• Journal of KIISE:Databases
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• v.29 no.5
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• pp.347-357
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• 2002

Graphs have provided a powerful methodology to solve a lot of real-world problems, and therefore there have been many proposals on the graph representations and algorithms. But, because most of them considered only memory-based graphs, there are still difficulties to apply them to large-scale problems. To cope with the difficulties, this paper proposes a graph representation and graph algorithms based on the well-developed relational database theory. Graphs are represented in the form of relations which can be visualized as relational tables. Each vertex and edge of a graph is represented as a tuple in the tables. Graph algorithms are also defined in terms of relational algebraic operations such as projection, selection, and join. They can be implemented with the database language such as SQL. We also developed a library of basic graph operations for the management of graphs and the development of graph applications. This database approach provides an efficient methodology to deal with very large- scale graphs, and the graph library supports the development of graph applications. Furthermore, it has many advantages such as the concurrent graph sharing among users by virtue of the capability of database.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 1996.10a
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• pp.337-339
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• 1996

In this paper, we construct rough relational database model using approximation concepts of rough set. Also, we analyze the relation between objects, attributes and attribute values and, propose the method that can generate flexible retrieval results.

• 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.

• Asia pacific journal of information systems
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• v.6 no.1
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• pp.165-194
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• 1996

Data distribution is one of the most important steps in distributed database design. This paper proposes a methodology for distributing database by using a relational schema as an input. A design support system called DBDD (Database Distribution Design) is implemented within the framework of this methodology. The methodology consists of three phases such as (i) schema analysis, (ii) fragmentation, and (iii) allocation. In the schema analysis phase, all the table names are acquired from a global relational schema. In the fragmentation phase, fragments are generated according to transaction retrieval patterns. Furthermore, DBDD enhances the design quality by allocating fragments in a progressive manner. A real-life case is illustrated to demonstrate the practical usefulness of the DBDD.

• IE interfaces
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• v.16 no.spc
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• pp.45-48
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• 2003

Entity-relationship modeling for designing relational database is a very complicated thinking process that requires extensive knowledge and experiences. It is very likely that designers make mistakes in this process. In order to minimize the mistakes, a systematic method to guide the thinking process is needed. In this research, an entity-relationship modeling system is developed, which resolves the whole process of information modeling, data modeling, and functional dependency relationship analysis into small and simple decision-making steps. Therefore, it can reduce the possibility of making decision errors and improve the efficiency of the modeling process. It's functionality and efficiency is verified through some modeling examples. It is expected that the modeling system can be commercialized, if some functions are added, such as detection, warning, and correction of decision errors, and educational help.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2014.05a
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• pp.615-616
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• 2014

Currently, XML is a standard language used to exchange data. Most of the data in the file system is not stored in the database system. The data stored in an object-oriented database, the data can be represented by a hierarchical structure. However, in the case of a relational database table, each independently of the hierarchical structure data is present can not be expressed. In this paper, a hierarchical representation of data is difficult in traditional relational database without changing the data in the database, without having to build a new database, Define the structure of the existing data in the XML document for the automatic generation of a PL / SQL procedure is designed.

• Asia pacific journal of information systems
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• v.12 no.2
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• pp.99-118
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• 2002

In this paper, we propose a visual relational database query language, VRQL, by modifying and extending the recently proposed $VOQL^*$. Like $VOQL^*$, VRQL, based on ven Diagram and graph, naturally reflects the structure of schemas in queries and has recursive formal semantics. However, VRQL has relationally complete expressiveness, while $VOQL^*$ is only a conjunctive query language. In the logical definition part of VRQL, which is the relational version of $VOQL^*$, most features of $VOQL^*$ are retained, and the semantics of queries are based on the tuple relational calculus. In the procedural definition part of VRQL, by introducing the concept of VRQL view and set operations, the expressiveness of VRQL is increased to the level equivalent to that of the relational algebra. Due to the introduction of VRQL views, existing queries or temporary queries used in the process of creating queries can be represented with views, so that complex queries may be represented more conveniently. Set operations, used with VRQL views, enable us to represent various queries, beyond the expressiveness of conjunctive query languages.

• 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 the Korea Society of Computer and Information
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• v.16 no.11
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• pp.25-34
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• 2011

In this paper we present an integrated design methodology for relational database based on object-oriented analysis and design. The integrated design methodology is based on business profile and has six phases. In the first phase, business use cases are identified and described by macroactivity diagrams and then the macroactivity diagrams are transformed to detailed business activity diagrams by using objects, object flows and business worker's responsibilities. In the third phase, the detailed business activity diagrams are transformed to business class diagrams that describe the static structure of the entire business system based on detailed business activity diagrams. In the four phase, the business class diagrams are transformed to class diagrams that represent the initial conceptual model of the target relational database. In the five phase, we add additional transformations on the class diagrams with generalization and specialization of associations, roles, activities, additional classes and redundant associations. Eventually, the final class diagrams are transformed to relational database schema. The methodology presented in this paper by applying that proposal for organic connection between object-oriented analysis and design methodology and relational database design methodology. And it will be able to deal with integration management. By the integrated design methodology, we can make more easily software systems based on relational database. In the case study, proposal integrated design methodology applied for a visa issuing system.

• Journal of Intelligence and Information Systems
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• v.9 no.2
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• pp.19-38
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• 2003

In this research, we propose the mechanism to develop self-evolving expert systems (SEES) based on data mining (DM), fuzzy neural networks (FNN), and relational database (RDB)-driven forward/backward inference engine. Most researchers had tried to develop a text-oriented knowledge base (KB) and inference engine (IE). However, this approach had some limitations such as 1) automatic rule extraction, 2) manipulation of ambiguousness in knowledge, 3) expandability of knowledge base, and 4) speed of inference. To overcome these limitations, knowledge engineers had tried to develop an automatic knowledge extraction mechanism. As a result, the adaptability of the expert systems was improved. Nonetheless, they didn't suggest a hybrid and generalized solution to develop self-evolving expert systems. To this purpose, we propose an automatic knowledge acquisition and composite inference mechanism based on DM, FNN, and RDB-driven inference engine. Our proposed mechanism has five advantages. First, it can extract and reduce the specific domain knowledge from incomplete database by using data mining technology. Second, our proposed mechanism can manipulate the ambiguousness in knowledge by using fuzzy membership functions. Third, it can construct the relational knowledge base and expand the knowledge base unlimitedly with RDBMS (relational database management systems) module. Fourth, our proposed hybrid data mining mechanism can reflect both association rule-based logical inference and complicate fuzzy relationships. Fifth, RDB-driven forward and backward inference time is shorter than the traditional text-oriented inference time.