• Asia pacific journal of information systems
• /
• v.25 no.3
• /
• pp.579-596
• /
• 2015

Many studies have focused on the prediction of corporate credit rating using various data mining techniques. One of the most frequently used algorithms is support vector machines (SVM), and recently, novel techniques such as SVM+ and SVM+MTL have emerged. This paper intends to show the applicability of such new techniques to multi-classification and corporate credit rating and compare them with conventional SVM regarding prediction performance. We solve multi-class SVM+ and SVM+MTL problems by constructing several binary classifiers. Furthermore, to demonstrate the robustness and outstanding performance of SVM+MTL algorithm over other techniques, we utilized four typical multi-class processing methods in our experiments. The results show that SVM+MTL outperforms both conventional SVM and novel SVM+ in predicting corporate credit rating. This study contributes to the literature by showing the applicability of new techniques such as SVM+ and SVM+MTL and the outperformance of SVM+MTL over conventional techniques. Thus, this study enriches solving techniques for addressing multi-class problems such as corporate credit rating prediction.

• Information Systems Review
• /
• v.22 no.3
• /
• pp.81-97
• /
• 2020

Recent trends in sentiment analysis have been focused on applying single label classification approaches. However, when considering the fact that a review comment by one person is usually composed of several topics or aspects, it would be better to classify sentiments for those aspects respectively. This paper has two purposes. First, based on the fact that there are various aspects in one sentence, aspect mining is performed to classify the emotions by each aspect. Second, we apply the multiple label classification method to analyze two or more dependent variables (output values) at once. To prove our proposed approach's validity, online review comments about musical performances were garnered from domestic online platform, and the multi-label classification approach was applied to the dataset. Results were promising, and potentials of our proposed approach were discussed.

• Journal of Korean Society of Industrial and Systems Engineering
• /
• v.22 no.50
• /
• pp.363-372
• /
• 1999

This paper is to propose models for systematic classification and estimation of quality costs. Especially in this research, quality costs are categorized into three aspects, ie., conventional quality cost system, ZD(Zero Defect) quality cost system and Taguchi quality system. In conclusion, I hope that this study will have contribution to application of quality loss system for all the business in Korea.

• IE interfaces
• /
• v.20 no.3
• /
• pp.387-394
• /
• 2007

Numerous countries promote business programs to revitalize local economy, increase employment, and nurture high-tech industries. Recently, a number of business incubators have been established and operated with aims to adapt to changing environment and increase economic competitiveness in Korea. To give satisfactory results of governmental policy, the requirement to develop the evaluation model to support effective operations of business incubators using the objective and rational criteria is growing. The purpose of this study is to develop evaluation model in Business Incubator using Data Mining Process. We suggested the evaluation model of business incubator, 'Score-5 RS' consists of making evaluation factor process using weighted sum and 5-grade classification and analyzing process by Decision Tree algorithm.

• Proceedings of the Korea Association of Information Systems Conference
• /
• 2001.12a
• /
• pp.438-450
• /
• 2001

This study is to classify the typology of e-business model based on the practical strategic model for successful e-business implementation. For that purpose, we review the conceptual framework of e-business and collected the data from 127 companies implementing e-business. The study is conducted in three phases as follows. First, six factors consisted of 22 items are derived through factor analysis. Second, Cluster analysis is employed to group the firms into different strategic patterns. A five-cluster solution is found to maximize the distances between cluster means across the six factor patterns. The models are named as 'ascendancy and convergence', 'expansion and moderate price', 'expansion and improvement of quality', 'ascendancy and process', and 'improvement of quality' respectively. Third, ANOVA is used to examine the impact on the performance differences attributable to the models. The results of the study are; (1) the 'ascendancy and process', 'expansion and improvement of quality' and 'expansion and moderate price' models were associated with significantly higher performance levels than the 'improvement of quality' model, and (2) the hybrid strategies are needed to implement e-business successfully based on the 'ascendancy and process' model.

• Journal of Intelligence and Information Systems
• /
• v.18 no.4
• /
• pp.79-95
• /
• 2012

As credit loan products significantly increase in most financial institutions, the number of fraudulent transactions is also growing rapidly. Therefore, to manage the financial risks successfully, the financial institutions should reinforce the qualifications for a loan and augment the ability to detect a credit loan fraud proactively. In the process of building a classification model to detect credit loan frauds, utility from classification results (i.e., benefits from correct prediction and costs from incorrect prediction) is more important than the accuracy rate of classification. The objective of this paper is to propose a new approach to building a classification model for detecting credit loan fraud based on an individual-level utility. Experimental results show that the model comes up with higher utility than the fraud detection models which do not take into account the individual-level utility concept. Also, it is shown that the individual-level utility computed by the model is more accurate than the mean-level utility computed by other models, in both opportunity utility and cash flow perspectives. We provide diverse views on the experimental results from both perspectives.

• Journal of the Computational Structural Engineering Institute of Korea
• /
• v.33 no.2
• /
• pp.73-79
• /
• 2020

Building Information Modeling (BIM) tools have not only increased the use of technology in the design process, but also increased the need for more information standard systems. The object classification system consists of 327 types of construction results obtained from 25 kinds of facilities, 174 types of parts, and 207 types of construction parts. In the previous study, the property classification system was developed into 4 major classifications, 13 middle classifications, 58 small classifications (category), and 333 attribution information of roads and rivers. It is extremely difficult to input the property information according to such extensive object classification. In addition, the development of external applications such as Revit plug-ins has created a need to automate specific and repetitive tasks. Therefore, following the BIM property classification system, an attribute input program was implemented for the system to enhance the productivity and convenience of the BIM users.

• Asia pacific journal of information systems
• /
• v.29 no.1
• /
• pp.65-82
• /
• 2019

Technological innovations over the years have accentuated the workings in corporate- connected organizations and different application platforms. Hence, a unified management information system (MIS) that can utilize the Web and propel programming developments is required. Software agents, the latest developments in computer software technology, can be utilized to rapidly and effortlessly build integrated information systems. Consequently, 59 research papers on the use of software agents in MIS were identified from top 40 MIS journals published between 2007 and 2017. Then, we reviewed and classified all the research papers according to two categories: application fields and application categories. The application fields consisted of eight sub-groups: manufacturing, telecommunication systems, traffic and transportation management, information filtering and gathering, electronic commerce, business process management, entertainment, and medical care; whereas the application categories consisted of three sub-groups: multi-agent systems, personal assistants, and multi-agent simulation. The research papers were further divided into journal and year of publication, and journal and application field. The objective of our research was to understand the trend of the use software agent technology in MIS by examining the published research paper beside to add knowledge and content to the information system academic discipline.

• Journal of the Korean Society of Systems Engineering
• /
• v.18 no.1
• /
• pp.99-104
• /
• 2022

In this paper, to increase the maintenance efficiency of the urban railway train control system and to build a standard data system, we collect as much as possible structured, unstructured, and semi-structured data, and collect data by sensing and monitoring the system status and system status and monitoring. pre-process function data(Identification, purification, integration, transformation) through effective data classification and maintenance activities business classification system was studied. The purpose of this is to define the data matrix model by considering the relationship with the data generated and managed in the O&M stage of the train control system operated by the urban railway together with the WBS model, and to reflect and utilize it in practice.

• Proceedings of the Safety Management and Science Conference
• /
• 2011.04a
• /
• pp.243-250
• /
• 2011

In this study, we examine the changes of the freight transport business penetration system and its classification through the theoretical study. By searching case studies of related systems in developed countries, this thesis derives problem and suggests improvement.