• 정보처리학회논문지D
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• 제12D권6호
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• pp.837-848
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• 2005

다중축척 공간데이터베이스란 동일한 현실 공간을 여러 축척으로 저장한 것으로, 기존에 구축된 원시 공간 데이터베이스로부터 유도될 수 있다. 이 유도과정에서 원시 데이터베이스에 있던 기하 및 위상관계는 변형이 되고, 이 관계 변형은 유도된 데이터베이스의 무결성을 보장하지 못하는 원인이 되므로, 유도과정이 수행된 후에는 반드시 유도된 데이터베이스와 원시 데이터베이스의 관계 일관성을 조사해야한다. 이 논문에서는 원시 데이터베이스와 유도된 다중축척 데이터베이스간의 위상 관계 일관성을 평가하는 방법을 제시하겠다. 특히, 2차원 공간객체가 1차원으로 축소되었을 때 위상관계의 일관성을 평가하는 방법을 제한할 것이며, 이 평가 방법들의 구현에 대해서 기술하고, 사례를 이용하여 구현결과를 기술하겠다.

• 한국전산구조공학회:학술대회논문집
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• 한국전산구조공학회 2007년도 정기 학술대회 논문집
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• pp.725-730
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• 2007

A framework of multi layered database is proposed for the integrated operation of civil infrastructure information in this study. The multi-layered database is a logically integrated database composed of standardized information layers. The framework of multi-layered database is defined by three axes, national assets, lifetime, and data levels. The axis of national assets indicates civil infrastructures such as bridges, dams, tunnels and power plants that can be considered as national key structures. The axes of lifetime and data levels indicate the standardized information layers generated from the life-phase of civil infrastructure and the priority of data in the information layers, respectively. The standardized information layers are basically composed of reusable data sets defined by information models. A prototype of standard database for steel bridges is constructed based on the framework as a proof of concept. Demonstration examples such as data consistency check and automatic generation of a FEA model show that the proposed concept can assure the sustainable interoperability of civil infrastructure information as well as design information of steel bridges.

• Management Science and Financial Engineering
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• 제7권1호
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• pp.27-39
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• 2001

The multi-projective model considers attributes and the relationships among attributes called projections. The critical features of the multi-projective model are the way of relating attributes in the description of the system, the way of reasoning incomplete projections, and the determination of connected patterns between projection. In order to get a full picture of the system, we build a set of projections. The multi-projective model can be thought of as projections of a multi-dimensional reality onto simplified “model space”. The multi-projective database modeling approach used in this paper unified the ideas and terminology of various database models. Most importantly, the multi-projective modeling is presented as a tool of database design in the relational and other database models.

• Asia pacific journal of information systems
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• 제13권1호
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• pp.47-72
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• 2003

It is important to retrieve information that a user requires on the web. The web is an open system. The amount of information is increasing rapidly. While each of information was compiled into the database piece at a single platform in the past, it is now compiled into complicated structure at a multi-platform. Restructuring the multi-platform database is needed to efficiently retrieve information. MIRAS(Meta Information Retrieval Agent System) has a multi-platform database on web. This study applies the classification of the existent site's categories to restructure the database systematically. The empirical analysis shows that the suggested method is effective for information retrieval and multi-platform database restructuring. This study helps users to save on time-cost of searching information.

• 한국전산구조공학회논문집
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• 제20권3호
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• pp.393-404
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• 2007

본 연구에서는 교량정보의 통합 운용을 지원하기 위해 멀티레이어 데이터베이스의 프레임워크를 제시하였다. 멀티레이어 데이터베이스란 표준화된 정보 레이어로 이루어진 논리적으로 통합된 데이터베이스를 말한다. 표준화된 정보 레이어는 한 부류로 구분할 수 있는 데이터 집합을 나타내며, 정보모델에 의해 정의된다. 본 연구에서 제시한 교량의 멀티레이어 데이터베이스 개념은 구조요소의 분류를 나타내는 정보체계를 기반으로 하며, 구조요소의 분류체계에 따른 코드를 사용함으로써 여러 정보계층에 분포된 데이터를 통합하도록 하였다. 또한 멀티레이어 데이터베이스 프레임워크의 한 축으로서 데이터 레벨을 설정하였다. 데이터 레벨은 정보계층에 포함된 데이터들의 재활용성에 따른 중요도를 의미하며, 이에 따라 정보모델의 세분화되는 정도를 정의하여 방대한 양의 교량정보 데이터베이스 구축을 위한 효과적인 전략수립이 가능하도록 하였다. 제시된 개념의 검증을 위해 객체지향개념의 3-D 형상정보 계층과 구조계산서 정보계층으로 이루어진 시범 데이터베이스를 구축하였다. 또한 두 계층으로 분산되어 있는 데이터의 일치여부를 자동으로 검토하는 실험을 통하여 본 연구에서 제시된 멀티레이어 데이터베이스 개념이 교량정보를 관리하는데 있어 정보의 무결성과 일관성을 보장할 수 있음을 보였다.

