• Journal of Computing Science and Engineering
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• v.5 no.3
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• pp.183-196
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• 2011

There has recently been a surge of interest in relational database mining that aims to discover useful patterns across multiple interlinked database relations. It is crucial for a learning algorithm to explore the multiple inter-connected relations so that important attributes are not excluded when mining such relational repositories. However, from a data privacy perspective, it becomes difficult to identify all possible relationships between attributes from the different relations, considering a complex database schema. That is, seemingly harmless attributes may be linked to confidential information, leading to data leaks when building a model. Thus, we are at risk of disclosing unwanted knowledge when publishing the results of a data mining exercise. For instance, consider a financial database classification task to determine whether a loan is considered high risk. Suppose that we are aware that the database contains another confidential attribute, such as income level, that should not be divulged. One may thus choose to eliminate, or distort, the income level from the database to prevent potential privacy leakage. However, even after distortion, a learning model against the modified database may accurately determine the income level values. It follows that the database is still unsafe and may be compromised. This paper demonstrates this potential for privacy leakage in multi-relational classification and illustrates how such potential leaks may be detected. We propose a method to generate a ranked list of subschemas that maintains the predictive performance on the class attribute, while limiting the disclosure risk, and predictive accuracy, of confidential attributes. We illustrate and demonstrate the effectiveness of our method against a financial database and an insurance database.

• The Journal of Information Technology and Database
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• v.6 no.1
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• pp.15-25
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• 1999

We propose an extended relational data model which can represent the reliability of data. In this paper, the reliability of data is defined as the reliability of the source, from which the data originated. We represent the reliability of data at the level of attribute values, instead of tuples, then define the selection, product and join operators.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 1996.04a
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• pp.179-182
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• 1996

Database management systems are now used in almost every organization to maintain and utilize important collections of information. Relational DBMSs have a firm theoretical base. However, it lacks important features needed for representing certain critical aspects of an entity. One alternatives to remedy this problem is to adopt the object-oriented approach to the data model development process. In this paper, we tried to show the advantages of object-oriented data model design process for the development of extended relational database schema needed for the integrated plant information system at H. Heavy Industry Co.

• Journal of Multimedia Information System
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• v.7 no.3
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• pp.205-214
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• 2020

Crime has become one of the major problems in modern society. Even though visual surveillances through closed-circuit television (CCTV) is extensively used for solving crime, the number of crimes has not decreased. This is because there is insufficient workforce for performing 24-hour surveillance. In addition, CCTV surveillance by humans is not efficient for detecting dangerous situations owing to accuracy issues. In this paper, we propose the autonomous detection of dangerous situations in CCTV scenes using a deep learning model with relational inference. The main feature of the proposed method is that it can simultaneously perform object detection and relational inference to determine the danger of the situations captured by CCTV. This enables us to efficiently classify dangerous situations by inferring the relationship between detected objects (i.e., distance and position). Experimental results demonstrate that the proposed method outperforms existing methods in terms of the accuracy of image classification and the false alarm rate even when object detection accuracy is low.

• 제어로봇시스템학회:학술대회논문집
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• 1994.10a
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• pp.146-151
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• 1994

An empirical comparison of static fuzzy relational models which are identified with different fuzzy implication operators and inferred by different composition operators is made in case that all the information is represented by the fuzzy discretization. Four performance measures (integral of mean squared error, maximal error, fuzzy equality index and mean lack of sharpness) are adopted to evaluate and compare the quality of the fuzzy relational models both at the numerical level and logical level. As the results, the fuzzy implication operators useful in various fuzzy modeling problems are discussed and it is empirically shown that the selection of data pairs is another important factor for identifying the fuzzy model with high quality.

• International Area Studies Review
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• v.15 no.3
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• pp.3-28
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• 2011

The present study empirically tested hypotheses delineated from a proposed model of trust-forgiveness-performance of business services, Empirical data was collected from 506 business service companies in Korea, Japan and China. The structural equation model analysis confirmed the significant effect of forgiveness on relational performance and trust on forgiveness, and also found there exist meaningful cross-national differences and similarities both in intensity and directionality of the relations.

• Journal of Information Technology Services
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• v.13 no.2
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• pp.35-53
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• 2014

Company Social Networks (CSN) has emerged as a commonly used marketing channel. One of the most important advantages in CSN is the user's voluntary behavior as a relational performance. We classified level of voluntary behavior, as 'consumption', 'active participation', and 'creative contribution' to comprehend different relational performance of CSN. Moreover, we proposed research model to compare positive attitude and negative attitude. This study aims to investigate 'the process of user's voluntary behavior in CSN' which is causal relationship between benefits of CSN, user's attitude and voluntary behavior. Empirical results with 175 valid questionnaire data revealed that CSN benefit factors played a significant role in trust and distrust. Based on these effects, trust and distrust have different influences as level of voluntary behavior, just as proposed. For practitioners, it is crucial finding that users are more active behavior based on strong trust.

• Knowledge Management Research
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• v.13 no.3
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• pp.37-54
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• 2012

The purpose of this study is to investigate determinants of partner opportunism in Korean discount store distribution channels. In addition, this study also try to examine moderating role of relational learning in the relationship. This study deals with transaction specific investment asymmetry, mutual hostages, payoff inequity, cultural diversity, and goal incompatibilities as determinants of partner opportunism. For empirical testing, 293 respondents of suppliers of discount store in Korea were surveyed and the analysis utilizing partial least square model indicated that TSI asymmetry, payoff inequity, and goal incompatibilities had positive effects on partner opportunism. On the other hand, mutual hostages had negative effect on partner opportunism. In addition, relational learning had moderating effect on the relationship between TSI asymmetry, mutual hostages, and payoff inequity and partner opportunism.

• International journal of advanced smart convergence
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• v.9 no.3
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• pp.215-220
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• 2020

The purpose of this study is to analyze the structural relationship among expectation value(relational, hedonistic), brand image, brand attitude, continuance viewing intention. The survey subjects to achieve the purpose of this study were selected the 521 YouTube sports contents Viewer in the metropolitan area. Data processing was done with SPSS 23 for frequency analysis, Cronbach's α analysis. Also, AMOS 21 was used for confirmatory factor analysis and structural equation model analysis. The results of the analysis are as follows: First, both relational value and,, hedonistic value had a positive effect on the brand image. Second, both relational value and,, hedonistic value had a positive effect on the brand attitude. Third, both brand image and brand attitudee had a positive effect on the brand attitude.

• Journal of Distribution Research
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• v.4 no.1
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• pp.71-92
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• 1999

The basic purpose of this study is to investigate how the traits of the buyer-seller transaction-relationship relate to relationship performance, including relationship performance explicitly in the proposed model. The traits examined include relational norm, formalization, market uncertainty, and relationship investment. It is hypothesized that relational norm and formalization have positive impacts on relationships performance while market uncertainty has a minus impact. In addition, it is hypothesized that relational norm has a positive moderating impact on the effect of relationship investment--the investment and efforts for maintaining a relationship to relationship performance. A mail-survey to the manufacturers of machinery and equipment about their relationships with the parts suppliers was performed. Data provided a strong support for the hypotheses. As hypothesized, relationship performance and formalization generally had positive impacts on relationship performance and formalization generally had positive impacts on relationship performance while market uncertainty showed negative impacts. Also, there is a good evidence for the positive moderating effect of relational norm to the impact of relationship investment on relationship performance.