• Journal of Korean Society for Geospatial Information Science
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• v.3 no.1 s.5
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• pp.45-54
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• 1995

The relational data model is based on mathematical concept of relations and is well formulated, and so there have been numerous practical applications and studies. However, it is not suitable for representing a complex hierarchical structure, which is the characteristic of most geographical objects. On the other hand, the object-oriented data model can naturally represent a complex hierarchical structure, but there is a difficulty in sharing data with the relational data model which is currently used by most commercial GIS users. Also it has no standard query language with standardized format. In this paper, we propose an Object Grouping based on RDBMS to use data from a traditional relational data model while supporting various concepts of the object-oriented data model, and we applied this data model to design a GIS.

• 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 Institute of Intelligent Systems Conference
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• 1993.06a
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• pp.1222-1225
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• 1993

The purpose of this paper is to construct a prediction system on the chance of rain in a local region using a fuzzy relational model. The prediction system consists of two parts. One is a prediction part on the chance of rain. The compositional law of fuzzy inference, proposed by Zadeh, is applied to predict the chance of rain. The other is a learning part of a fuzzy relational model using input-output data. A simple and fast learning algorithm is used in this part. Simulations are carried out by the actual weather data in our city and their results show the validity of prediction by the fuzzy relational approach.

• The Journal of Society for e-Business Studies
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• v.7 no.1
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• pp.153-166
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• 2002

Nowadays an information exchange on Bn such as B2B electronic commerce is spreading. Therefore the systematic and stable management mechanism for storing the exchanged information is needed. For this goal there are many research activities for connection between XML application and relational database. But because XML data have hierarchical structures and relational database can store only flat-structured data, we need to store XML data in object-relational database that support hierarchical structure. Accordingly the modeling methodology for storing XML data in object-relational database is needed. In order to build good quality application systems, modeling is an important first step. In 1997, the OMG adopted the UML as its standard modeling language. Since industry has warmly embraced UML its popularity should become more important in the future. So a design methodology based on UML is need to develop efficiently XML applications. In this paper, we propose a unified design methodology for In applications based on object-relational database using In. To this goal, first we introduce a XML modeling methodology to design W3C XML schema using UML and second we propose data modeling methodology for object-relational database schema to store efficiently XML data in object-relational databases.

• Journal of Korean Institute of Industrial Engineers
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• v.37 no.3
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• pp.264-270
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• 2011

A new method for creating a logical data model is proposed. The logical data model developed by the method defines table, primary key, foreign key, and fields. The framework of the logical data model is constructed by modeling the relationships between events and their related entity types. The proposed method consists of a series of objective and quantitative decisions such as maximum cardinality of relationships and functional dependency between the primary key and attributes. Even beginners to database design can use the methology as long as they understand such basic concepts about relational databases as primary key, foreign key, relationship cardinality, parent-child relationship, and functional dependency. The simple and systematic approach minimizes decision errors made by a database designer. In practial database design the method creates a logical data model in Boyce-Codd normal form unless the user of the method makes a critical decision error, which is very unlikely.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.16 no.1
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• pp.726-734
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• 2015

Relational databases used by structuralizing data are the most widely used in data management at present. However, in relational databases, service becomes slower as the amount of data increases because of constraints in the reading and writing operations to save or query data. Furthermore, when a new task is added, the database grows and, consequently, requires additional infrastructure, such as parallel configuration of hardware, CPU, memory, and network, to support smooth operation. In this paper, in order to improve the web information services that are slowing down due to increase of data in the relational databases, we implemented a model to extract a large amount of data quickly and safely for users by processing Hadoop Distributed File System (HDFS) files after sending data to HDFSs and unifying and reconstructing the data. We implemented our model in a Web-based civil affairs system that stores image files, which is irregular data processing. Our proposed system's data processing was found to be 0.4 sec faster than that of a relational database system. Thus, we found that it is possible to support Web information services with a Hadoop-based big data processing technique in order to process a large amount of data, as in conventional relational databases. Furthermore, since Hadoop is open source, our model has the advantage of reducing software costs. The proposed system is expected to be used as a model for Web services that provide fast information processing for organizations that require efficient processing of big data because of the increase in the size of conventional relational databases.

• Journal of National Security and Military Science
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• s.1
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• pp.269-310
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• 2003

AS Extensible Markup Language(XML) is emerging as the data format of the Internet era, there are increasing needs to efficiently transform between database and XML documents. In this paper, we propose a schema transformation method from relational database to XML database. To transform the schema, we represent input schema as Entity-Relationship diagram. Entity-Relationship model translator scans the input Entity-Relationship diagram using BFS (breadth First Search) and translates the diagram into hierarchical structure model. The XML Schema generator produces XML Scema code using the transformed hierarchical structure model. The proposed method has a merit that having reusability facility of XML Schema property in comparison with existing researches.

• KIPS Transactions on Software and Data Engineering
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• v.3 no.1
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• pp.19-30
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• 2014

For the expansion of the Semantic Web, studies in converting the data stored in the relational database into the ontology are actively in process. Such studies mainly use an RDB to RDF mapping model, the model to map relational database components to RDF components. However, pre-proposed mapping models have got different expression modes and these damage the accessibility and reusability of the users. As a consequence, the necessity of the standardized mapping language was raised and the W3C suggested the R2RML as the standard mapping language for the RDB to RDF model. The R2RML has a characteristic that converts only the relational database schema data to RDF. For the same reasons above, the ontology about the relation data between table name and column name of the relational database cannot be added. In this paper, we propose an RDB to RDF mapping system considering semantic relations of RDB components in order to solve the above issue. The proposed system generates the mapping data by adding the RDFS attribute data into the schema data defined by the R2RML in the relational database. This mapping data converts the data stored in the relational database into RDF which includes the RDFS attribute data. In this paper, we implement the proposed system as a Java-based prototype, perform the experiment which converts the data stored in the relational database into RDF for the comparison evaluation purpose and compare the results against D2RQ, RDBToOnto and Morph. The proposed system expresses semantic relations which has richer converted ontology than any other studies and shows the best performance in data conversion time.

• Journal of KIISE:Databases
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• v.33 no.5
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• pp.526-537
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• 2006

The most representative approach for efficient storing of XML data is to store XML data in relational databases. The merit of this approach is that it can easily accept the realistic status that most data are still stored in relational databases. This approach needs to convert XML data into relational data or relational data into XML data. The most important issue in the translation is to reflect structural and semantic relations of RDB to XML schema model exactly. Many studies have been done to resolve the issue, but those methods have several problems: Not cover structural semantics or just support explicit referential integrity relations. In this paper, we propose an algorithm for extracting implicit referential integrities automatically. We also design and implement the suggested algorithm, and execute comparative evaluations using translated XML documents. The proposed algorithm provides several good points such as improving semantic information extraction and conversion, securing sufficient referential integrity of the target databases, and so on. By using the suggested algorithm, we can guarantee not only explicit referential integrities but also implicit referential integrities of the initial relational schema model completely. That is, we can create more exact XML schema model through the suggested algorithm.

• Proceedings of the Korean Institute Of Construction Engineering and Management
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• 2007.11a
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• pp.301-305
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• 2007

Mapping of EXPRESS, which is object-favored language to represent IFC model, to Relational Database is not straightforward. Model size can be much bigger and data can be missed through process. However mapping to the object concept added database, such as Object Oriented Database or Object Relational Database, may be simpler and have lots of advantages. This study investigates previous IFC mapping studies, concept of Relational Database and Object Oriented Database, and mapping methodology to Object Relational Database using object.