• Industrial Engineering and Management Systems
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• v.11 no.1
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• pp.87-93
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• 2012

This paper discusses a new weighting method for text analyzing from the view point of supervised learning. The term frequency and inverse term frequency measure (tf-idf measure) is famous weighting method for information retrieval, and this method can be used for text analyzing either. However, it is an experimental weighting method for information retrieval whose effectiveness is not clarified from the theoretical viewpoints. Therefore, other effective weighting measure may be obtained for document classification problems. In this study, we propose the optimal weighting method for document classification problems from the view point of supervised learning. The proposed measure is more suitable for the text classification problem as used training data than the tf-idf measure. The effectiveness of our proposal is clarified by simulation experiments for the text classification problems of newspaper article and the customer review which is posted on the web site.

• The Journal of Information Systems
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• v.19 no.4
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• pp.65-85
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• 2010

The importance of communities of practice(CoP) as an organizational informal unit for fostering knowledge transfer and sharing gains a lot of attention from KM researchers and practitioners. Since most of CoPs are formulated online these days, the credibility or trustworthiness of knowledge contents circulated within a certain CoP should be considered thoroughly for them to be fully utilized safely. Here comes the need for an appropriate trust measuring methodology to determine the true value of knowledge given by unknown people through an online channel. In this paper, an improved trust measuring method is proposed using new trust variables such as level of degrees derived from the relationships among community users. In addition, activeness, relevance, and usefulness of the knowledge contents themselves, which are calculated automatically using a text categorization technique, are also used for trust measurement. The proposed framework incorporates fuzzy set and calculation concepts to help build trust matrices and models, which are used to measure the level of trust involved in specific knowledge artifacts concerned.

• Journal of Korean Society for Quality Management
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• v.29 no.3
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• pp.97-108
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• 2001

The information system for measuring and analyzing service quality of telephone network is designed on the service quality scheme recommended by ITU(International Telecommunication Union) in this study. The information system is composed of the equipments which measure service quality and the systems which analyze the measured data. The schedule algorithm for effectively operating measurement equipments which are located over public switched telephone network is proposed. The functions of the Information system are Introduced. The information system improves the service quality effectively.

• Information Systems Review
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• v.19 no.2
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• pp.71-94
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• 2017

Recommender systems reduce information overload and enhance choice quality. This technology is used in many services and industry. Previous studies did not consider recommendation quantity and the repetitive recommendations of an item. This study is the first to examine recommender systems by considering recommendation quantity and repetitive recommendations. Only a limited number of items are displayed in offline stores because of their physical limitations. Determining the type and number of items that will be displayed is an important consideration. In this study, I suggest the use of a user-based recommender system that can recommend the most appropriate items for each store. This model is evaluated by MAE, Precision, Recall, and F1 measure, and shows higher performance than the baseline model. I also suggest a new performance evaluation measure that includes Quantity Precision, Quantity Recall, and Quantity F1 measure. This measure considers the penalty for short or excess recommendation quantity. Novelty is defined as the proportion of items in a recommendation list that consumers may not experience. I evaluate the new revenue creation effect of the suggested model using this novelty measure. Previous research focused on recommendations for customer online, but I expand the recommender system to cover stores offline.

• International Journal of Computer Science & Network Security
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• v.24 no.8
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• pp.125-134
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• 2024

With the great development of technology in all fields these days, including the financial field, people have gone into cryptocurrency trading, without prior knowledge or experience, which made them prey and coveted by hackers through phishing attacks. Therefore, we will study cases where people can be a victim of phishing because cryptocurrency occurs without an intermediary, such as banks and monetary institutions. It is a form of peer-to-peer transaction, physical wallets, and fake investing. This study aims to know the concept of a phishing attack on cryptocurrencies, and to measure the extent of peoples awareness of the security risks on these currencies. Previous literature will be reviewed, and a questionnaire will be published on traders who use cryptocurrency trading platforms, and then we collect data and analyze the answers provided, so that we can suggest educational solutions to these phishing problems.

