment, and from 14 hours to 24 hours every 2 years for continuing education. Course contents were Occupational safety and health law, introduction of occupational health, health education methodology, planning and evaluation, periodic health exam, occupational disease care, primary care, emergency care, management, industrial environment evaluation, etc. In 1996, Korea Industrial Nursing Association has begun to provide continuing education after Industrial Safety Training Institute. 5) Various educational programs in voluntary base were developed such as monthly seminar, CE articles, annual academic symposium, etc. It was shown that changes of law and policy led rapid growth of occupational health nursing education in various levels. From this trend, it is expected that occupational health nurse expertise be continuously to be enhanced in Korea. Legal and political supports should proceed for the development of occupational health nursing in early stage.

• Journal of Intelligence and Information Systems
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• v.22 no.3
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• pp.23-43
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• 2016

As a result of the growth of Internet data and the rapid development of Internet technology, "big data" analysis has gained prominence as a major approach for evaluating and mining enormous data for various purposes. Especially, in recent years, people tend to share their experiences related to their leisure activities while also reviewing others' inputs concerning their activities. Therefore, by referring to others' leisure activity-related experiences, they are able to gather information that might guarantee them better leisure activities in the future. This phenomenon has appeared throughout many aspects of leisure activities such as movies, traveling, accommodation, and dining. Apart from blogs and social networking sites, many other websites provide a wealth of information related to leisure activities. Most of these websites provide information of each product in various formats depending on different purposes and perspectives. Generally, most of the websites provide the average ratings and detailed reviews of users who actually used products/services, and these ratings and reviews can actually support the decision of potential customers in purchasing the same products/services. However, the existing websites offering information on leisure activities only provide the rating and review based on one stage of a set of evaluation criteria. Therefore, to identify the main issue for each evaluation criterion as well as the characteristics of specific elements comprising each criterion, users have to read a large number of reviews. In particular, as most of the users search for the characteristics of the detailed elements for one or more specific evaluation criteria based on their priorities, they must spend a great deal of time and effort to obtain the desired information by reading more reviews and understanding the contents of such reviews. Although some websites break down the evaluation criteria and direct the user to input their reviews according to different levels of criteria, there exist excessive amounts of input sections that make the whole process inconvenient for the users. Further, problems may arise if a user does not follow the instructions for the input sections or fill in the wrong input sections. Finally, treating the evaluation criteria breakdown as a realistic alternative is difficult, because identifying all the detailed criteria for each evaluation criterion is a challenging task. For example, if a review about a certain hotel has been written, people tend to only write one-stage reviews for various components such as accessibility, rooms, services, or food. These might be the reviews for most frequently asked questions, such as distance between the nearest subway station or condition of the bathroom, but they still lack detailed information for these questions. In addition, in case a breakdown of the evaluation criteria was provided along with various input sections, the user might only fill in the evaluation criterion for accessibility or fill in the wrong information such as information regarding rooms in the evaluation criteria for accessibility. Thus, the reliability of the segmented review will be greatly reduced. In this study, we propose an approach to overcome the limitations of the existing leisure activity information websites, namely, (1) the reliability of reviews for each evaluation criteria and (2) the difficulty of identifying the detailed contents that make up the evaluation criteria. In our proposed methodology, we first identify the review content and construct the lexicon for each evaluation criterion by using the terms that are frequently used for each criterion. Next, the sentences in the review documents containing the terms in the constructed lexicon are decomposed into review units, which are then reconstructed by using the evaluation criteria. Finally, the issues of the constructed review units by evaluation criteria are derived and the summary results are provided. Apart from the derived issues, the review units are also provided. Therefore, this approach aims to help users save on time and effort, because they will only be reading the relevant information they need for each evaluation criterion rather than go through the entire text of review. Our proposed methodology is based on the topic modeling, which is being actively used in text analysis. The review is decomposed into sentence units rather than considering the whole review as a document unit. After being decomposed into individual review units, the review units are reorganized according to each evaluation criterion and then used in the subsequent analysis. This work largely differs from the existing topic modeling-based studies. In this paper, we collected 423 reviews from hotel information websites and decomposed these reviews into 4,860 review units. We then reorganized the review units according to six different evaluation criteria. By applying these review units in our methodology, the analysis results can be introduced, and the utility of proposed methodology can be demonstrated.

