• 한국지능시스템학회:학술대회논문집
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• 한국퍼지및지능시스템학회 1997년도 춘계학술대회 학술발표 논문집
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• pp.252-255
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• 1997

In this paper, we will propose the methodology of data analysis using the fuzzy property set model. In real world, the data can be represented with the object. $\theta$. and the property, $\pi$, and its has-property relation, P. Then, the conceptual space can be defined with the chosen properties. Each object has a unique location in the conceptual space. In Fuzzy mode, the fuzzy property, and fuzzy conceptual space can be redefined. To analyze data using the fuzzy property set model, the rough set need to be defined in the fuzzy conceptual space.

• Journal of Information Technology Applications and Management
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• 제18권4호
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• pp.95-118
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• 2011

In developing information systems, conceptual modeling is among the most fundamental means. The importance attributed to conceptual modeling has not only given rise to a lot of modeling methods, but also to the "yet another modeling approach (YAMA)" syndrome and the "not another modeling approach (NAMA)" hysteria. Criticism of conceptual modeling methods usually targets their lacking of theoretical foundations. In response to such criticism, various approaches towards theoretical foundations of conceptual modeling have been proposed so far. One of the recent responses to the quest for theoretical foundations of conceptual modeling is the reference to the philosophical ontology. The currently most prominent of diverse approaches towards ontological foundations of conceptual modeling appears to be the Bunge-Wand-Weber (BWW) ontology. Recent approaches attempt to regard BWW ontology as another conceptual data model as well as a criterion for evaluating various conceptual models. However, unfortunately, relatively few researches have been made on interoperability between the Entity-Relationship (ER) model, which is the most dominant conceptual data model, and ontology based model. In this paper, we investigate the interoperability between ontology and the ER model. In detail we (i) reclassify components of ER model with respect to ontology concepts, (ii) identify some components that cannot be directly represented in ontology notation, and (iii) present alternative representations to the components to acquire ontologically clear ER diagrams. Additionally, we (iv) present a set of mapping rules for converting the ontologically clear ER diagram into the corresponding ontology. In a case study, we show the process of converting an ER diagram for a concise Project Management System (PMS) into the ontologically clear ER diagram and the corresponding ontology. We also describe an experiment that we undertook to test whether users understand the Ontologically-Clear ER diagram better.

• 전기전자학회논문지
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• 제7권2호
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• pp.144-155
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• 2003

본 논문에서는 객체 기술과 복잡한 구조적 데이터와 관련된 데이터베이스 구조를 효율적으로 표현하기 위한 통합 데이타 모델(UDM)이라고 하는 개념 데이터 모델을 제안한다. 이 모델은 E-R 모델, 의미 객체 모델, UML 등의 데이타 모델의 주요 기능을 데이타베이스 설계 관점에서 통합한 것이다. 이 모델은 시공간 멀티미디어 데이타의 복잡한 구조를 모델링하기 위해 제안된 객체-관계 모델을 단순화시키고 일부 기능을 확장시킨 버전이다. 이 모델은 현대적인 데이터베이스 응용의 주요한 의미적, 구조적인 정보의 표현을 지원하며, 관계, 객체-관계, 객체-지향, (반-)구조 데이터베이스 등 주요 논리적 데이터베이스 모델을 지원하도록 고안되었다. 데이터베이스 설계를 위한 도구로 통합 데이타 다이아그램(UDD)을 제안하며, 이 통합 데이타 모델로부터 논리적 뷰를 유도하기 위한 방법도 제안한다. 제안된 모델은 다양한 개념적 데이터베이스 설계를 위한 편리하고 실용적인 도구로 활용될 수 있다.

• 한국의류학회지
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• 제28권6호
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• pp.830-841
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• 2004

The necessity to understand shopping orientation is increasing. Yet, there has been few research that investigated the conceptual structure of clothing shopping orientation[CSO]. Therefore, the purpose of this study is to develop the conceptual structure of CSO. For that purpose, both documentary and empirical researches were conducted. The documentary research was conducted to develop a theoretical structure model as a basis for exploring the conceptual structure of CSO. The empirical research was conducted to identify and modify the theoretical model so as to develop a conceptual structure model. The data was analyzed using confirmatory factor analysis, exploratory factor analysis, and Pearson's correlation analysis. As a result, a conceptual structure model of CSO was developed. The model consisted of three hierarchical levels of dimensions; upper-dimensions, middle-dimensions and lower-dimensions. The upper-dimensions were composed of 'economic', 'hedonic', and 'convenient' dimensions. Each upper-dimension consisted of middle-dimensions and lower-dimensions. Confirmatory factor analysis was executed to assess the fitness and cross validity of the structure model.

• 한국도서관정보학회지
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• 제54권1호
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• pp.167-190
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• 2023

본 연구는 활동이론을 이론적 틀로 활용하여 연구데이터 큐레이션 모델을 분석한 문헌 연구로, 활동이론에서 사용하는 활동의 구성 요소들을 바탕으로 여러 연구데이터 큐레이션 모델을 분석했을 뿐만 아니라 연구데이터 큐레이션 활동을 수행하는데 있어서 도서관계에서 논의가 필요한 현안을 분석하였다. 그리고 이를 기반으로 새로운 연구데이터 큐레이션 개념 모델을 제안하였다. 본 연구는 기존에 제안된 5개의 디지털 큐레이션 생애주기모델이 어떻게 구성되어 있는지 분석하고 각각의 모델에서 산발적으로 제시되는 활동요인들을 분석하여 공통요인을 추출하고 새로운 모델로 통합하여 새로운 연구데이터 큐레이션 개념 모델을 제안하였다. 또한, 도서관 및 리포지토리에서 연구데이터 큐레이션 활동을 수행함에 있어서 고려해야 할 6가지의 현안들을 분석하고 논의하였다. 본 연구에서 제안되는 연구데이터 큐레이션 개념 모델은 총 10단계로 이루어져 있으며, 각 활동의 단계에서 고려해야 할 실천적 문제와 모순을 포함하고 있다.

