• Journal of Information Technology Services
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• v.14 no.3
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• pp.99-116
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• 2015

The concept of Cloud computing has been introduced in the IT field over 10 years and industry has been expanding constantly. However, compare to the maturity of global market, Korea cloud computing industry is only in the early stage. Even the Korea has advantages in technology infrastructure; the pace of Korea cloud computing market growth is taking a serious downturn. Under these circumstances, it is needed to be discussing that strategy for expanding the cloud computing market size and for sustaining global competitiveness of local companies. Previous studies on plans for Korea cloud computing market has been conducted since 2009 and most of them are tend to examined in demand perspective. Thus, this study aims at identifying the priority of business challenges for making better performance in the market with service provider aspects. To analyze the important factors in the providing cloud computing service, ANP methodology was applied in this study. The network model including five clusters, security, stability, performance, consumer, and institution, was defined through literature review and expert survey was conducted to collect data. As a result of ANP analysis, 'Securing service reliability' was analyzed as the most important factor and followed by 'Preparing the range of legal liability', 'Preventing personal information leakage' and 'Preventing confidential information data leakage.' The priority of result indicates that service provider needs to focus on to make the secured service environment. This study has significance on analyzing the priority of business challenges in the service provider perspective. This study will provide useful guidelines to for establishing strategies in cloud computing market.

• Journal of Intelligence and Information Systems
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• v.13 no.4
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• pp.91-104
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• 2007

Ontology matching technique is one of the most important techniques in the Semantic Web as well as in other areas. Ontology matching algorithm takes two ontologies as input, and finds out the matching relations between the two ontologies by using some parameters in the matching process. Ontology matching is very useful in various areas such as the integration of large-scale ontologies, the implementation of intelligent unified search, and the share of domain knowledge for various applications. In general cases, the performance of ontology matching is estimated by measuring the matching results such as precision and recall regardless of the requirements that came from the matching environment. Therefore, most research focuses on controlling parameters for the optimization of precision and recall separately. In this paper, we focused on the harmony of precision and recall rather than independent performance of each. The purpose of this paper is to propose a methodology that determines parameters for the desired ratio of precision and recall that is appropriate for the requirements of the matching environment.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.46 no.1
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• pp.32-41
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• 2023

Recently, many studies are being conducted to extract emotion from text and verify its information power in the field of finance, along with the recent development of big data analysis technology. A number of prior studies use pre-defined sentiment dictionaries or machine learning methods to extract sentiment from the financial documents. However, both methods have the disadvantage of being labor-intensive and subjective because it requires a manual sentiment learning process. In this study, we developed a financial sentiment dictionary that automatically extracts sentiment from the body text of analyst reports by using modified Bayes rule and verified the performance of the model through a binary classification model which predicts actual stock price movements. As a result of the prediction, it was found that the proposed financial dictionary from this research has about 4% better predictive power for actual stock price movements than the representative Loughran and McDonald's (2011) financial dictionary. The sentiment extraction method proposed in this study enables efficient and objective judgment because it automatically learns the sentiment of words using both the change in target price and the cumulative abnormal returns. In addition, the dictionary can be easily updated by re-calculating conditional probabilities. The results of this study are expected to be readily expandable and applicable not only to analyst reports, but also to financial field texts such as performance reports, IR reports, press articles, and social media.

• The Journal of Society for e-Business Studies
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• v.22 no.3
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• pp.87-103
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• 2017

In recent years, many small and medium-sized manufacturing companies are making process innovation and product innovation through the public knowledge services. K Research institute provides different types of knowledge services in combination and due to this complexity, it is difficult to analyze the performance of knowledge service programs precisely. In this study, we derived performance items from bottom-up viewpoints, rather than top-down approaches selecting those items as in previous performance analysis. As a result, 74 items were finded from 82 companies in the K Research Institute case book, and the final result was refined to 17 items. After that a case-performance matrix was constructed, and binary data was entered to analyze. As a result, three clusters were identified through K-means clustering as 'enhancement of core competitiveness (product and patent),' 'expansion of domestic and overseas market,' and 'improvement of operational efficiency.'

• Asia pacific journal of information systems
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• v.23 no.4
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• pp.129-149
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• 2013