• The Journal of Information Systems
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• v.17 no.3
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• pp.25-37
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• 2008

In a fault tree analysis, an uncertainty importance measure is often used to assess how much uncertainty of the top event probability (Q) is attributable to the uncertainty of a basic event probability ($q_i$), and thus, to identify those basic events whose uncertainties need to be reduced to effectively reduce the uncertainty of Q. For evaluating the measures suggested by many authors which assess a percentage change in the variance V of Q with respect to unit percentage change in the variance $v_i$ of $q_i$, V and ${\partial}V/{\partial}v_i$ need to be estimated analytically or by Monte Carlo simulation. However, it is very complicated to analytically compute V and ${\partial}V/{\partial}v_i$ for large-sized fault trees, and difficult to estimate them in a robust manner by Monte Carlo simulation. In this paper, we propose a method for evaluating the measure using discretization technique and Monte Carlo simulation. The proposed method provides a stable uncertainty importance of each basic event.

• Journal of Information Technology Applications and Management
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• v.24 no.1
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• pp.45-61
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• 2017

Business intelligence has been attracting much attention these days. Despite such popularity of BI systems, it is widely known that about a half of BI system projects have failed. To grasp why many BI projects end in failure and what factors would make BI projects less failure-prone, a number of BI studies were made to produce a variety of CSFs. However, there is a paucity of information on whether these CSFs are distinctive from those of typical information systems. By identifying how BI CSFs differ from CSFs of typical information systems, we would be able to explain why most BI projects are more likely to be failure. It is believed that a corrective measure about CSFs will lead to more success in future BI projects. In addition, though there have been a number of similar types of BI systems such as decision support systems and executive information systems in existence, there was no study to determine whether there is ever a discrimination between CSFs of BI systems and the similarly-titled systems. This study is to answer these questions using a literature review analysis. The findings of our study are expected to be helpful in a successful implementation of BI systems.

• 한국경영정보학회:학술대회논문집
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• 2007.06a
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• pp.807-813
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• 2007

Although firms are adopting strategic performance management systems (PMS) that provide information that allows the firms to identify the strategies offering the highest potential for achieving the firms' objectives, many firms still suffer from making the implementation of PMS a success. The purpose of this paper is to identify those factors that influence the successful implementation of performance management systems. This paper performs a comprehensive literature scrutiny on the implementation factors of PMS including the Balanced Scorecard, Performance Prism, Intellectual Capital Navigation, and Activity-based Costing, as well as traditional performance management systems. The findings of this research will provide useful insights into the anatomy of the success factors for implementing performance management systems and will help management to all the different sized organizations in the different sectors and industries. This paper also provides some future directions for research.

• Journal of Korean Society for Quality Management
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• v.27 no.4
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• pp.20-41
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• 1999

This study addresses the development of a quality measurement of information systems integration(SI) service. Several dimensions which affect on quality of systems integration service have been identified and tested. Also, a measurement tool(questionnaire) of the factors has been developed. To achieve above purpose, extensive literature review and in-depth interview with several SI managers and customers were used. We suggested the analysis framework including performance variables such as quality, customer satisfaction, intention of renewal contract, and contribution to better customer's information system and the quality factors as well. To verify the research framework, collected data from the survey was analyzed statistically. The data from 73 respondents was used for analysis. Consequently, we identified eight factors and developed a 41-item instrument with Likert 5 points to measure the quality of SI service. It was proved that the 41-item instrument suggested in this study was very useful to measure the performance of SI service such as quality and customer satisfaction. Also it was shown that the instrument measured intention of renewal contract and contribution of customer's information system well.

• Journal of the Korean Operations Research and Management Science Society
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• v.18 no.2
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• pp.183-203
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• 1993

One of the most difficult and time-consuming stages in the development of the knowledge-based system is a knowledge acquisition. A splitting algorithm is developed to infer a rule-tree which can be converted to a rule-typed knowledge. A market segmentation may be performed in order to establish market strategy suitable to each market segment. As the sales data of a product market is probabilistic and noisy, it becomes necessary to prune the rule-tree-at an acceptable level while generating a rule-tree. A splitting algorithm is developed using the pruning measure based on a total amount of information gain and the measure of existing algorithms. A user can easily adjust the size of the resulting rule-tree according to his(her) preferences and problem domains. The algorithm is applied to a market segmentation problem of a medium-large computer market. The algorithm is illustrated step by step with a sales data of a computer market and is analyzed.