• 한국체육학회지인문사회과학편
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• v.55 no.1
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• pp.221-233
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• 2016

The purpose of this study was to prove a development and initial validation of the korean version of coach-athlete relationship maintenance scale that originated from the work of Rhind & Jowett(2012) in pro baseball. The items were then administered to 132 Participants(29 coaches and 103 athletes) completed the questionnaires of the coach-athlete relationship maintenance in First preliminary investigation. Maximum likelihood estimate was used to identify the latent underlying structure. In order to verify the validity of Korean version of coach-athlete relationship maintenance was administered to an independent sample of 273 coaches and athletes. Pro baseball coach-athlete relationship maintenance is consisted of six factors(25 items) with conflict management, motivational, preventative, openness/assurance, support, and social network. SPSS18.0 and AMOS16.0 were used to analyze the exploratory factor analysis, confirmatory factory analysis and internal consistency, test-retest with bootstrapping using of the data in this study. The results of the pro baseball coach-athlete relationship maintenance scale had six factors with 25 items, and each six factor was positively correlated. Overall, this study verified pro baseball coach-athlete relationship maintenance questionnaire. Thus, suggest that path of comparing the differences between the first division and farm team by using the test of the structural model invariance across the groups.

• Korean Journal of Hospice Care
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• v.1 no.1
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• pp.46-69
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• 2001

Hospice Care is the best way to care for terminally ill patients and their family members. However most of them can not receive the appropriate hospice service because the Korean health delivery system is mainly be focussed on acutly ill patients. This study was carried out to clarify the situation of hospice in Korea and to develop a hospice care delivery system model which is appropriate in the Korean context. The theoretical framework of this study that hospice care delivery system is composed of hospice resources with personnel, facilities, etc., government and non-government hospice organization, hospice finances, hospice management and hospice delivery, was taken from the Health Delivery System of WHO(1984). Data was obtained through data analysis of litreature, interview, questionairs, visiting and Delphi Technique, from October 1998 to April 1999 involving 56 hospices, 1 hospice research center, 3 non-government hospice organizations, 20 experts who have had hospice experience for more than 3 years(mean is 9 years and 5 months) and officials or members of 3 non-government hospice organizations. There are 61 hospices in Korea. Even though hospice personnel have tried to study and to provide qualified hospice serices, there is nor any formal hospice linkage or network in Korea. This is the result of this survey made to clarify the situation of Korean hospice. Results of the study by Delphi Technique were as follows: 1.Hospice Resources: Key hospice personnel were found to be hospice coordinator, doctor, nurse, clergy, social worker, volunteers. Necessary qualifications for all personnel was that they conditions were resulted as have good health, receive hospice education and have communication skills. Education for hospice personnel is divided into (i)basic training and (ii)special education, e.g. palliative medicine course for hospice specialist or palliative care course in master degree for hospice nurse specialist. Hospice facilities could be developed by adding a living room, a space for family members, a prayer room, a church, an interview room, a kitchen, a dining room, a bath facility, a hall for music, art or work therapy, volunteers' room, garden, etc. to hospital facilities. 2.Hospice Organization: Whilst there are three non-government hospice organizations active at present, in the near future an hospice officer in the Health&Welfare Ministry plus a government Hospice body are necessary. However a non-government council to further integrate hospice development is also strongly recommended. 3.Hospice Finances: A New insurance standards, I.e. the charge for hospice care services, public information and tax reduction for donations were found suggested as methods to rise the hospice budget. 4.Hospice Management: Two divisions of hospice management/care were considered to be necessary in future. The role of the hospice officer in the Health & Welfare Ministry would be quality control of hospice teams and facilities involved/associated with hospice insurance standards. New non-government integrating councils role supporting the development of hospice care, not insurance covered. 5.Hospice delivery: Linkage&networking between hospice facilities and first, second, third level medical institutions are needed in order to provide varied and continous hospice care. Hospice Acts need to be established within the limits of medical law with regards to standards for professional staff members, educational programs, etc. The results of this study could be utilizes towards the development to two hospice care delivery system models, A and B. Model A is based on the hospital, especially the hospice unit, because in this setting is more easily available the new medical insurance for hospice care. Therefore a hospice team is organized in the hospital and may operate in the hospice unit and in the home hospice care service. After Model A is set up and operating, Model B will be the next stage, in which medical insurance cover will be extended to home hospice care service. This model(B) is also based on the hospital, but the focus of the hospital hospice unit will be moved to home hospice care which is connected by local physicians, national public health centers, community parties as like churches or volunteer groups. Model B will contribute to the care of terminally ill patients and their family members and also assist hospital administrators in cost-effectiveness.

