• The KIPS Transactions:PartD
• /
• v.12D no.6 s.102
• /
• pp.837-848
• /
• 2005

A multi-scale database is a set of spatial database, covering same geographic area with different scales and it can be derived from pre-existing databases. In the derivation processes of a new multi-scale spatial database, the geometries and topological relations on the source database can be transformed and the transformation can be the cause of the lack of integrity Therefore, it is necessary to assess the transformation whether it is consistent or not after the derivation process of a new multi-scale database. Thus, we propose assessment methods for the topological consistency between a source database and a derived multi-scale database in this paper. In particular, we focus on the case that 2-dimensional objects are collapsed to 1-dimensional ones in the derivation process of a multi-scale database. We also describe implementation of the assessment methods and show the results of the implementation with experimental data.

• Proceedings of the Computational Structural Engineering Institute Conference
• /
• 2007.04a
• /
• pp.725-730
• /
• 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
• /
• v.7 no.1
• /
• pp.27-39
• /
• 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
• /
• v.13 no.1
• /
• pp.47-72
• /
• 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.

• Journal of the Computational Structural Engineering Institute of Korea
• /
• v.20 no.3
• /
• pp.393-404
• /
• 2007

A concept of multi-layered database is proposed for the integrated operation of bridge information in this study. The multi-layered database is a logically integrated database composed of standardized information layers. The standardized information layers represent the data sets that can be unified, and they are defined by standardized information models. Classification system of bridge component was used as a basis of the multi-layered database, and code system based on the classification system was employed as a key integrator to manipulate the distributed data located on the different information layers. In addition, data level indicating priorities of information layers was defined to support strategic planning of the multi-layered database construction. As a proof of concept, a prototype of multi-layered database for object-oriented 3-D shape information and structural calculation document was built. Data consistency check of the semantically same data in the two different information layer was demonstrated, It is expected that the proposed concept can assure the integrity and consistency of information in the bridge information management.

• The Journal of Society for e-Business Studies
• /
• v.3 no.1
• /
• pp.23-41
• /
• 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
• /
• v.14 no.3
• /
• pp.709-726
• /
• 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.

• Journal of Digital Convergence
• /
• v.15 no.10
• /
• pp.243-251
• /
• 2017

As external data have become important corporate information resources, there are growing needs to combine them with internal data. This paper proposes an ontology-based scheme to combine external data with multi-dimensional databases, which shall be called multi-dimensional event ontology. In the ontology, external data are represented as events. Event characteristics such as actors, places, times, targets are linked to dimensions of a multi-dimensional database. By mapping event characteristics to database dimensions, external event data are shared via multi-dimensional hierarchies. This paper proposes rules to synchronize information sharing in multi-dimensional event ontology such as upward event information sharing, downward event information sharing and complex event information sharing. These rules are implemented using Protege. This study has a value in suggesting Big Data information sharing processes using an event database framework.

• Journal of Computing Science and Engineering
• /
• v.5 no.3
• /
• pp.183-196
• /
• 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.

• Proceedings of the Korean Society for Emotion and Sensibility Conference
• /
• 2000.04a
• /
• pp.120-125
• /
• 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.