• International Journal of Computer Science & Network Security
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• 제21권9호
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• pp.247-260
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• 2021

Data modeling is a process of developing a model to design and develop a data system that supports an organization's various business processes. A conceptual data model represents a technology-independent specification of structure of data to be stored within a database. The model aims to provide richer expressiveness and incorporate a set of semantics to (a) support the design, control, and integrity parts of the data stored in data management structures and (b) coordinate the viewing of connections and ideas on a database. The described structure of the data is often represented in an entity–relationship (ER) model, which was one of the first data-modeling techniques and is likely to continue to be a popular way of characterizing entity classes, attributes, and relationships. This paper attempts to examine the basic ER modeling notions in order to analyze the concepts to which they refer as well as ways to represent them. In such a mission, we apply a new modeling methodology (thinging machine; TM) to ER in terms of its fundamental building constructs, representation entities, relationships, and attributes. The goal of this venture is to further the understanding of data models and enrich their semantics. Three specific contributions to modeling in this context are incorporated: (a) using the TM model's five generic actions to inject processing in the ER structure; (b) relating the single ontological element of TM modeling (i.e., a thing/machine or thimac) to ER entities and relationships; and (c) proposing a high-level integrated, extended ER model that includes structural and time-oriented notions (e.g., events or behavior).

• 한국정보시스템학회지:정보시스템연구
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• 제7권1호
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• pp.181-208
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• 1998

In many literatures of model management, various schemes for representing model base schema have proposed. Ultimately, the goal is to arrive at a set of mutually supportive and synergistic methodologies and tools for the modeling problem domain and model base design. This paper focus on how best to structure and represent conceptual model of problem domain and schema of model base. Semantic concepts and modeling constructs are valuable conceptual tools for understanding the structural relationships and constraints involved in an model management environment. To this end, we reviewed the model management literature, and analyzed the constructs of modeling tools of data model management graph-based approach. Although they have good tools but most of them are not enough for the representation of structural relationships and constraints. So we wanted more powerful tools which can represent diverse constructs in a decision support modeling and model base schema design. For the design of a model base, we developed object modeling framework which uses Object Modeling Techniques (OMT). In Object Modeling Framework, model base schema are classified into conceptual schema, logical schema, and physical schema. The conceptual schema represents the user's view of problem domain, and the logical schema represents a model formatted by a particular modeling language. The schema design, this paper proposes an extension of Object Model to overcome some of the limitations exhibited by the OMT. The proposed tool, Extended Object Model(EOM) have diverse constructs for the representation of decision support problem domain and conceptual model base schema.

• 한국인터넷방송통신학회논문지
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• 제15권4호
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• pp.231-237
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• 2015

XML은 다양한 언어들을 이용하여 문서의 구조나 형식을 논리적으로 정의하고 있지만, 각각의 언어들은 서로 다른 구조와 문법을 채택하고 있어 실세계의 데이터의 의미나 데이터 사이의 관계를 표현하는 개념적 모델의 도구로 사용하기 어렵다. 본 논문은 XML 스키마 문서를 개념적으로 모델링할 수 있는 기법인 CMXML을 제안한다. CMXML은 XML을 형식으로(formal)으로 정의하고, 형식에 의해 각 요소들을 그래픽으로 표현하는 방법을 제시하고, 본 모델의 타당성을 보여주기 위해 CMXML으로 모델링한 개념적 모델을 논리적 모델인 XML 스키마로 매핑하는 기법을 제시한다.

• 대기
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• 제26권2호
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• pp.215-226
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• 2016

Conceptual models to analyze both typhoon and Changma using products extracted by the GEO-KOMPSAT-2A (GK-2A) are suggested in this study. The GK-2A which is scheduled to be launched in 2018 has a high resolution, 16 channels, and 52 products. This means GK-2A is expected to obtain high quality images and products, which can detect severe weather earlier than the Communications, Ocean and Meteorological Satellite (COMS). Since there are not enough conceptual models for typhoon and Changma using satellite images and products, our conceptual model can increase both the applicability of satellite data and the accuracy of analysis. In the conceptual model, typhoons are classified as three types by prevailing factors; 1) heavy-rainfall type, 2) wind type, and 3) complex type. For Changma, two types are divided by the characteristics; band type and heavy-rainfall type. Among the high resolution 52 products, each type of typhoon and Changma are selected. In addition, the numerical products and dynamic factors are considered in order to improve conceptual models.

• Journal of Computing Science and Engineering
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• 제4권4호
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• pp.291-312
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• 2010

The last decades a large amount of research has been done in the genomics domain which has and is generating terabytes, if not exabytes, of information stored globally in a very fragmented way. Different databases use different ways of storing the same data, resulting in undesired redundancy and restrained information transfer. Adding to this, keeping the existing databases consistent and data integrity maintained is mainly left to human intervention which in turn is very costly, both in time and money as well as error prone. Identifying a fixed conceptual dictionary in the form of a conceptual model thus seems crucial. This paper presents an effort to integrate the mutational data from the established genomic data source HGMD into a conceptual model driven database HGDB, thereby providing useful lessons to improve the already existing conceptual model of the human genome.