• Journal of the International Relations & Interdisciplinary Education
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• v.3 no.1
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• pp.1-28
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• 2023

This study was conducted to examine the quantitative trend of domestic studies in invention gifted education, identify the intrinsic meaning and connection attributes in these research analysis, and provide basic data to explore future development plans. To this end, 97 domestic academic papers were finally selected as "Invention Gifted Education" by the Korea Research and Information Service (RISS), technical statistical analysis was conducted with SPSS on publication year, author composition, researcher's affiliation and location area, and published journal. The trend, which had been on the rise since 2007, confirmed by academic papers on gifted education in invention, peaked at the time of the 3rd comprehensive plan for gifted education and has since declined again. As a result of technical statistical analysis of the author's characteristics, half of the papers were jointly published, followed by a number of independent authors. The papers published alone were identified as belonging to universities, research institutes, elementary schools, and middle schools, and the cooperative papers were many studies cooperated with young researchers and professional researchers, and only one collaborative study was conducted between young researchers. When looking at the regions and journals in which the Invention Gifted Education thesis was published, it was concentrated in some regions or journals, and the deviation was very large. As a result of language network analysis using academic paper keywords, creativity and programs were identified as meaningful keywords that showed top appearance, and the keyword pair with high co-appearance was invention gifted-creativity. The keyword of connection-centeredness at the top served as an intermediary for creativity, problem-solving, development, and company to expand to other research topics, and served as a research topic that could be expanded to various topics. In the case of mediation-centeredness, creativity, programs, and effects showed high mediation-centeredness, indicating that it is an important keyword that plays a role in mediating or mediating other keywords. Through these research results, national policy measures need to be prepared for the development of gifted education, and the need to create an invention ecological culture that can enhance teachers' expertise while increasing social responsibility for gifted education.

• Journal of Intelligence and Information Systems
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• v.20 no.2
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• pp.39-58
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• 2014

As the importance of big data and related technologies continues to grow in the industry, it has become highlighted to visualize results of processing and analyzing big data. Visualization of data delivers people effectiveness and clarity for understanding the result of analyzing. By the way, visualization has a role as the GUI (Graphical User Interface) that supports communications between people and analysis systems. Usually to make development and maintenance easier, these GUI parts should be loosely coupled from the parts of processing and analyzing data. And also to implement a loosely coupled architecture, it is necessary to adopt design patterns such as MVC (Model-View-Controller) which is designed for minimizing coupling between UI part and data processing part. On the other hand, big data can be classified as structured data and unstructured data. The visualization of structured data is relatively easy to unstructured data. For all that, as it has been spread out that the people utilize and analyze unstructured data, they usually develop the visualization system only for each project to overcome the limitation traditional visualization system for structured data. Furthermore, for text data which covers a huge part of unstructured data, visualization of data is more difficult. It results from the complexity of technology for analyzing text data as like linguistic analysis, text mining, social network analysis, and so on. And also those technologies are not standardized. This situation makes it more difficult to reuse the visualization system of a project to other projects. We assume that the reason is lack of commonality design of visualization system considering to expanse it to other system. In our research, we suggest a common information model for visualizing text data and propose a comprehensive and reusable framework, TexVizu, for visualizing text data. At first, we survey representative researches in text visualization era. And also we identify common elements for text visualization and common patterns among various cases of its. And then we review and analyze elements and patterns with three different viewpoints as structural viewpoint, interactive viewpoint, and semantic viewpoint. And then we design an integrated model of text data which represent elements for visualization. The structural viewpoint is for identifying structural element from various text documents as like title, author, body, and so on. The interactive viewpoint is for identifying the types of relations and interactions between text documents as like post, comment, reply and so on. The semantic viewpoint is for identifying semantic elements which extracted from analyzing text data linguistically and are represented as tags for classifying types of entity as like people, place or location, time, event and so on. After then we extract and choose common requirements for visualizing text data. The requirements are categorized as four types which are structure information, content information, relation information, trend information. Each type of requirements comprised with required visualization techniques, data and goal (what to know). These requirements are common and key requirement for design a framework which keep that a visualization system are loosely coupled from data processing or analyzing system. Finally we designed a common text visualization framework, TexVizu which is reusable and expansible for various visualization projects by collaborating with various Text Data Loader and Analytical Text Data Visualizer via common interfaces as like ITextDataLoader and IATDProvider. And also TexVisu is comprised with Analytical Text Data Model, Analytical Text Data Storage and Analytical Text Data Controller. In this framework, external components are the specifications of required interfaces for collaborating with this framework. As an experiment, we also adopt this framework into two text visualization systems as like a social opinion mining system and an online news analysis system.

