• Korean Journal of Remote Sensing
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• v.39 no.5_1
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• pp.481-493
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• 2023

In high-density urban areas, the urban heat island effect increases urban temperatures, leading to negative impacts such as worsened air pollution, increased cooling energy consumption, and increased greenhouse gas emissions. In urban environments where it is difficult to secure additional green spaces, rooftop greening is an efficient greenhouse gas reduction strategy. In this study, we not only analyzed the current status of the urban heat island effect but also utilized high-resolution satellite data and spatial information to estimate the available rooftop greening area within the study area. We evaluated the mitigation effect of the urban heat island phenomenon and carbon sequestration capacity through temperature predictions resulting from rooftop greening. To achieve this, we utilized WorldView-2 satellite data to classify land cover in the urban heat island areas of Busan city. We developed a prediction model for temperature changes before and after rooftop greening using machine learning techniques. To assess the degree of urban heat island mitigation due to changes in rooftop greening areas, we constructed a temperature change prediction model with temperature as the dependent variable using the random forest technique. In this process, we built a multiple regression model to derive high-resolution land surface temperatures for training data using Google Earth Engine, combining Landsat-8 and Sentinel-2 satellite data. Additionally, we evaluated carbon sequestration based on rooftop greening areas using a carbon absorption capacity per plant. The results of this study suggest that the developed satellite-based urban heat island assessment and temperature change prediction technology using Random Forest models can be applied to urban heat island-vulnerable areas with potential for expansion.

• Journal of Intelligence and Information Systems
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• v.18 no.3
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• pp.185-202
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• 2012

.Since the value of information has been realized in the information society, the usage and collection of information has become important. A facial expression that contains thousands of information as an artistic painting can be described in thousands of words. Followed by the idea, there has recently been a number of attempts to provide customers and companies with an intelligent service, which enables the perception of human emotions through one's facial expressions. For example, MIT Media Lab, the leading organization in this research area, has developed the human emotion prediction model, and has applied their studies to the commercial business. In the academic area, a number of the conventional methods such as Multiple Regression Analysis (MRA) or Artificial Neural Networks (ANN) have been applied to predict human emotion in prior studies. However, MRA is generally criticized because of its low prediction accuracy. This is inevitable since MRA can only explain the linear relationship between the dependent variables and the independent variable. To mitigate the limitations of MRA, some studies like Jung and Kim (2012) have used ANN as the alternative, and they reported that ANN generated more accurate prediction than the statistical methods like MRA. However, it has also been criticized due to over fitting and the difficulty of the network design (e.g. setting the number of the layers and the number of the nodes in the hidden layers). Under this background, we propose a novel model using Support Vector Regression (SVR) in order to increase the prediction accuracy. SVR is an extensive version of Support Vector Machine (SVM) designated to solve the regression problems. The model produced by SVR only depends on a subset of the training data, because the cost function for building the model ignores any training data that is close (within a threshold ${\varepsilon}$) to the model prediction. Using SVR, we tried to build a model that can measure the level of arousal and valence from the facial features. To validate the usefulness of the proposed model, we collected the data of facial reactions when providing appropriate visual stimulating contents, and extracted the features from the data. Next, the steps of the preprocessing were taken to choose statistically significant variables. In total, 297 cases were used for the experiment. As the comparative models, we also applied MRA and ANN to the same data set. For SVR, we adopted '${\varepsilon}$-insensitive loss function', and 'grid search' technique to find the optimal values of the parameters like C, d, ${\sigma}^2$, and ${\varepsilon}$. In the case of ANN, we adopted a standard three-layer backpropagation network, which has a single hidden layer. The learning rate and momentum rate of ANN were set to 10%, and we used sigmoid function as the transfer function of hidden and output nodes. We performed the experiments repeatedly by varying the number of nodes in the hidden layer to n/2, n, 3n/2, and 2n, where n is the number of the input variables. The stopping condition for ANN was set to 50,000 learning events. And, we used MAE (Mean Absolute Error) as the measure for performance comparison. From the experiment, we found that SVR achieved the highest prediction accuracy for the hold-out data set compared to MRA and ANN. Regardless of the target variables (the level of arousal, or the level of positive / negative valence), SVR showed the best performance for the hold-out data set. ANN also outperformed MRA, however, it showed the considerably lower prediction accuracy than SVR for both target variables. The findings of our research are expected to be useful to the researchers or practitioners who are willing to build the models for recognizing human emotions.

