• 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.

• The KIPS Transactions:PartB
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• v.8B no.5
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• pp.533-538
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• 2001

In this paper, we extend FARGs single mode attribute to multiple attributes for real image application and present a new CBIR using FMARG(Fuzzy Multiple Attribute Relational Graph), which can handle queries involving multiple attributes, not only object label, but also color, texture and spatial relation. In the experiment using the synthetic image database of 1,024 images and the natural image database of 1.026 images built from NETRA database and Corel Draw, the proposed approach shows 6~30% recall increase in the synthetic image database and a good performance, at the displacements and the retrieved number of similar images in the natural image database, compared with the single attribute approach.

• The Journal of Society for e-Business Studies
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• v.3 no.1
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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 the military operations research society of Korea
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• v.23 no.2
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• pp.85-102
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• 1997

There have been several research efforts to support interoperability among multiple databases. In integrating multiple databases, we must resolve schema conflicts due to the heterogeneity in databases. To resolve these conflicts, not only meta-data for database schemas but also general knowledge expressing the real world meanings associated with the database schemas are required. This paper presents a uniform representation method for relational schema and general knowledge base that is composed, among other things, of concept hierarchy and thematic roles in relationship, using the knowledge representation language Lk. This representation method has a flexible descriptive power which facilitates concepts to be expressed at different levels of granularity and can describe knowledge expressed in Lk are used for input of the next step, such as conflict resolution and query processing of multiple database.

• Proceedings of the KSRS Conference
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• 2004.10a
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• pp.302-305
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• 2004

The aim of this study is to apply and crossvalidate a spatial logistic multiple-regression model at Boun, Korea, using a Geographic Information System (GIS). Landslide locations in the Boun area were identified by interpretation of aerial photographs and field surveys. Maps of the topography, soil type, forest cover, geology, and land-use were constructed from a spatial database. The factors that influence landslide occurrence, such as slope, aspect, and curvature of topography, were calculated from the topographic database. Texture, material, drainage, and effective soil thickness were extracted from the soil database, and type, diameter, and density of forest were extracted from the forest database. Lithology was extracted from the geological database and land-use was classified from the Landsat TM image satellite image. Landslide susceptibility was analyzed using landslide-occurrence factors by logistic multiple-regression methods. For validation and cross-validation, the result of the analysis was applied both to the study area, Boun, and another area, Youngin, Korea. The validation and cross-validation results showed satisfactory agreement between the susceptibility map and the existing data with respect to landslide locations. The GIS was used to analyze the vast amount of data efficiently, and statistical programs were used to maintain specificity and accuracy.

• Genomics & Informatics
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• v.3 no.3
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• pp.53-62
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• 2005

MicroRNAs play an important role in regulating gene expression, but their target identification is a difficult task due to their short length and imperfect complementarity. Burge and coworkers developed a program called TargetScan that allowed imperfect complementarity and established a procedure favoring targets with multiple binding sites conserved in multiple organisms. We improved their algorithm in two major aspects - (i) using well-defined UTR (untranslated region) database, (ii) examining the extent of conservation inside the 3' UTR specifically. Average length in our UTR database, based on the ECgene annotation, is more than twice longer than the Ensembl. Then, TargetScan was used to identify putative binding sites. The extent of conservation varies significantly inside the 3' UTR. We used the 'tight' tracks in the UCSC genome browser to select the conserved binding sites in multiple species. By combining the longer 3' UTR data, TargetScan, and tightly conserved blocks of genomic DNA, we identified 107 putative target genes with multiple binding sites conserved in multiple species, of which 85 putative targets are novel.

• Proceedings of the Korea Contents Association Conference
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• 2003.05a
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• pp.356-360
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• 2003

There have been many considerations to develop new content services that integrate a variety of contents databases being already constructed and then produce new content services which are more valuable than existing services in many applications such as Internet portal, EC, and CRM. By doing the above thing, the burden of searching databases to access interesting databases and service applications can be reduced and the database availability of users is also enhanced through a single view integrating multiple contents database. This paper presents implementation details of the query processing system that is a core component of the database integration system, which can construct a virtual database that integrates databases being managed by multiple heterogeneous database systems using XML data model and support a quay facility on the integrated database.

• Genomics & Informatics
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• v.15 no.1
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• pp.19-27
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• 2017

Understanding complex relationships among heterogeneous biological data is one of the fundamental goals in biology. In most cases, diverse biological data are stored in relational databases, such as MySQL and Oracle, which store data in multiple tables and then infer relationships by multiple-join statements. Recently, a new type of database, called the graph-based database, was developed to natively represent various kinds of complex relationships, and it is widely used among computer science communities and IT industries. Here, we demonstrate the feasibility of using a graph-based database for complex biological relationships by comparing the performance between MySQL and Neo4j, one of the most widely used graph databases. We collected various biological data (protein-protein interaction, drug-target, gene-disease, etc.) from several existing sources, removed duplicate and redundant data, and finally constructed a graph database containing 114,550 nodes and 82,674,321 relationships. When we tested the query execution performance of MySQL versus Neo4j, we found that Neo4j outperformed MySQL in all cases. While Neo4j exhibited a very fast response for various queries, MySQL exhibited latent or unfinished responses for complex queries with multiple-join statements. These results show that using graph-based databases, such as Neo4j, is an efficient way to store complex biological relationships. Moreover, querying a graph database in diverse ways has the potential to reveal novel relationships among heterogeneous biological data.

• Journal of Korea Multimedia Society
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• v.22 no.2
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• pp.225-230
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• 2019

There are several methods which efficiencies of database are uprise. One of the well-known methods is that segments of database satisfying a query was rapidly accessed and processed. So if it is possible to search completely parallel multiple database segment types which satisfy a query, the response time of the query will be reduced. The matter of obtaining CPS(Completely Parallel Searchable) distribution without redundancy can be viewed as graph theoretic problem, and the operation of ring sum on the graph is used for CPS. In this paper, the parallel algorithm is proposed.

• Journal of Information Processing Systems
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• v.14 no.3
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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.