• Journal of Intelligence and Information Systems
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• v.21 no.3
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• pp.101-116
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• 2015

Recently, due to the development of smart devices and social media, vast amounts of information with the various forms were accumulated. Particularly, considerable research efforts are being directed towards analyzing unstructured big data to resolve various social problems. Accordingly, focus of data-driven decision-making is being moved from structured data analysis to unstructured one. Also, in the field of recommendation system, which is the typical area of data-driven decision-making, the need of using unstructured data has been steadily increased to improve system performance. Approaches to improve the performance of recommendation systems can be found in two aspects- improving algorithms and acquiring useful data with high quality. Traditionally, most efforts to improve the performance of recommendation system were made by the former approach, while the latter approach has not attracted much attention relatively. In this sense, efforts to utilize unstructured data from variable sources are very timely and necessary. Particularly, as the interests of users are directly connected with their needs, identifying the interests of the user through unstructured big data analysis can be a crew for improving performance of recommendation systems. In this sense, this study proposes the methodology of improving recommendation system by measuring interests of the user. Specially, this study proposes the method to quantify interests of the user by analyzing user's internet usage patterns, and to predict user's repurchase based upon the discovered preferences. There are two important modules in this study. The first module predicts repurchase probability of each category through analyzing users' purchase history. We include the first module to our research scope for comparing the accuracy of traditional purchase-based prediction model to our new model presented in the second module. This procedure extracts purchase history of users. The core part of our methodology is in the second module. This module extracts users' interests by analyzing news articles the users have read. The second module constructs a correspondence matrix between topics and news articles by performing topic modeling on real world news articles. And then, the module analyzes users' news access patterns and then constructs a correspondence matrix between articles and users. After that, by merging the results of the previous processes in the second module, we can obtain a correspondence matrix between users and topics. This matrix describes users' interests in a structured manner. Finally, by using the matrix, the second module builds a model for predicting repurchase probability of each category. In this paper, we also provide experimental results of our performance evaluation. The outline of data used our experiments is as follows. We acquired web transaction data of 5,000 panels from a company that is specialized to analyzing ranks of internet sites. At first we extracted 15,000 URLs of news articles published from July 2012 to June 2013 from the original data and we crawled main contents of the news articles. After that we selected 2,615 users who have read at least one of the extracted news articles. Among the 2,615 users, we discovered that the number of target users who purchase at least one items from our target shopping mall 'G' is 359. In the experiments, we analyzed purchase history and news access records of the 359 internet users. From the performance evaluation, we found that our prediction model using both users' interests and purchase history outperforms a prediction model using only users' purchase history from a view point of misclassification ratio. In detail, our model outperformed the traditional one in appliance, beauty, computer, culture, digital, fashion, and sports categories when artificial neural network based models were used. Similarly, our model outperformed the traditional one in beauty, computer, digital, fashion, food, and furniture categories when decision tree based models were used although the improvement is very small.