• Asia pacific journal of information systems
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• v.22 no.3
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• pp.99-124
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• 2012

Our society has long been talking about necessity for innovation. Since companies in particular need to carry out business innovation in their overall processes, they have attempted to apply many innovation factors on sites and become to pay more attention to their innovation. In order to achieve this goal, companies has applied various information technologies (IT) on sites as a means of innovation, and consequently IT have been greatly developed. It is natural for the field of IT to have faced another revolution which is called cloud computing, which is expected to result in innovative changes in software application via the Internet, data storing, the use of devices, and their operations. As a vehicle of innovation, cloud computing is expected to lead the changes and advancement of our society and the business world. Although many scholars have researched on a variety of topics regarding the innovation via IT, few studies have dealt with the issue of could computing as IT. Thus, the purpose of this paper is to set the variables of innovation attributes based on the previous articles as the characteristic variables and clarify how these variables affect "Performance Expectancy" of companies and the intention of using cloud computing. The result from the analysis of data collected in this study is as follows. The study utilized a research model developed on the innovation diffusion theory to identify influences on the adaptation and spreading IT for cloud computing services. Second, this study summarized the characteristics of cloud computing services as a new concept that introduces innovation at its early stage of adaptation for companies. Third, a theoretical model is provided that relates to the future innovation by suggesting variables for innovation characteristics to adopt cloud computing services. Finally, this study identified the factors affecting expectation and the intention to use the cloud computing service for the companies that consider adopting the cloud computing service. As the parameter and dependent variable respectively, the study deploys the independent variables that are aligned with the characteristics of the cloud computing services based on the innovation diffusion model, and utilizes the expectation for performance and Intention to Use based on the UTAUT theory. Independent variables for the research model include Relative Advantage, Complexity, Compatibility, Cost Saving, Trialability, and Observability. In addition, 'Acceptance for Adaptation' is applied as an adjustment variable to verify the influences on the expected performances from the cloud computing service. The validity of the research model was secured by performing factor analysis and reliability analysis. After confirmatory factor analysis is conducted using AMOS 7.0, the 20 hypotheses are verified through the analysis of the structural equation model, accepting 12 hypotheses among 20. For example, Relative Advantage turned out to have the positive effect both on Individual Performance and on Strategic Performance from the verification of hypothesis, while it showed meaningful correlation to affect Intention to Use directly. This indicates that many articles on the diffusion related Relative Advantage as the most important factor to predict the rate to accept innovation. From the viewpoint of the influence on Performance Expectancy among Compatibility and Cost Saving, Compatibility has the positive effect on both Individual Performance and on Strategic Performance, while it showed meaningful correlation with Intention to Use. However, the topic of the cloud computing service has become a strategic issue for adoption in companies, Cost Saving turns out to affect Individual Performance without a significant influence on Intention to Use. This indicates that companies expect practical performances such as time and cost saving and financial improvements through the adoption of the cloud computing service in the environment of the budget squeezing from the global economic crisis from 2008. Likewise, this positively affects the strategic performance in companies. In terms of effects, Trialability is proved to give no effects on Performance Expectancy. This indicates that the participants of the survey are willing to afford the risk from the high uncertainty caused by innovation, because they positively pursue information about new ideas as innovators and early adopter. In addition, they believe it is unnecessary to test the cloud computing service before the adoption, because there are various types of the cloud computing service. However, Observability positively affected both Individual Performance and Strategic Performance. It also showed meaningful correlation with Intention to Use. From the analysis of the direct effects on Intention to Use by innovative characteristics for the cloud computing service except the parameters, the innovative characteristics for the cloud computing service showed the positive influence on Relative Advantage, Compatibility and Observability while Complexity, Cost saving and the likelihood for the attempt did not affect Intention to Use. While the practical verification that was believed to be the most important factor on Performance Expectancy by characteristics for cloud computing service, Relative Advantage, Compatibility and Observability showed significant correlation with the various causes and effect analysis. Cost Saving showed a significant relation with Strategic Performance in companies, which indicates that the cost to build and operate IT is the burden of the management. Thus, the cloud computing service reflected the expectation as an alternative to reduce the investment and operational cost for IT infrastructure due to the recent economic crisis. The cloud computing service is not pervasive in the business world, but it is rapidly spreading all over the world, because of its inherited merits and benefits. Moreover, results of this research regarding the diffusion innovation are more or less different from those of the existing articles. This seems to be caused by the fact that the cloud computing service has a strong innovative factor that results in a new paradigm shift while most IT that are based on the theory of innovation diffusion are limited to companies and organizations. In addition, the participants in this study are believed to play an important role as innovators and early adapters to introduce the cloud computing service and to have competency to afford higher uncertainty for innovation. In conclusion, the introduction of the cloud computing service is a critical issue in the business world.

