• Journal of KIISE
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• v.43 no.12
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• pp.1385-1395
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• 2016

In the era of Big Data, NoSQL databases provide solutions for problems, circumventing the limitations of traditional relational databases by using new architectures and data model. Contrary to relational database products, the range of the features architectures, and limitations of NoSQL databases is very broad. Thus, choosing the right database products requires more considerations and difficulties. The advent of NoSQL does not only promote the abundance of NoSQL products, but also stimulates the relational database realm to expand their features beyond the relational model. In order to understand NoSQL trends more accurately, here we discuss and compare NoSQL databases with relational databases. We also present the newest features associated with NoSQL in one of the most advanced open-source relational databases, PostgreSQL. To discuss future directions for PostgreSQL we analyzed the performance of NoSQL and PostgreSQL by conducting experiments using the NoSQL benchmark tool (YCSB).

• Journal of Digital Contents Society
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• v.10 no.1
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• pp.129-145
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• 2009

As the secure distribution and sharing of information over the World Wide Web becomes increasingly important, the needs for flexible and efficient support of access control systems naturally arise. Since the eXtensible Markup Language (XML) is emerging as the de-facto standard format of the Internet era for storing and exchanging information, there have been recently, many proposals to extend the XML model to incorporate security aspects. To the lesser or greater extent, however, such proposals neglect the fact that the data for XML documents will most likely reside in relational databases, and consequently do not utilize various security models proposed for and implemented in relational databases. In this paper, we take a rather different approach. We explore how to support security models for XML documents by leveraging on techniques developed for relational databases considering object perspective. More specifically, in our approach, (1) Users make XML queries against the given XML view/schema, (2) Access controls for XML data are specified in the relational database, (3) Data are stored in relational databases, (4) Security check and query evaluation are also done in relational databases, and (5) Controlling access control is executed considering XML tree levels

• Journal of KIISE:Databases
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• v.31 no.4
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• pp.432-443
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• 2004

As the XML data has been widely used in the Internet, it is necessary to store and retrieve the XML data by using DBMSs. However, relational DBMSs suffer from the model difference between graph structure of the XML data and table forms in relational databases. We propose an ORDBMS-based DTD-dependent XML data management system Xing. Xing stores XML data in a DTD-dependent form in an object database. Since the object database schema has a graph structure and supports multi-valued attributes, mapping from an XML data model and queries into an object data model and OQLs is a simple problem. For rapid storing of large quantities of the XML data, we use SAX parser with customized Xing-tree which requires a small memory space compared with the DOM-tree. Xing also returns the query result in an XML document form. We have implemented the Xing system on top of UniSQL object-relational DBMS for the validity checking and performance comparison. For XML genome data from GenBank, and experimental evaluation shows that Xing can provide significant performance improvement (maximum 10 times) compared with the relational approach.

• Journal of the Korean Operations Research and Management Science Society
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• v.21 no.3
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• pp.197-214
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• 1996

Financial analysis of stock data usually involves extensive computation of large amount of time series data sets. To handle the large size of the data sets and complexity of the analyses, database management systems have been increasingly adaopted for efficient management of stock data. Specially, relational database management system is employed more widely due to its simplistic data management approach. However, the normalized two-dimensional tables and the structured query language of the relational system turn out to be less effective than expected in accommodating time series stock data as well as the various computational operations. This paper explores a new data management approach to stock data management on the basis of an object-oriented database management system (ODBMS), and proposes a data model supporting times series data storage and incorporating a set of financial analysis functions. In terms of functional stock data analysis, it specially focuses on a primitive set of operations such as variance of stock data. In accomplishing this, we first point out the problems of a relational approach to the management of stock data and show the strength of the ODBMS. We secondly propose an object model delineating the structural relationships among objects used in the stock data management and behavioral operations involved in the financial analysis. A prototype system is developed using a commercial ODBMS.

• 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.

• 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.

• Human Ecology Research
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• v.58 no.1
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• pp.75-86
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• 2020

This study examined the mediating effect of intimate partner violence (IPV) between alcohol use and relational satisfaction by the Actor Partner Interdependence Model (APIM). For this study, data were drawn from the 13^th-wave Korea Welfare Panel data and a total of 2,263 married couples were included in the analysis. SPSS 25.0 and AMOS 24 were used to analyze data and the Actor Partner Interdependence Mediation Model (APIMeM) examined the mediating effect. The results of this study are summarized as follows. First, the actor effect and the partner effect on the relationship of alcohol use and partner violence were all verified to be positive effects. Second, the actor effect and the partner effect on the relationship of partner violence and relational satisfaction were all verified to be negative effects. Third, comparison of the actor effect and partner effect between the husband and wife showed that the partner effect in which alcohol use to partner violence was greater in the husband than in the wife. In addition, both the actor and partner effect of violent reducing their relational satisfaction were greater in wives than in husbands. The findings of this study suggest that IPV has a mediating role between couples' alcohol use and the relational satisfaction and husband's violent behavior has more negative effect on the quality of the relationship than the wife's violent behavior.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.25 no.6A
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• pp.870-884
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• 2000

Among OLAP(On-Line Analytical Processing) approaches, ROLAP(Relational OLAP) based on the star, snowflake schema which offer the multidimensional analytical method has performance problem and MOLAP (Multidimensional OLAP) based on Multidimensional Database System has scalability problem. In this paper, to solve the limitaions of previous approaches, design and implementation of multidimensional data model based on Object-Relation DBMS was proposed. With the extensibility of Object-Relation DBMS, it is possible to advent multidimensional data model which more expressively define multidimensional concept and analysis functions that are optimized for the defined multidimensional data model. In addition, through the hierarchy between data objects supported by Object-Relation DBMS, the aggregated data model which is inherited from the super-table, multidimensional data model, was designed. One these data models and functions are defined, they behave just like a built-in function, w th the full performance characteristics of Object-Relation DBMS engine.

• Proceedings of the Computational Structural Engineering Institute Conference
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• 2004.10a
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• pp.126-132
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• 2004

The database design for the management of bridge measurement information is presented in this paper. To express the associated data generated during the whole process of ambient measurement efficiently, requirements analysis for database construction is performed. And to define objects and organize schema conceptual and logical design are performed, which convert data model into logical schema. Finally, physical design is performed using DDL(data defined language). This database is based on the object-relational data modeling approach that has rich expressive power and good reusability in comparison with the traditional entity-relational modeling.

• Proceedings of the Korea Society for Industrial Systems Conference
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• 2007.02a
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• pp.163-167
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• 2007

We propose an XML document storage system, called XDMS (XML Document Management System), by using an object-relational DBMS. XDMS generates object database schema from XML Schema and stores the XML documents in an object-relational database. SAX parser is used for understanding the structure of the XML documents, and XDMS transforms the documents into objects in the database. Experiment shows that object-relational databases provide more efficient storage and query model compared with relational databases.