• Journal of Intelligence and Information Systems
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• v.25 no.2
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• pp.57-75
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• 2019

In this paper, we conducted a study focusing on the innovation direction of the documentary model on the Internet of Things industry, which is the most actively industrialized among the core technologies of the 4th Industrial Revolution. Policy, economic, social, and technical issues were derived using PEST analysis for global trend analysis. It also presented future prospects for the Internet of Things industry of ICT-related global research institutes such as Gartner and International Data Corporation. Global research institutes predicted that competition in network technologies will be an issue for industrial Internet (IIoST) and IoT (Internet of Things) based on infrastructure and platforms. As a result of the PEST analysis, developed countries are pushing policies to respond to the fourth industrial revolution through cooperation of private (business/ research institutes) led by the government. It was also in the process of expanding related R&D budgets and establishing related policies in South Korea. On the economic side, the growth tax of the related industries (based on the aggregate value of the market) and the performance of the entity were reviewed. The growth of industries related to the fourth industrial revolution in advanced countries overseas was found to be faster than other industries, while in Korea, the growth of the "technical hardware and equipment" and "communication service" sectors was relatively low among industries related to the fourth industrial revolution. On the social side, it is expected to cause enormous ripple effects across society, largely due to changes in technology and industrial structure, changes in employment structure, changes in job volume, etc. On the technical side, changes were taking place in each industry, representing the health and medical sectors and manufacturing sectors, which were rapidly changing as they merged with the technology of the Fourth Industrial Revolution. In this paper, various management methodologies for innovation of existing business model were reviewed to cope with rapidly changing industrial environment due to the fourth industrial revolution. In addition, four criteria were established to select a management model to cope with the new business environment: 'Applicability', 'Agility', 'Diversity' and 'Connectivity'. The expert survey results in an AHP analysis showing that Business Model Canvas is best suited for business model innovation methodology. The results showed very high importance, 42.5 percent in terms of "Applicability", 48.1 percent in terms of "Agility", 47.6 percent in terms of "diversity" and 42.9 percent in terms of "connectivity." Thus, it was selected as a model that could be diversely applied according to the industrial ecology and paradigm shift. Business Model Canvas is a relatively recent management strategy that identifies the value of a business model through a nine-block approach as a methodology for business model innovation. It identifies the value of a business model through nine block approaches and covers the four key areas of business: customer, order, infrastructure, and business feasibility analysis. In the paper, the expansion and application direction of the nine blocks were presented from the perspective of the IoT company (ICT). In conclusion, the discussion of which Business Model Canvas models will be applied in the ICT convergence industry is described. Based on the nine blocks, if appropriate applications are carried out to suit the characteristics of the target company, various applications are possible, such as integration and removal of five blocks, seven blocks and so on, and segmentation of blocks that fit the characteristics. Future research needs to develop customized business innovation methodologies for Internet of Things companies, or those that are performing Internet-based services. In addition, in this study, the Business Model Canvas model was derived from expert opinion as a useful tool for innovation. For the expansion and demonstration of the research, a study on the usability of presenting detailed implementation strategies, such as various model application cases and application models for actual companies, is needed.

• Journal of the Korean Institute of Landscape Architecture
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• v.50 no.1
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• pp.33-52
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• 2022