• Journal of Intelligence and Information Systems
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• v.25 no.1
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• pp.63-83
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• 2019

Investors prefer to look for trading points based on the graph shown in the chart rather than complex analysis, such as corporate intrinsic value analysis and technical auxiliary index analysis. However, the pattern analysis technique is difficult and computerized less than the needs of users. In recent years, there have been many cases of studying stock price patterns using various machine learning techniques including neural networks in the field of artificial intelligence(AI). In particular, the development of IT technology has made it easier to analyze a huge number of chart data to find patterns that can predict stock prices. Although short-term forecasting power of prices has increased in terms of performance so far, long-term forecasting power is limited and is used in short-term trading rather than long-term investment. Other studies have focused on mechanically and accurately identifying patterns that were not recognized by past technology, but it can be vulnerable in practical areas because it is a separate matter whether the patterns found are suitable for trading. When they find a meaningful pattern, they find a point that matches the pattern. They then measure their performance after n days, assuming that they have bought at that point in time. Since this approach is to calculate virtual revenues, there can be many disparities with reality. The existing research method tries to find a pattern with stock price prediction power, but this study proposes to define the patterns first and to trade when the pattern with high success probability appears. The M & W wave pattern published by Merrill(1980) is simple because we can distinguish it by five turning points. Despite the report that some patterns have price predictability, there were no performance reports used in the actual market. The simplicity of a pattern consisting of five turning points has the advantage of reducing the cost of increasing pattern recognition accuracy. In this study, 16 patterns of up conversion and 16 patterns of down conversion are reclassified into ten groups so that they can be easily implemented by the system. Only one pattern with high success rate per group is selected for trading. Patterns that had a high probability of success in the past are likely to succeed in the future. So we trade when such a pattern occurs. It is a real situation because it is measured assuming that both the buy and sell have been executed. We tested three ways to calculate the turning point. The first method, the minimum change rate zig-zag method, removes price movements below a certain percentage and calculates the vertex. In the second method, high-low line zig-zag, the high price that meets the n-day high price line is calculated at the peak price, and the low price that meets the n-day low price line is calculated at the valley price. In the third method, the swing wave method, the high price in the center higher than n high prices on the left and right is calculated as the peak price. If the central low price is lower than the n low price on the left and right, it is calculated as valley price. The swing wave method was superior to the other methods in the test results. It is interpreted that the transaction after checking the completion of the pattern is more effective than the transaction in the unfinished state of the pattern. Genetic algorithms(GA) were the most suitable solution, although it was virtually impossible to find patterns with high success rates because the number of cases was too large in this simulation. We also performed the simulation using the Walk-forward Analysis(WFA) method, which tests the test section and the application section separately. So we were able to respond appropriately to market changes. In this study, we optimize the stock portfolio because there is a risk of over-optimized if we implement the variable optimality for each individual stock. Therefore, we selected the number of constituent stocks as 20 to increase the effect of diversified investment while avoiding optimization. We tested the KOSPI market by dividing it into six categories. In the results, the portfolio of small cap stock was the most successful and the high vol stock portfolio was the second best. This shows that patterns need to have some price volatility in order for patterns to be shaped, but volatility is not the best.