According to the development of new Information Technologies, firms consistently invest a significant amount of money in IT activities, such as establishing internal and external information systems. However, several anti-Information activities-such as hacking, leakage of information and system destruction-are also rapidly increasing, thus many firms are exposed to direct and indirect threats. Therefore, firms try to establish information security systems and manage these systems more effectively via an enterprise perspective. However, stakeholders or some managers have negative opinions about information security systems. Therefore, in this research, we study the relationship between multibusiness firms' performance and information security systems. Information security indicates physical and logical correspondence of information system department against threats and disaster. Studies on information security systems suggested frameworks such as IT Governance Cube and COBIT Framework to identify information security systems. Thus, this study define that information security systems is a controlled system on enterprise IT process and resource on IT Governance perspective rather than independent domain of IT. Thus, Information Security Systems should be understood as a subordinate concept of IT and business processes. In addition, this study incorporates information capability to information security system literature to show the positive relationship between Information Security Systems and Corporate Performance. The concept of information capability suggested that an interaction of human, information, technical and an effect on corporate performance using three types of capability (IT Practice, Information Management Practice, Information Behaviors and Values). Information capability is about firms' capability to manage IT infrastructure and information as well as individual employees who use IT infrastructure and information. Thus, this study uses information capability as a mediating variable for the relationship between information security systems and firms' performance. To investigate the relationship between Information Security Systems and multibusiness firms' performance, this study extends the IT relatedness concept into Information Security Systems. IT relatedness provides understanding of how corporations cope with conflicts between headquarters and business units to create a synergy effect and achieve high performance using IT resources. Based on the previous literature, this study develops the IT Security Relatedness model. IT Security Relatedness is our main independent variable, while Information Capability and Information Security Performance are mediating variables. To control for the common method bias, we collect each multibusiness firm's financial performance and use it as our dependent variable. We find that Information Security Systems influence Information Capability and Information Security Performance positively, and these two variables consequently influence Corporate Performance positively. In addition, this result indirectly shows that corporations under a multibusiness environment can obtain synergy effects using the integrated Information Security Systems. This positive impact of Information Security Systems on multibusiness firms' performance has an important implication to various stakeholders. Therefore, multibusiness firms need to establish Information Security Systems to achieve better financial performance.

• Journal of the Korea Safety Management & Science
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• v.10 no.2
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• pp.71-83
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• 2008

Most researches on the corporate credit rating are generally classified into the area of bankruptcy prediction and bond rating. The studies on bankruptcy prediction have focused on improving the performance in binary classification problem, since the criterion variable is categorical, bankrupt or non-bankrupt. The other studies on bond rating have predicted the credit ratings, which was already evaluated by bond rating experts. The financial institute, however, should perform effective loan evaluation and risk management by employing the corporate credit rating model, which is able to determine the credit of corporations. Therefore, in this study we present a medium sized corporate credit rating system by using Artificial Neural Network(ANN) and Analytical Hierarchy Process(AHP). Also, we developed AHP model for credit rating using non-financial information. For the purpose of completed credit rating model, we integrated the ANN and AHP model using both financial information and non-financial information. Finally, the credit ratings of each firm are assigned by the proposed method.

• JSTS:Journal of Semiconductor Technology and Science
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• v.1 no.1
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• pp.20-30
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• 2001

A 1.8V $650{\;}\textrm{mm}^2$ 4Gb DRAM having $0.10{\;}\mu\textrm{m}^2$ cell size has been successfully developed using 0.11 $\mu\textrm{m}$DRAM technology. Considering manufactur-ability, we have focused on developing patterning technology using KrF lithography that makes $0.11{\;}\mu\textrm{m}$ DRAM technology possible. Furthermore, we developed novel DRAM technologies, which will have strong influence on the future DRAM integration. These are novel oxide gap-filling, W-bit line with stud contact for borderless metal contact, line-type storage node self-aligned contact (SAC), mechanically stable metal-insulator-silicon (MIS) capacitor and CVD Al process for metal inter-connections. In addition, 80 nm array transistor and sub-80 nm memory cell contact are also developed for high functional yield as well as chip performance. Many issues which large sized chip often faces are solved by novel design approaches such as skew minimizing technique, gain control pre-sensing scheme and bit line calibration scheme.

• Journal of Korean Institute of Industrial Engineers
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• v.42 no.1
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• pp.30-37
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• 2016

A multi-server queueing system with an infinite buffer and impatient customers is analyzed. The system operates in the finite state Markovian random environment. The number of available servers, the parameters of the batch Markovian arrival process, the rate of customers' service, and the impatience intensity depend on the current state of the random environment and immediately change their values at the moments of jumps of the random environment. Dynamics of the system is described by the multi-dimensional asymptotically quasi-Toeplitz Markov chain. The ergodicity condition is derived. The main performance measures of the system are calculated. Numerical results are presented.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.27 no.1
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• pp.103-108
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• 2004

Companies adopted a program called Six Sigma, in order to make fundamental changes in the way the company operated to fulfill customers' expectations. Six Sigma reduces the occurrence of defects. This approach derives the overall process of selection the right projects based on their potential to improve performance metrics and selection and training the right people to get the business results. However, in the course of Six Sigma process steps, companies are in the face of problems. This study is to solve the problems using TOC(Theory of Constrains). TOC is methodology for solving key problem in system which is called Constraints. Nowadays, its application is going to be wide and its concept is being implemented. In this paper, it is showed possibility of application TOC to Six Sigma.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 2001.10a
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• pp.55-58
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• 2001

It is more important than ever for companies to distinguish themselves through knowledge management strategies. Without a constant creation of knowledge, a business is condemned to poor performance. However, it is still unclear how these strategies affect knowledge creation. Knowledge management strategies can be categorized as being either human or system oriented. This paper proposes a model to illustrate the link between the strategies and its creating process. It is found that human strategy is more likely to be effective for socialization while system strategy is more likely to be effective for combination. Furthermore, the result suggests that managers should adjust knowledge management strategies in view of the characteristics of their departments.