The History and Culture Park and the Lee Kun-hee Donation Hall will be built in Songhyeon-dong, Seoul. Political games from the Joseon Dynasty to the present greatly influenced the historicity of Songhyeon-dong. However, place analysis was limited to changes in landowners and land uses rather than a historical context. Therefore, this study analyzed the context in which the placeness of Songhyeon-dong changed according to the emergence of cultural hegemony using the perspective of modern cultural geography and comparative history. As a result of the analysis, cultural hegemony in historical transitions, such as Sinocentrism, maritime expansion, civil revolutions, imperialism, nationalism, popular art, and neoliberalism, was found to have created new intellectuals in Bukchon, including Songhyeon-dong, and influenced social systems and spatial policies. In this social relations, the placeness of Songhyeon-dong changed as follows. First, the founding forces of Joseon created pine forests as Bibo Forests to invocate the permanence of the dynasty. In the late Joseon dynasty, it was an era of maritime expansion, and as Joseon's yeonhaeng increased, a garden for the Gyeonghwasejok, who enjoyed the culture of the Qing dynasty, was built. Although pine forests and gardens disappeared due to the development of housing complexes as the population soared during the Japanese colonial era, Cha Gyeong's landscape aesthetics, which harmonized artificial gardens and external nature, are worth reinterpreting in modern times. Second, the wave of modernization created a new school in Bukchon and a boarding house in Songhyeon-dong owned by a pro-Japanese faction. Angukdongcheon-gil, next to Songhyeon-dong, was where thinkers who promoted civil revolution and national self-determination exchanged ideas. Songhyeon-dong, the largest boarding house, served as a residence for students to participate in the March 1st Movement and was the cradle of the resulting culture of student movements. The appearance of the old road is preserved, so it is a significant part of the regeneration of walking in the historic city center, connecting Gwanghwamun-Bukchon-Insadong -Donhwamunro. Third, from the cultural rule of the Government General of Joseon to the Military Government, Songhyeon-dong acted as a passage to western culture with the Joseon Siksan Bank's cultural housing and staff accommodations at the U.S. Embassy. Ancient and contemporary art coexisted in the surrounding area, so the modern and contemporary art market was formed. The Lee Kun-hee Donation Hall is expected to form a cultural belt for citizens with the gallery, Bukchon Hanok Village, the Craft Museum, and the Modern Museum of Art. Discourses and challenges are needed to recreate the place in harmony with the forests, gardens, the street of citizens' birth, history and culture park, the art museum, and the surrounding walking network.

• Journal of Nutrition and Health
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• v.56 no.5
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• pp.573-588
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• 2023

Purpose: This study aimed to examine social networking service (SNS) use and recommended information utilization (SURU) according to the food-related lifestyles (FRLs) of consumers and analyze how the interaction between the FRL and SURU affects the practice of eating alone and visiting restaurants. Methods: Data on 4,624 adults in their 20s to 50s were collected from the 2021 Consumer Behavior Survey for Food. Statistical methods included factor analysis, K-means cluster analysis, the complex samples general linear model, the complex samples Rao-Scott χ² test, and the general linear model. Results: The following three factors were extracted from the FRL data: Convenience pursuit, rational consumption pursuit, and gastronomy pursuit, and the subjects were classified into three groups, namely the rational consumption, convenient gastronomy, and smart gourmet groups. An examination of the difference in SURU according to the FRL showed that the smart gourmet group had the highest score. The result of analyzing the effects of the FRL and SURU on eating alone revealed that both the main effect and the interaction effect were significant (p < 0.01, p < 0.001). The higher the SURU, the higher the frequency of eating alone in the convenience pursuit, and gastronomy pursuit groups. The main and interaction effects of the FRL and SURU on the frequency of eating out were also significant (p < 0.01, p < 0.001). In all the FRL groups, the higher the SURU level, the higher the frequency of visiting restaurants. Specifically, the two groups with convenience and gastronomic tendencies showed a steeper increase. Conclusion: This study provides important basic data for research on consumer behavior related to food SNS, market segmentation of restaurant consumers, and development of marketing strategies using SNS in the future.

• Journal of Science Education
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• v.39 no.3
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• pp.358-375
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• 2015