• Asian Oncology Nursing
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• v.1 no.2
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• pp.191-203
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• 2001

The health of a nurse is very important because her mental and physical health can influence toward nursing patients directly, Especially, Cancer patients are growing annually. Also, terminal cancer patients' nursing and dead place are increasingly using hospital and the period of nursing for cancer patients are increasing. Nursing for cancer patients are different with acute disease. Therefore, I analysed comparing nurses' health working in cancer and general ward so that nurses working at cancer ward could be developed as a professional nurse, and I wanted to establish the foundation of nursing administration and reasonable manpower management to supply good quality of nursing to patients. In my research, I selected 117 nurses working in cancer ward and 134 nurses working in general word to analyse the stress rate and nurse's health comparing nurses working in general ward and cancer ward. The survey was conducted of nurses working in cancer ward nurses in 2 university hospitals, nurses working in a cancer hospital, and general ward nurses working in 3 public hospital. Also, the data was collected from Sep. 13, 2001 to Sep. 28, 2001. As health measuring tool, I used Cornell Medical Index(CMI) which are developed to fit Koreans by Ko Ungrin and Park Hang-bas (1980) using Cornell Medical Services which were designed by Weiser, Brosman, Mittelman, Wechler, Wolff in Cornell University(1945). As working stress measuring tool, I used Questionaries which were designed by Kim Mae-ja and Ku Mi-ok(1984) and then developed by Bae In-sook(1996). For managing the data, I used frequency, percentage, ${\chi}^2$ verification, t-test, and F-test (ANOVA). And in the case of significant data(p<.05). I did Duncan's test for post verification. The mutual relation between health condition and working stress rate have been conducted using Pearson's Correlation Coefficient. Followings are the results of my research. 1. Two groups showed significant differency at age after testing homogeneous character between two groups (${\chi}^2$ =9.919, p=.007). 2. Comparing two group's health condition, cancer ward(average 19.35${\pm}$18.34) were higher than general ward(14.42${\pm}$10.59) and showed statistical significant differency(p=.009). And, comparing two group's mental condition, cancer ward(9.00${\pm}$9.79) were higher than general ward(7.13${\pm}$6.35) and statistically no differency. 3. After comparing two group's working stress rate, the rate of cancer ward nurse's working stress(3.36${\pm}$.50) is higher than general ward nurse (3.32${\pm}$.48). There are no significant differency. However, in the detailed verification test, there were significant differency at inappropriate compensation (t=3.254, p=.001) and medication issue (t=2.170, p=.031). 4. After comparing health condition at general points, physical health condition showed significant differency at age(p=.020), the number of children (p=.015), religion (p=.015), position(p=.005), career(p=.008), working satisfaction(p=.003), activity after office hour(p=.045); and mental health condition showed significant differency at position(p=.010), career (p=.017), working satisfaction (p=.003). 5. After comparing the working stress rate according to general points, there were significant differency at working satisfaction (F=5.285, p=.006), predicted nursing(F=3.822, p=.023). 6. At the relation of health condition and working stress rate between two groups. physical and mental condition showed significant relation with working stress rate. i.e, if a nurse's health condition is not good, she are feeling much more stress than others. After considering all the factors in my research, I found that the health condition and stress rate of cancer ward nurses is much higher than general ward nurses. Considering that cancer ward nurses is necessary to care for increasing cancer patients with mental and physical nursing, the less stress for cancer ward nurses is very important to develop nursing quality and working efficiency by keeping good health condition, specializing cancer ward nurses. Therefore, we need following studies to find the factors which are effecting to cancer ward nurses' health and specialization. Also, we need to improve managing working condition to decrease working stress by improving working condition.