• Korean Journal of Environment and Ecology
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• v.30 no.6
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• pp.1047-1056
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• 2016

This study aims to provide managerial implications for provincial parks through an analysis on visitors' characteristics and motivational factors. The information was collected by surveying 290 visitors. The survey questionnaire consisted of questions regarding visitors' socioeconomic characteristics, characteristics of their travel behavior, visitors' motivation to visit the park, and the degree of satisfaction derived from visiting the park. Results show that most respondents appeared not to collect any information on the park prior to their visit. It was also seen that most visitors do not visit other tourist sites nearby, and are not aware of the Gochang UNESCO biosphere, which indicates that Gochang-gun, which is responsible for park management, needs to make more efforts to promote the park. A factor analysis on the visitors' motivation to visit the park extracted three factors to visit the Seonunsan Provincial Park: 'to hike,' 'to experience and observe nature,' i.e., nature learning field trip and camping, and 'to build and nurture bonding with family and friends.' To examine the effect of these various motivational factors had on the visitors' satisfaction level upon visiting the park, we conducted a multiple regression analysis with the three extracted factors to visit the park and the respondents' socioeconomic characteristics as independent variables, and the degree of recommendation of visiting the park as a dependent variable. The result shows found that, of the three travel factors, only the 'hiking' factor statistically significantly affected the degree of recommendation of visiting the park. This result suggests that the Seonunsan Provincial Park only satisfied hikers and failed to meet the demands for nature experience and observation. It is therefore suggested that the park managers develop new experience-based tourism programs, such as guided tours conducted by professional eco-interpreters.

• Asia pacific journal of information systems
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• v.17 no.4
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• pp.61-95
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• 2007

Small-and-medium sized enterprises(SMEs) represent quite a large proportion of the industry as a whole in terms of the number of enterprises or employees. However researches on information system so far have focused on large companies, probably because SMEs were not so active in introducing information systems as larger enterprises. SMEs are now increasingly bringing in information systems such as ERP(Enterprise Resource Planning Systems) and some of the companies already entered the stage of ongoing use. Accordingly, researches should deal with the use of information systems by SME s operating under different conditions from large companies. This study examined factors and mechanism inducing faithful appropriation of information systems, in particular integrative systems such as ERP, in view of individuals` active feedback-seeking behavior. There are three factors expected to affect end users` feedback-seeking behavior for faithful appropriation of information systems. They are management support, peer IT champ support, and IT staff support. The main focus of the study is on how these factors affect feedback-seeking behavior and whether the feedback-seeking behavior plays the role of mediator for realizing faithful appropriation of information systems by end users. To examine the research model and the hypotheses, this study employed an empirical method based on a field survey. The survey used measurements mostly employed and verified by previous researches, while some of the measurements had gone through minor modifications for the purpose of the study. The survey respondents are individual employees of SMEs that have been using ERP for one year or longer. To prevent common method bias, Task-Technology Fit items used as the control variable were made to be answered by different respondents. In total, 127 pairs of valid questionnaires were collected and used for the analysis. The PLS(Partial Least Squares) approach to structural equation modeling(PLS-Graph v.3.0) was used as our data analysis strategy because of its ability to model both formative and reflective latent constructs under small-and medium-size samples. The analysis shows Reliability, Construct Validity and Discriminant Validity are appropriate. The path analysis results are as follows; first, the more there is peer IT champ support, the more the end user is likely to show feedback-seeking behavior(path-coefficient=0.230, t=2.28, p<0.05). In other words, if colleagues proficient in information system use recognize the importance of their help, pass on what they have found to be an effective way of using the system or correct others' misuse, ordinary end users will be able to seek feedback on the faithfulness of their appropriation of information system without hesitation, because they know the convenience of getting help. Second, management support encourages ordinary end users to seek more feedback(path-coefficient=0.271, t=3.06, p<0.01) by affecting the end users' perceived value of feedback(path-coefficient=0.401, t=6.01, p<0.01). Management support is far more influential than other factors that when the management of an SME well understands the benefit of ERP, promotes its faithful appropriation and pays attention to employees' satisfaction with the system, employees will make deliberate efforts for faithful appropriation of the system. However, the third factor, IT staff support was found not to be conducive to feedback-seeking behavior from end users(path-coefficient=0.174, t=1.83). This is partly attributable to the fundamental reason that there is little support for end users from IT staff in SMEs. Even when IT staff provides support, end users may find it less important than that from coworkers more familiar with the end users' job. Meanwhile, the more end users seek feedback and attempt to find ways of faithful appropriation of information systems, the more likely the users will be able to deploy the system according to the purpose the system was originally meant for(path-coefficient=0.35, t=2.88, p<0.01). Finally, the mediation effect analysis confirmed the mediation effect of feedback-seeking behavior. By confirming the mediation effect of feedback-seeking behavior, this study draws attention to the importance of feedback-seeking behavior that has long been overlooked in research about information system use. This study also explores the factors that promote feedback-seeking behavior which in result could affect end user`s faithful appropriation of information systems. In addition, this study provides insight about which inducements or resources SMEs should offer to promote individual users' feedback-seeking behavior when formal and sufficient support from IT staff or an outside information system provider is hardly expected. As the study results show, under the business environment of SMEs, help from skilled colleagues and the management plays a critical role. Therefore, SMEs should seriously consider how to utilize skilled peer information system users, while the management should pay keen attention to end users and support them to make the most of information systems.

