• Journal of Physiology & Pathology in Korean Medicine
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• v.23 no.4
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• pp.745-750
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• 2009

The goal of this study is to examine on reasoning and search for construction of diagnosis ontology as a knowledge base of diagnosis expert system in oriental medicine. Expert system is a field of artificial intelligence. It is a system to acquire information with diverse reasoning methods after putting expert's knowledge in computer systematically. A typical model of expert system consists of knowledge base and reasoning & explanatory structure offering conclusion with the knowledge. To apply ontology as knowledge base to expert system practically, consideration on reasoning and search should be together. Therefore, this study compared and examined reasoning, search with diagnosis process in oriental medicine. Reasoning is divided into Rule-based reasoning and Case-based reasoning. The former is divided into Forward chaining and Backward chaining. Because of characteristics of diagnosis, sometimes Forward chaining or backward chaining are required. Therefore, there are a lot of cases that Hybrid chaining is effective. Case-based reasoning is a method to settle a problem in the present by comparing with the past cases. Therefore, it is suitable to diagnosis fields with abundant cases. Search is sorted into Breadth-first search, Depth-first search and Best-first search, which have respectively merits and demerits. To construct diagnosis ontology to be applied to practical expert system, reasoning and search to reflect diagnosis process and characteristics should be considered.

• Journal of KIISE:Software and Applications
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• v.36 no.2
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• pp.153-160
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• 2009

As size of ontology has been increased more and more, the descriptions in the ontologies become more complicated, Therefore finding and modifying unsatisfiable concepts is hard work in ontology construction process, Minerva is an ontology reasoner which detects unsatisfiable concepts automatically and infers subsumption relation between concepts in ontology, Most description logic based ontology reasoners (including Minerva) work using tableaux algorithm, Because tableaux algorithm is very costly, ontology reasoners need various optimization methods, In this paper, we propose optimizing methods to reduce execution time of tableaux algorithm based ontology reasoner. Proposed methods were applied to Minerva which was developed as preceding study result. In consequence the new version Minerva shows high performance.

• Proceedings of the Computational Structural Engineering Institute Conference
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• 2008.04a
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• pp.435-441
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• 2008

Building Information Modelings(BIM) are more complex than typically required for early phase of the design process of a building. Construction projects have many participants from various disciplines involved throughout the entire process. Therefore the success of the project greatly depend on the efficiency of decision-making using the information generated from each process stage. This research utilized an ontology to provide an underlying structure of objects and relationships of a building. The OWL is introduced as a main vehicle to encode the information and knowledge about the building structures and spaces. A case study was conducted to develop a structured representation of an ontology where the relationships among the necessary components in the stage of preliminary design were to be automatically utilized to plan on the sizes of each room in a building and structured thoroughly with a simple structured representation.

• International conference on construction engineering and project management
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• 2011.02a
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• pp.213-220
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• 2011

In the current construction industry where various stakeholders take part, BIM Data exchange using standard format can provide a more efficient working environment for related staffs during the life-cycle of the building. Currently, the formats used to exchange the data from 3D-CAD application to structure energy analysis at the design stages are IFC, the international standard format provided by IAI, and gbXML, developed by Autodesk. However, because of insufficient data compatibility, the BIM data produced in the 3D-CAD application cannot be directly used in the energy analysis, thus there needs to be additional data entry. The reasons for this are as follows: First, an IFC file cannot contain all the data required for energy simulation. Second, architects sometimes write material names on the drawings that are not matching to those in the standard material library used in energy analysis tools. DOE-2.2 and Energy Plus are the most popular energy analysis engines. And both engines have their own material libraries. However, our investigation revealed that the two libraries are not compatible. First, the types and unit of properties were different. Second, material names used in the library and the codes of the materials were different. Furthermore, there is no material library in Korean language. Thus, by comparing the basic library of DOE-2, the most commonly used energy analysis engine worldwide, and EnergyPlus regarding construction materials; this study will analyze the material data required for energy analysis and propose a way to effectively enter these using semantic web's ontology. This study is meaningful as it enhances the objective credibility of the analysis result when analyzing the energy, and as a conceptual study on the usage of ontology in the construction industry.

• Women's Health Nursing
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• v.19 no.1
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• pp.1-12
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• 2013

Purpose: This study was performed to propose an ontology methodology based on standardized nursing process as framework in obstetric and gynecologic nursing practice. Methods: The instrument used in this study was based on the nursing diagnosis classification established by North American Nursing Diagnosis Association (NANDA) (2009-2011), fifth edition of the Nursing Interventions Classification (NIC) (2008), forth edition of the Nursing Outcomes Classification (NOC) (2008) developed by Iowa State University and systematized nomenclature of medicine clinical terms (SNOMED CT). The nursing records data were collected from electronic medical records of one hospital from August to October 2010. Results: One hundred and forty-one nursing diagnosis statements used in obstetric and gynecologic nursing unit were linked standardized nursing classifications and constructed nursing diagnosis ontology including interoperability. Conclusion: Not only will this result be helpful to complete nurse's lack of knowledge and experience, it will also help to determine nursing diagnosis logically by using standardized nursing process. It will be utilized as the method to construct ontology including interoperability in other nursing units. It will be presented nursing interventions according to nursing diagnosis and thus will be easier to establish nursing planning. This can provide immediate feedback of the nursing process application.