• Journal of Internet Computing and Services
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• v.22 no.2
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• pp.109-121
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• 2021

As the global COVID-19 pandemic is prolonged, the Corona Blue phenomenon, combined with COVID-19 and blue, is intensifying. The purpose of this study is to analyze the current trend of Corona Blue in consideration of the possibility of increasing mental illness and the need for countermeasures, especially after COVID-19. This study tried to find out the relationship between stress and leisure activities before and after COVID-19 by using Corona Blue news article analysis through the topic modeling method, and questionnaire find out the help of stress and leisure activities. This study was compared and analyzed using two research methods. First, a total of 363 news articles were analyzed through topic modeling based on newspaper articles from January 2020, when COVID- 19 was upgraded to the "border" stage, until September, where the social distancing stage was strengthened to stage 2.5 in Korea. As a result of the study, a total of 28 topics were extracted, and similar topics were grouped into 7 groups: mental-demic, generational spread, causes of depression acceleration, increased fatigue, attitude to coping with long-term wars, changes in consumption, and efforts to overcome depression. Second, the SPSS statistical program was used to analyze the level of stress change according to leisure activities before/after COVID-19 and the main help according to leisure activities. As a result of the study, it was confirmed that the average difference in stress reduction according to participation in leisure activities before COVID-19 was larger than after COVID-19. Also, leisure activities were found to be effective in stress relief even after COVID-19. In addition, if the main help from leisure activities before COVID-19 was the meaning of relaxation and recharging through physical and social activities. After COVID-19, psychological roles such as mood swings through nature, outdoor activities, or intellectual activities were found to play a large part. As such, in this study, it was confirmed that understanding the current status of Corona Blue and coping with leisure in extreme stress situations has a positive effect. It is expected that this research can serve as a basis for preparing realistic and desirable leisure policies and countermeasures to overcome Corona Blue.

• Journal of agricultural medicine and community health
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• v.40 no.3
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• pp.126-136
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• 2015

Objectives: This study was performed to investigate the effects of a health education program for the aged on knowledge about the warning signs and symptoms of acute myocardial infarction and stroke. Methods: Data from 337 elderly people (159 participated and 178 non-participated) at senior centers in Jeju-si were collected by 1 to 1 interview from January to March 2012, one year after the education program provided. Two stages of study were performed: Cross-sectional, case-control study on the level of knowledge about the warning signs and symptoms; and multivariate logistic regression to fine out predictors of optimal awareness. Results: No significant discrepancy of knowledge level between case and control group was found. The knowledge level as high as a surge was shown in both groups one year later. A surge of knowledge had been shown after the education provided in one month. The factors affecting the optimal level of knowledge were education (Odds ratio 3.01; Confidence Interval 1.72-5.26; P-value <0.001) and 7 days of watching TV news per week (2.97; 1.68-5.23; P<0.001). However, participation in the health education was not significant (1.60; 0.98-2.61; P=0.059). Conclusions: The effects of a targeted program in high-risk groups for cardio-cerebrovascular disease are only guaranteed in the enhancement by a population-based mass-media education campaign.

• Journal of Intelligence and Information Systems
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• v.28 no.1
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• pp.69-88
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• 2022

One of the characteristics of South Korea's economic structure is that it is highly dependent on exports. Thus, many businesses are closely related to the global economy and diplomatic situation. In addition, small and medium-sized enterprises(SMEs) specialized in exporting are struggling due to the spread of COVID-19. Therefore, this study aimed to develop a model to forecast exports for next year to support SMEs' export strategy and decision making. Also, this study proposed a strategy to recommend promising export countries of each item based on the forecasting model. We analyzed important variables used in previous studies such as country-specific, item-specific, and macro-economic variables and collected those variables to train our prediction model. Next, through the exploratory data analysis(EDA) it was found that exports, which is a target variable, have a highly skewed distribution. To deal with this issue and improve predictive performance, we suggest a separated learning method. In a separated learning method, the whole dataset is divided into homogeneous subgroups and a prediction algorithm is applied to each group. Thus, characteristics of each group can be more precisely trained using different input variables and algorithms. In this study, we divided the dataset into five subgroups based on the exports to decrease skewness of the target variable. After the separation, we found that each group has different characteristics in countries and goods. For example, In Group 1, most of the exporting countries are developing countries and the majority of exporting goods are low value products such as glass and prints. On the other hand, major exporting countries of South Korea such as China, USA, and Vietnam are included in Group 4 and Group 5 and most exporting goods in these groups are high value products. Then we used LightGBM(LGBM) and Exponential Moving Average(EMA) for prediction. Considering the characteristics of each group, models were built using LGBM for Group 1 to 4 and EMA for Group 5. To evaluate the performance of the model, we compare different model structures and algorithms. As a result, it was found that the separated learning model had best performance compared to other models. After the model was built, we also provided variable importance of each group using SHAP-value to add explainability of our model. Based on the prediction model, we proposed a second-stage recommendation strategy for potential export countries. In the first phase, BCG matrix was used to find Star and Question Mark markets that are expected to grow rapidly. In the second phase, we calculated scores for each country and recommendations were made according to ranking. Using this recommendation framework, potential export countries were selected and information about those countries for each item was presented. There are several implications of this study. First of all, most of the preceding studies have conducted research on the specific situation or country. However, this study use various variables and develops a machine learning model for a wide range of countries and items. Second, as to our knowledge, it is the first attempt to adopt a separated learning method for exports prediction. By separating the dataset into 5 homogeneous subgroups, we could enhance the predictive performance of the model. Also, more detailed explanation of models by group is provided using SHAP values. Lastly, this study has several practical implications. There are some platforms which serve trade information including KOTRA, but most of them are based on past data. Therefore, it is not easy for companies to predict future trends. By utilizing the model and recommendation strategy in this research, trade related services in each platform can be improved so that companies including SMEs can fully utilize the service when making strategies and decisions for exports.