• 대한공업교육학회지
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• v.39 no.2
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• pp.101-121
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• 2014

The study aims to develop the NCS based vocational curriculum model for the practical and creative human resources. For effectiveness of the study, the study consists of literature studies of both domestic and international, contents analysis, case study, expert(9samples) consultation and review, and in-depth-interview of the three advisory members. The validity of the developed model is analyzed through mean, standard deviation and contents validity ratio(CVR). The main results of the model development in our study are as follow. First, our NCS based vocational curriculum model for the practical and creative human resources is developed with the analyses of NCS development manuals, training standard utilization and training curriculum organization manuals, NCS learning module development manual and case studies, NCS research report, NCS based curriculum pilot development resources directed toward the high schools and vocational school as well as the domestic and international literature study on career training model like NCS. Second, based on the findings of our analysis in combination with the findings from the consultations with the expert and advisory committee, total 19 sub-factors of each step and domain are extracted. The sub-factors of domain in step 1 are the competency unit, definition of competency unit, competency unit element, performance criteria, range of variable, guide of assessment, key competency; in step 2, they are subject title, subject objectives, chapter title, chapter objectives, pedagogical methods, assessment methods and basic job competence; and in step 2, they are NCS based subject matrix table, NCS based subject profile, NCS based job training curriculum table, NCS based subjects organization flowchart, NCS based job training operation plan. Third, the final model including step 3 NCS based subject profile are developed in association with the linked organizational sub-factors of step 1 and step 2. Forth, the validity tests for the final model by the step and domain yield the mean 4.67, CVR value 1.00, indicating the superior validity. Also, the means of each sub-factors are all over 4.33 with the CVR value 1.00, indicating the high validity as well. The means of the associated organizations within the model are also over 4.33 with the CVR value of 1.00. Standard deviations are all .50 or lower which are small. Fifth, based on the validity test results and the in-depth-interview of the expert and advisory committee, the model is adjusted complemented to establish final model of the NCS based vocational curriculum for the practical and creative human resources.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.7 no.2
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• pp.195-205
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• 2012