• 한국전자거래학회지
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• 제3권1호
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• pp.23-41
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• 1998

In a centralized database system, all system components reside at a single platform. In recent years there has been a rapid trend toward the integration of information systems over multiple sites that are interconnected via a communication network, and users' needs are changed to integration of multiple information sites. Multi database System is one of solutions for integrating distributed heterogeneous databases. However the problems in multi database system are restriction in distributed environment support, limitation in integrating heterogeneous media type data, static integration, and data-only of integration. In order to solve these problems, we propose a hybrid database integration model, HyDIM. HyDIM is used for the integrating legacy multimedia data, adopting CORBA, MDS, and mediator. We demonstrate a prototype system far PDM application domain.

• Journal of Information Processing Systems
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• 제14권3호
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• pp.709-726
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• 2018

Database classification is an important preprocessing step for the multi-database mining (MDM). In fact, when a multi-branch company needs to explore its distributed data for decision making, it is imperative to classify these multiple databases into similar clusters before analyzing the data. To search for the best classification of a set of n databases, existing algorithms generate from 1 to ($n^2-n$)/2 candidate classifications. Although each candidate classification is included in the next one (i.e., clusters in the current classification are subsets of clusters in the next classification), existing algorithms generate each classification independently, that is, without taking into account the use of clusters from the previous classification. Consequently, existing algorithms are time consuming, especially when the number of candidate classifications increases. To overcome the latter problem, we propose in this paper an efficient approach that represents the problem of classifying the multiple databases as a problem of identifying the connected components of an undirected weighted graph. Theoretical analysis and experiments on public databases confirm the efficiency of our algorithm against existing works and that it overcomes the problem of increase in the execution time.

• 디지털융복합연구
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• 제15권10호
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• pp.243-251
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• 2017

효과적인 데이터 분석 및 활용을 위해서는 빅 데이터를 내부 데이터와 유연하게 연계할 수 있는 방안이 필요하다. 빅 데이터 분석 정보를 내부 정보시스템과 연계시키기 위한 방안으로서 본 연구는 다차원 이벤트 온톨리지를 제시하였다. 이를 위해서 먼저 빅 데이터 분석 정보를 이벤트 모형을 사용하여 온톨리지로 표현하고, 다차원 데이터베이스 또한 OWL-DL 온톨리지로 변환하여 표현하였다. 다차원 이벤트 온톨리지에서 빅 데이터 분석정보들은 차원 계층구조를 통하여 다차원 데이터베이스에 저장된 모든 개체들에게 공유되는데, 본 연구에서는 이를 이벤트의 하향공유, 상향 공유 및 복합 이벤트 공유로 구분한다. 이들 정보공유 유형별로 빅 데이터 분석 정보의 공유 및 활용 방안들을 제시하였으며, Protege를 사용하여 시험적으로 구현하였다. 본 연구는 외부의 빅 데이터 분석 정보를 내부의 다차원 데이터베이스와 연계하는 방안을 실험적으로 제시하였다는 점에서 의의를 가진다고 할 수 있다.

• Journal of Computing Science and Engineering
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• 제5권3호
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• pp.183-196
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• 2011

There has recently been a surge of interest in relational database mining that aims to discover useful patterns across multiple interlinked database relations. It is crucial for a learning algorithm to explore the multiple inter-connected relations so that important attributes are not excluded when mining such relational repositories. However, from a data privacy perspective, it becomes difficult to identify all possible relationships between attributes from the different relations, considering a complex database schema. That is, seemingly harmless attributes may be linked to confidential information, leading to data leaks when building a model. Thus, we are at risk of disclosing unwanted knowledge when publishing the results of a data mining exercise. For instance, consider a financial database classification task to determine whether a loan is considered high risk. Suppose that we are aware that the database contains another confidential attribute, such as income level, that should not be divulged. One may thus choose to eliminate, or distort, the income level from the database to prevent potential privacy leakage. However, even after distortion, a learning model against the modified database may accurately determine the income level values. It follows that the database is still unsafe and may be compromised. This paper demonstrates this potential for privacy leakage in multi-relational classification and illustrates how such potential leaks may be detected. We propose a method to generate a ranked list of subschemas that maintains the predictive performance on the class attribute, while limiting the disclosure risk, and predictive accuracy, of confidential attributes. We illustrate and demonstrate the effectiveness of our method against a financial database and an insurance database.

• 한국감성과학회:학술대회논문집
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• 한국감성과학회 2000년도 춘계 학술대회 및 국제 감성공학 심포지움 논문집 Proceeding of the 2000 Spring Conference of KOSES and International Sensibility Ergonomics Symposium
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• pp.120-125
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• 2000

We propose a semi-automatic and dynamic indexing algorithm for multi-media database(e.g. movie files, audio files), which are difficult to create indexes expressing their emotional or abstract contents, according to user's sensitivity by using user's histories of access to database. In this algorithm, we simply categorize data at first, create a vector space of each user's interest(user model) from the history of which categories the data belong to, and create vector space of each data(title model) from the history of which users the data had been accessed from. By continuing the above method, we could create suitable indexes, which show emotional content of each data. In this paper, we define the recurrence formulas based on the proposed algorithm. We also show the effectiveness of the algorithm by simulation result.