• Journal of Intelligence and Information Systems
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• v.22 no.4
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• pp.193-215
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• 2016

In recent years, the proliferation of diverse social networking services has led users to use many mediums simultaneously depending on their individual purpose and taste. Besides, while collecting information about particular themes, they usually employ various mediums such as social networking services, Internet news, and blogs. However, in terms of management, each document circulated through diverse mediums is placed in different categories on the basis of each source's policy and standards, hindering any attempt to conduct research on a specific category across different kinds of sources. For example, documents containing content on "Application for a foreign travel" can be classified into "Information Technology," "Travel," or "Life and Culture" according to the peculiar standard of each source. Likewise, with different viewpoints of definition and levels of specification for each source, similar categories can be named and structured differently in accordance with each source. To overcome these limitations, this study proposes a plan for conducting category mapping between different sources with various mediums while maintaining the existing category system of the medium as it is. Specifically, by re-classifying individual documents from the viewpoint of diverse sources and storing the result of such a classification as extra attributes, this study proposes a logical layer by which users can search for a specific document from multiple heterogeneous sources with different category names as if they belong to the same source. Besides, by collecting 6,000 articles of news from two Internet news portals, experiments were conducted to compare accuracy among sources, supervised learning and semi-supervised learning, and homogeneous and heterogeneous learning data. It is particularly interesting that in some categories, classifying accuracy of semi-supervised learning using heterogeneous learning data proved to be higher than that of supervised learning and semi-supervised learning, which used homogeneous learning data. This study has the following significances. First, it proposes a logical plan for establishing a system to integrate and manage all the heterogeneous mediums in different classifying systems while maintaining the existing physical classifying system as it is. This study's results particularly exhibit very different classifying accuracies in accordance with the heterogeneity of learning data; this is expected to spur further studies for enhancing the performance of the proposed methodology through the analysis of characteristics by category. In addition, with an increasing demand for search, collection, and analysis of documents from diverse mediums, the scope of the Internet search is not restricted to one medium. However, since each medium has a different categorical structure and name, it is actually very difficult to search for a specific category insofar as encompassing heterogeneous mediums. The proposed methodology is also significant for presenting a plan that enquires into all the documents regarding the standards of the relevant sites' categorical classification when the users select the desired site, while maintaining the existing site's characteristics and structure as it is. This study's proposed methodology needs to be further complemented in the following aspects. First, though only an indirect comparison and evaluation was made on the performance of this proposed methodology, future studies would need to conduct more direct tests on its accuracy. That is, after re-classifying documents of the object source on the basis of the categorical system of the existing source, the extent to which the classification was accurate needs to be verified through evaluation by actual users. In addition, the accuracy in classification needs to be increased by making the methodology more sophisticated. Furthermore, an understanding is required that the characteristics of some categories that showed a rather higher classifying accuracy of heterogeneous semi-supervised learning than that of supervised learning might assist in obtaining heterogeneous documents from diverse mediums and seeking plans that enhance the accuracy of document classification through its usage.