This study examines runaway youths at risk in a youths' shelter who are preparing for an independent life and both the facilitating and adverse factors to personal characteristics and independence of runaway youths at risk with the aim to grasp their recognition of independence and level of desire for it and find out necessary factors for a successful independence in multidimensional perspectives including the economic independence, educational independence, psychological independence, and social independence for their sound growth. This will provide the basis for desirable interventions for youths runaway youths at risk to prepare for an independent life. The findings of this study on the factors that affect the preparation for an independent life are as follows: First, as a result of analyzing the effect of micro-systematic factors on the preparation for an independent life, it turned out that problem-solving abilities and self-efficacy had influence on the preparation for a career Second, as a result of analyzing the effect of mesoscopic-systematic variables on the preparation for an independent life, it turned out that the preparation for a career were affected by whether to participate in independence preparation programs and institutional supports, and that career maturity of runaway youths at risk were affected only by the relationship with teachers and participation in independence preparation programs. Third, as a result of analyzing the effect of macro systematic variables on the preparation for an independent life, it turned out that the preparation for a career were affected by participation of the local community and service network, and that participation of the local community was an predictor variable that would affect a career maturity of runaway youths at risk. Fourth, as a result of analyzing ecological systematic variables that might affect the preparation for a career, it turned out that intervening variables and macro systematic variables had the most powerful influence on the preparation for a career among runaway youths at risk. It is necessary, therefore, to provide education programs organized by policies in order to develop problem-solving abilities and vocational capabilities so that runaway youths at risk, and to train and appoint more professional teachers at shelters. Programs for independence preparation need to be developed actively and practically in consideration of the characteristics of shelters, and the network with the local community for support also need to be established in utilization of the human resources and service programs of the community. With the understanding of leaving home of runaway youths at risk as the previous stage of an independence, there should be a housing support for their stable settlement in the perspective of housing welfare until become adults. In addition, there should be education specialized programs for occupation and careers to train runaway youths at risk as professionals including such areas as health, mentality, learning, and voluntary work for their sound growth.

• Journal of the Korean Society of School Health
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• v.12 no.2
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• pp.207-215
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• 1999

The objectives of this study are to explain the use of media materials in school health education with other related factors in elementary, middle, and high schools in Korea. The data were collected by questionnaires from June to September in 1998. The number of subjects were 294 school nurses. The PC-SAS program was used for statistical analysis such as percent distribution, chi-squared test, spearman correlation test, and logistic regression. The use of media materials in health education has become extremely common. Unfortunately, much of the early materials were of poor production quality, reflected low levels of interest, and generally did little to enhance health education programming. A recent trend in media materials is a move away from the fact filled production to a more affective, process-oriented approach. There is an obvious need for health educators to use high-quality, polished productions in order to counteract the same levels of quality used by commercial agencies that often promote "unhealthy" lifestyles. Health educators need to be aware of the advantages and disadvantages of the various forms of media. Selecting media materials should be based on more than cost, availability, and personal preference. Selection should be based on the goal of achieving behavioral objectives formulated before the review process begins. The decision to use no media materials rather than something of dubious quality usually be the right decision. Poor-quality, outdated, or boring materials will usually have a detrimental effect on the presentation. Media materials should be viewed as vehicles to enhance learning, not products that will stand in isolation. Process of materials is an essential part of the educational process. The major results were as follows : 1. The elementary schools used the materials more frequently. But the production rate of media materials was not enough. The budget was too small for a wide use of media materials in school health education. These findings suggest that all schools have to increase the budget of health education programs. 2. Computers offer an incredibly diverse set of possibilities for use in health education, ranging from complicated statistical analysis to elementary-school-level health education games. But the use rate of this material was not high. The development of related software is essential. Health educators would be well advised to develop a basic operating knowledge of media equipment. 3. In this study, the most effective materials were films in elementary school and videotapes in middle and high school. Film tends to be a more emotive medium than videotape. The difficulties of media selection involved the small amount of extant educational materials. Media selection is a multifaceted process and should be based on a combination of sound principles. 4. The review of material use following student levels showed that the more the contents were various, the more the use rate was high. 5. Health education videotapes and overhead projectors proved the most plentiful and widest media tools. The information depicted was more likely to be current. As a means to display both text and graphic information, this instructional medium has proven to be both effective and enduring. 6. An analysis of how effective the quality of school nurse and school use of media materials shows a result that is not complete (p=0.1113). But, the budget of health education is a significant variable. The increase of the budget therefore is essential to effective use of media materials. From these results it is recommended that various media materials be developed and be wide used.