• Knowledge Management Research
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• v.14 no.4
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• pp.75-86
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• 2013

The deeping interests and research toward Entrepreneurship, which is considered as an potential alternative for solving the continuing economic recession in the $21^{st}$ century, have grown. The process and methodology of the research could not be systematically arranged and the results of the research lack in efforts on the application of increasing suceess ratio in starting new business. This study adopted corpus methodology, through which we try to analyzes the knowledge structure in entrepreneurship research, derive essential concepts and the consisting domains in venture research. Based on the results of analysis, this study constructs the knowledge structure of venture research in a form of knowledge ontology. The results of the study could be a ground for entrepreneurship research and utilized as implication for a creation of construction for the entrepreneurship knowledge ontology.

• Journal of Physiology & Pathology in Korean Medicine
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• v.20 no.1
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• pp.202-208
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• 2006

The goal of this study is to develop knowledge representation method for the construction and evaluation of ontology for diagnosis in oriental medicine. To develop the expert system for decision making on diagnosis and treatment, the systematic and structural knowledge which can be processible in EMR(Electronic Medical Record) must be precedent, and the Computational Process which control the system as well. This study set up an ontology as a trial model to represent the oriental medical knowledge into the machine processible one. Protege 2.1 has been used to build the ontology, and the serialization format of our ontology is the XML document based on OWL. The components of oriental medical diagnosis was arranged with the combination of symptoms which belong to the certain symptom patterns. Then natural language which expresses the oriental medical diagnosis components were converted into the logical sentence, and individual characteristic symptoms into each values of specific properties. In addition to the study, the diagnosis software for oriental medicine was developed and it used the ontology which we developed. Sequently, we tested the software to confirm the appropriateness of ontology. The result of the test shows that diagnostic questions are automatically formulated according to the diagnosis components of this ontology and that as such diagnostic results are induced. Therefore, the ontology system in this study will be efficient to develop the diagnosis program and useful as a tool for doctors to make decision. But, it is not recommendable to apply the system to the clinical environment until the clear diagnosis standards are introduced, and the more reliable diagnosis program can be developed based on the more appropriate ontology mentioned above.

• Proceedings of the Korean Institute of Building Construction Conference
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• 2016.05a
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• pp.235-236
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• 2016

The importance of construction management has been increasing due to the fact that complex construction projects blend several different industries depending on the traits of the construction. This research was conducted to search for a method to enhance efficiency in cost management of construction project and meet the need for reusability of accumulated construction information. The process of detailed estimation and methodology for using standard unit price information has been developed to strengthen the interoperability in cost information by utilizing a standard classification system. The concept of ontology is proposed as a method of connecting construction information based on a standard breakdown structure to increasing the connectivity of the cost information in the construction project. Therefore, construction information knowledge framework is developed in order to improve the efficiency of the detailed estimation work process.

• Journal of the Korea Society of Computer and Information
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• v.19 no.11
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• pp.105-113
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• 2014

In this paper, we propose an OWL DL mapping rules for construction legal ontology based on the analyzed relationship between the structural features and elements of the statute. The mapping rule to be proposed is the method building the structure of the domestic statute, unique attribute of the statute, and reference relation between laws with TBox, and the legal sentence is analyzed, and the pattern type of the sentence is selected. It expresses with ABox. The proposed mapping rule is transformed to the information in which the computer can process the domestic legal document. It is usable for the legal knowledge base.

• Journal of the Korea Society of Computer and Information
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• v.15 no.5
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• pp.1-11
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• 2010

The success of semantic web depends largely on the semantic annotation which systematizes knowledge for the construction and production of ontology. Therefore, the efficiency of semantic annotation is very important in order to change many knowledge expressions and generate into ontology instances. In this paper, we presents a generation system of rule-based ontology instances which are produced accurately and efficiently via semantic annotation in conventional web sites. In conventional studies, the manual process is necessary for finding relevant information, comparing it with ontology, and entering information. We propose a new method that manages keyword data regarding extracted information and rule information separately. Thus, it is quite practical to extract information efficiently from various web documents by adding a small number of keywords and rules. The proposed method shows the possibility of ontology instance generation which reuses the rules and keywords from the various websites.