• Journal of Scientific & Technological Knowledge Infrastructure
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• s.7
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• pp.76-85
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• 2001

• The Journal of Information Technology and Database
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• v.6 no.2
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• pp.45-57
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• 1999

This paper makes an attempt to find a systematic portion of the database design process, especially using the Entity-Relationship(E-R) model. Basically, we consider three aspects as a systematic portion of the database design process. They are, the strategy that a designer selects to design an E-R diagram, designer's cognitive style, and the knowledge and preference of the database designer. An experiment has been carried out in order to verify the systematic relationship between above-mentioned three aspects and the E-R modeling performance. The target system is a professional baseball system. A normative E-R diagram was constructed based upon 48 E-R diagrams produced during the experiment. The ANOVA process has been used to analyze the results. It has been found that there exist significant differences in query-answering capacity and the completeness of the E-R model among design methods. Individual differences in cognitive styles has not been found to be significantly related to the modeling performance.

• The Transactions of the Korea Information Processing Society
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• v.5 no.1
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• pp.11-23
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• 1998

In very large databases, the problem of searching for interesting information effectively is very important in terms of efficiency and flexibility. A multiple layered database approach based on AOG(attribute-oriented generalization) method is one of the useful approaches for knowledge discovery under various situations. In this paper, we propose a multiple layered database design methodology based on AOG method in object-oriented databases. In addition, we propose a dynamic schema evolution model and implementation strategy in order to continue providing information effectively in multiple layered databases.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.23 no.11
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• pp.44-51
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• 2009

A variety of Urban Rail Transit (URT) systems have been operating and they have different technology bases, causing a lot of difficulties in taking measures against trouble, training, upgrading, interoperability and so on. As such, a standardization project has been carried out to solve the problems by setting up the national standards for URT systems. A common database was built to provide the integrated engineering environment to the community of URT project. This paper discusses the design of the database and how it can be utilized in the successful promotion of the project. The products of the projects are stored into the database with traceability management to be referred to by other new URT projects for reusing and sharing the acquired knowledge through cross organizations.

• Journal of the Korean Society of Manufacturing Technology Engineers
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• v.7 no.5
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• pp.59-65
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• 1998

In order to utilize the information of well-know grinding database or grinding machine characteristics, a database needs to be designed by considering the delicate property of the machine tools for the high precision and quality of the demanding specification. Among the machine tools for the high precision and quality of the demanding specification. Among the machine tools, machining conditions of the grinding are various and knowledge repeatance obtained form the grinding process are less credable. therefore it is desirable for database, which is used to set the grinding conditions, to utilize the maximum machine tool capability. The present paper studied on the occurance limit of chatter vibration and burn considering the characteristics of machine tool. And also basic experiments were performed to establish the optimum grinding conditions which could maximize the grinding efficiency.

• 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 Intelligent Systems Conference
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• 1995.10b
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• pp.40-44
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• 1995

In this paper, we propose a retrieval system using knowledges of database expressed linguistically, where the relation between data are constructed by FCM. Several algorithms have been proposed to solve the major problem in the conventional retrieval system that the system doesn't reply in case of no data equal to user's query, and to express knowledge of database linguistically. This paper proposes the improved method of adding new cluster and the method of retrieving database from user's query. The validity of this retrieval system is shown by applying its algorithm to an example : the mail order service in post office.

• International conference on construction engineering and project management
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• 2022.06a
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• pp.800-807
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• 2022

This study aims to review the use of graph databases in construction research. Based on the diagnosis of the current research status, a future research direction is proposed. The use of graph databases in construction research has been increasing because of the efficiency in expressing complex relations between entities in construction big data. However, no study has been conducted to review systematically the status quo of graph databases. This study analyzes 42 papers in total that deployed a graph model and graph database in construction research, both quantitatively and qualitatively. A keyword analysis, topic modeling, and qualitative content analysis were conducted. The review identified the research topics, types of data sources that compose a graph, and the graph database application methods and algorithms. Although the current research is still in a nascent stage, the graph database research has great potential to develop into an advanced stage, fused with artificial intelligence (AI) in the future, based on the active usage trends this study revealed.

• Proceedings of the Korea Inteligent Information System Society Conference
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• 2001.01a
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• pp.431-434
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• 2001

Knowledge discovery in databases(KDD) is the process for extracting valid, novel, potentially useful and understandable knowledge form real data. There are many academic and industrial activities with new technologies and application areas. Particularly, data mining is the core step in the KDD process, consisting of many algorithms to perform clustering, pattern recognition and rule induction functions. The main goal of these algorithms is prediction and description. Prediction means the assessment of unknown variables. Description is concerned with providing understandable results in a compatible format to human users. We introduce an efficient data mining algorithm considering predictive and descriptive capability. Reasonable pattern is derived from real world data by a revised neural network model and a proposed fuzzy rule extraction technique is applied to obtain understandable knowledge. The proposed neural network model is a hierarchical self-organizing system. The rule base is compatible to decision makers perception because the generated fuzzy rule set reflects the human information process. Results from real world application are analyzed to evaluate the system\`s performance.

• Fashion & Textile Research Journal
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• v.11 no.4
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• pp.648-660
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• 2009

In this research, an expert system has been developed to select optimum well-matched fusible interlinings with a face fabric. First, a database of face fabrics and fusible interlinings has been constructed. And knowledge acquisition has been performed from the previous studies about the properties of fusible interlinings and fused composites as well as fusing prsocess quality control. Then, a rule-based knowledge-base has been constructed through knowledge classification. Finally, we have constructed an inference engine with the knowledge-base. The expert system enables us to easily select optimum fusible interlinings for a face fabric considering high quality fused composites and fashion trend.