• The Journal of Korean Academic Society of Nursing Education
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• v.3
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• pp.78-98
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• 1997

Health education, as the most fundamental concept for national health promotion, alms for developing the self-care ability of the general public. High school days are regarded as the period when most important physical, mental and social developments occur, and most health-related behaviors are formed. School health education is one of the major learning resources influencing health potential in the home and community as well as for the individual student. High school health education in Korea has a fundamental systemic flaw in that health-related subjects are divided and taught under various subjects areas at school. In order to achieve the goal of school health education, it is essential to make a systematic assessment of the learner's concerns connected with his health and life, and the factors affecting them. So far, most of the research projects that had been carried out for improving high school health education were limited in their concerns to a particular aspect of health. Even though some had been done in view of comprehensive school health education, they failed to Include a health assessment of the learner. Therefore, in this study the high school students' concerns related to health and life were investigated in the first place on the basis of the PRECEDE model, developed by Green and others for the purpose of a comprehensive diagnostic research on high school health education. This study was done in two steps : one was the basic study for developing research instrument and the other was the main one. The former was conducted at five high schools in Seoul and Cheongju for 2 months-beginning in March, 1996. The students were asked to respond to questions related to their health and lives in unstructured open-ended question forms. On the basis of analysis of the basic study, the diagnostic instruments for the quality of life, health problems, health behavior and educational factors were constructed to be used for the collection of data for main study. An expert panel and the pilot study were used to improve content validity and reliability of the instruments. The reliability of the instruments was measured at between .7697 and .9611 by the Cronbach $\alpha$. The data for this study were collected from the sample consisted of the junior and senior classes of twenty general and vocational high schools in Seoul and Cheongju for two months period beginning in July, 1996. In analyzing the data, both t-test and $X^2$-test were done by using SAS-$PC^+$ Program to compare data between the sexes of the high school students and the types of high school. A canonical correlation analysis was carried out to determine the relationships among the diagnostic variables, and a multivariate multiple regression analysis was conducted by using LISREL 8.03 to ascertain the influences of variables on the high school students' health and quality of life. The results were as follows : 1) The findings of the hypothesis tests (1) The canonical correlation between the educational diagnosis variables and behavioral, epidemiological, social diagnosis variables was .7221, which was significant at the level of p<.001. (2) The canonical correlation between the educational diagnosis variables and the behavior variables was .6851, which also was significant (p<.001). (3) The canonical correlation between the behavioral diagnosis variables and the epidemiological variables was 4295, which was significant (p<.001). (4) The canonical correlation between the epidemiological diagnosis variables and the social variables was .6005, which was also significant (p<.001). Therefore, the relationship between each diagnosis variable suggested by the PRECEDE model had been experimentally proven to be valid, supporting the conceptual framework of the study as appropriate for assessing the multi-dimensional factors affecting high school students' health and quality of life. Health behavior self-efficacy, the level of parents' interest and knowledge of health, and the level of the perception of school health education, all of which are the educational diagnostic variables, are the most influential variables in students' health and quality of life. In particular, health behavior self-efficacy, a causative factor, was one of the main influential variables in their health and quality of life. Other diagnostic variables suggested in the steps of the PRECEDE model were found to have reciprocal relations rather than a unidirectional causative relationship. The significance of this research is that it has diagnosed the needs of high school health education by the learner-centered assessment of variety of factors related to the health and the life of the students. This research findings suggest an integrated system of school health education to be contrived to enhance the effectiveness of the education by strengthening the influential factors such as self-efficacy to improve the health and quality of the lives of high school students.