The purposes of this study were to investigate the value, necessity and legitimacy of STEAM Education and to propose practical approaching methods for STEAM Education to be applicable in Korea through a variety of literature review, case studies and collecting suggestions from domestic and international educational experts. The research questions are as follows: (1) To investigate the perception, understanding and recognitions of domestic and foreign professionals in STEAM education. (2) To analyze policy implications for an improvement in STEAM. The following aspects of STEAM were found to be challenges in our current STEAM policy after analyzing multiple questionnaires with the professionals and case studies including their experiences, understanding, supports and directions of the policy from the governments. The results indicate that (1) there was a lack of precise and conceptual understanding of STEAM in respect to experience. Training sessions for teachers in this field to help transform their perception is necessary. Development of practical programs with an easy access is also required. It is important to get the aims of related educational activities recognized by the professionals and established standards for an evaluation. The experts perceived that a theme-based learning is the most preferred and effective approaching method and the programs that develop creative thinking and learning applicable to practice are required to promote. (2) The results indicate that there was a lack of programs and inducements for supporting outstanding STEAM educators. It is shown that making an appropriate environment for STEAM education takes the first priority before training numbers of teachers unilaterally, thus securing enough budget seems critical. The professionals also emphasize on developing specialized teaching materials that include diverse inter-related subjects such as science technology, engineering, arts and humanities and social science with diverse viewpoints and advanced technology. This work requires a STEAM network for teachers to link up and share their materials, documents and experiences. It is necessary to get corporations, universities, and research centers participated in the network. (3) With respect to direction, it is necessary to propose policy that makes STEAM education ordinary and more practical in the present education system. The professionals have recommended training sessions that help develop creative thinking and amalgamative problem-solving techniques. They require reducing the workload of teachers and changing teachers' perspectives towards STEAM. They further urge a tight cooperation between departments of the government related with STEAM.

• Journal of Intelligence and Information Systems
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• v.24 no.3
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• pp.21-44
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• 2018

In recent years, the rapid development of internet technology and the popularization of smart devices have resulted in massive amounts of text data. Those text data were produced and distributed through various media platforms such as World Wide Web, Internet news feeds, microblog, and social media. However, this enormous amount of easily obtained information is lack of organization. Therefore, this problem has raised the interest of many researchers in order to manage this huge amount of information. Further, this problem also required professionals that are capable of classifying relevant information and hence text classification is introduced. Text classification is a challenging task in modern data analysis, which it needs to assign a text document into one or more predefined categories or classes. In text classification field, there are different kinds of techniques available such as K-Nearest Neighbor, Naïve Bayes Algorithm, Support Vector Machine, Decision Tree, and Artificial Neural Network. However, while dealing with huge amount of text data, model performance and accuracy becomes a challenge. According to the type of words used in the corpus and type of features created for classification, the performance of a text classification model can be varied. Most of the attempts are been made based on proposing a new algorithm or modifying an existing algorithm. This kind of research can be said already reached their certain limitations for further improvements. In this study, aside from proposing a new algorithm or modifying the algorithm, we focus on searching a way to modify the use of data. It is widely known that classifier performance is influenced by the quality of training data upon which this classifier is built. The real world datasets in most of the time contain noise, or in other words noisy data, these can actually affect the decision made by the classifiers built from these data. In this study, we consider that the data from different domains, which is heterogeneous data might have the characteristics of noise which can be utilized in the classification process. In order to build the classifier, machine learning algorithm is performed based on the assumption that the characteristics of training data and target data are the same or very similar to each other. However, in the case of unstructured data such as text, the features are determined according to the vocabularies included in the document. If the viewpoints of the learning data and target data are different, the features may be appearing different between these two data. In this study, we attempt to improve the classification accuracy by strengthening the robustness of the document classifier through artificially injecting the noise into the process of constructing the document classifier. With data coming from various kind of sources, these data are likely formatted differently. These cause difficulties for traditional machine learning algorithms because they are not developed to recognize different type of data representation at one time and to put them together in same generalization. Therefore, in order to utilize heterogeneous data in the learning process of document classifier, we apply semi-supervised learning in our study. However, unlabeled data might have the possibility to degrade the performance of the document classifier. Therefore, we further proposed a method called Rule Selection-Based Ensemble Semi-Supervised Learning Algorithm (RSESLA) to select only the documents that contributing to the accuracy improvement of the classifier. RSESLA creates multiple views by manipulating the features using different types of classification models and different types of heterogeneous data. The most confident classification rules will be selected and applied for the final decision making. In this paper, three different types of real-world data sources were used, which are news, twitter and blogs.