• Asia pacific journal of information systems
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• v.19 no.2
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• pp.139-155
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• 2009

For the last few decades, many studies have tried to explore and unveil venture companies' success factors and unique features in order to identify the sources of such companies' competitive advantages over their rivals. Such venture companies have shown tendency to give high returns for investors generally making the best use of information technology. For this reason, many venture companies are keen on attracting avid investors' attention. Investors generally make their investment decisions by carefully examining the evaluation criteria of the alternatives. To them, credit rating information provided by international rating agencies, such as Standard and Poor's, Moody's and Fitch is crucial source as to such pivotal concerns as companies stability, growth, and risk status. But these types of information are generated only for the companies issuing corporate bonds, not venture companies. Therefore, this study proposes a method for evaluating venture businesses by presenting our recent empirical results using financial data of Korean venture companies listed on KOSDAQ in Korea exchange. In addition, this paper used multi-class SVM for the prediction of DEA-based efficiency rating for venture businesses, which was derived from our proposed method. Our approach sheds light on ways to locate efficient companies generating high level of profits. Above all, in determining effective ways to evaluate a venture firm's efficiency, it is important to understand the major contributing factors of such efficiency. Therefore, this paper is constructed on the basis of following two ideas to classify which companies are more efficient venture companies: i) making DEA based multi-class rating for sample companies and ii) developing multi-class SVM-based efficiency prediction model for classifying all companies. First, the Data Envelopment Analysis(DEA) is a non-parametric multiple input-output efficiency technique that measures the relative efficiency of decision making units(DMUs) using a linear programming based model. It is non-parametric because it requires no assumption on the shape or parameters of the underlying production function. DEA has been already widely applied for evaluating the relative efficiency of DMUs. Recently, a number of DEA based studies have evaluated the efficiency of various types of companies, such as internet companies and venture companies. It has been also applied to corporate credit ratings. In this study we utilized DEA for sorting venture companies by efficiency based ratings. The Support Vector Machine(SVM), on the other hand, is a popular technique for solving data classification problems. In this paper, we employed SVM to classify the efficiency ratings in IT venture companies according to the results of DEA. The SVM method was first developed by Vapnik (1995). As one of many machine learning techniques, SVM is based on a statistical theory. Thus far, the method has shown good performances especially in generalizing capacity in classification tasks, resulting in numerous applications in many areas of business, SVM is basically the algorithm that finds the maximum margin hyperplane, which is the maximum separation between classes. According to this method, support vectors are the closest to the maximum margin hyperplane. If it is impossible to classify, we can use the kernel function. In the case of nonlinear class boundaries, we can transform the inputs into a high-dimensional feature space, This is the original input space and is mapped into a high-dimensional dot-product space. Many studies applied SVM to the prediction of bankruptcy, the forecast a financial time series, and the problem of estimating credit rating, In this study we employed SVM for developing data mining-based efficiency prediction model. We used the Gaussian radial function as a kernel function of SVM. In multi-class SVM, we adopted one-against-one approach between binary classification method and two all-together methods, proposed by Weston and Watkins(1999) and Crammer and Singer(2000), respectively. In this research, we used corporate information of 154 companies listed on KOSDAQ market in Korea exchange. We obtained companies' financial information of 2005 from the KIS(Korea Information Service, Inc.). Using this data, we made multi-class rating with DEA efficiency and built multi-class prediction model based data mining. Among three manners of multi-classification, the hit ratio of the Weston and Watkins method is the best in the test data set. In multi classification problems as efficiency ratings of venture business, it is very useful for investors to know the class with errors, one class difference, when it is difficult to find out the accurate class in the actual market. So we presented accuracy results within 1-class errors, and the Weston and Watkins method showed 85.7% accuracy in our test samples. We conclude that the DEA based multi-class approach in venture business generates more information than the binary classification problem, notwithstanding its efficiency level. We believe this model can help investors in decision making as it provides a reliably tool to evaluate venture companies in the financial domain. For the future research, we perceive the need to enhance such areas as the variable selection process, the parameter selection of kernel function, the generalization, and the sample size of multi-class.