• Proceedings of the Korean Information Science Society Conference
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• 2003.10b
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• pp.199-201
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• 2003

온라인 분석처리 시스템의 핵심 기술인 큐브를 효과적으로 산출하기 위한 많은 연구들이 이루어 졌다. 이러한 연구는 크게 온라인 분석처리 시스템의 결과 데이터를 저장하는 방식에 의해 MOLAP과 ROLAP으로 구분하여 이루어 졌다. 최근에 온라인 분석처리 시스템에서 큐브 산출에 대한 연구로 다중키 엑세스를 효율적으로 처리하는 다차원 파일 구조를 사용하여 집계 연산의 효율을 높이는 연구가 이루어졌다. 본 논문은 이러한 연구들을 바탕으로 다차원 파일 구조를 사용하여 효과적으로 큐브를 산출하고 결과 값을 미리 저장하는 일반적인 방법을 제안한다.

• Journal of KIISE:Databases
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• v.30 no.3
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• pp.225-236
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• 2003

MOLAP systems store data in a multidimensional away called a 'cube' and access them using way indexes. When a cube is placed into disk, it can be Partitioned into a set of chunks of the same side length. Such a cube storage scheme is called the chunk-based MOLAP cube storage scheme. It gives data clustering effect so that all the dimensions are guaranteed to get a fair chance in terms of the query processing speed. In order to achieve high space utilization, sparse chunks are further compressed. Due to data compression, the relative position of chunks cannot be obtained in constant time without using indexes. In this paper, we propose a bitmap index for chunk-based MOLAP cubes. The index can be constructed along with the corresponding cube generation. The relative position of chunks is retained in the index so that chunk retrieval can be done in constant time. We placed in an index block as many chunks as possible so that the number of index searches is minimized for OLAP operations such as range queries. We showed the proposed index is efficient by comparing it with multidimensional indexes such as UB-tree and grid file in terms of time and space.

• Journal of Korea Multimedia Society
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• v.10 no.9
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• pp.1093-1105
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• 2007

This paper presents a multidimensional type inheritance indexing technique (MD-TIX) for XML databases. We use a multidimensional file organization as the index structure. In conventional XML database indexing techniques using one-dimensional index structures, they do not efficiently handle complex queries involving both nested elements and type inheritance hierarchies. We extend a two-dimensional type hierarchy indexing technique(2D-THI) for indexing the nested elements of XML databases. 2D-THI is an indexing scheme that deals with the problem of clustering elements in a two-dimensional domain space consisting of the key value domain and the type identifier domain for indexing a simple element in a type hierarchy. In our extended scheme, we handle the clustering of the index entries in a multidimensional domain space consisting of a key value domain and multiple type identifier domains that include one type identifier domain per type hierarchy on a path expression. This scheme efficiently supports queries that involve search conditions on the nested element represented by an extended path expression. An extended path expression is a path expression in which every type hierarchy on a path can be substituted by an individual type or a subtype hierarchy.

• The Transactions of the Korea Information Processing Society
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• v.7 no.8
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• pp.2298-2309
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• 2000

This paper proposes the multidimensioa! nested attribute indexing techniques (MD- NAI) in object-oriented databases using a multidimensional index structure. Since most conventional indexing techniques for object oriented databases use a one-dimensional index stnlcture such as the B-tree, they do not often handle complex qUlTies involving both nested attributes and class hierarchies. We extend a tunable two dimensional class hierachy indexing technique(2D-CHI) for nested attributes. The 2D-CHI is an indexing scheme that deals with the problem of clustering ohjects in a two dimensional domain space that consists of a kev attribute dOI11'lin and a class idmtifier domain for a simple attribute in a class hierachy. In our extended scheme, we construct indexes using multidimensional file organizations that include one class identifier domain per class hierarchy on a path expression that defines the indexed nested attribute. This scheme efficiently suppoI1s queries that involve search conditions on the nested attribute represcnted by an extcnded path expression. An extended path expression is a one in which a class hierarchy can be substituted by an indivisual class or a subclass hierarchy in the class hierarchy.

• Proceedings of the Korea Information Processing Society Conference
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• 2007.05a
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• pp.97-100
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• 2007

본 논문에서는 다차원 파일구조를 주어진 질의 패턴에 의해 최적으로 구성할 수 있는 방법을 제시한다. 지금까지의 다차원 파일구조는 응용 시스템에서 주어지는 질의의 패턴을 고려하지 않고 다차원 파일구조를 구성하는 애트리뷰트들의 클러스터링 정도를 동일하게 취급하였다. 그러나 다차원 파일구조를 이용하는 대부분의 응용 시스템에서 구성 애트리뷰트들 사이의 액세스 정도를 크게 다르게 하는 질의 패턴을 보인다. 따라서 본 논문에서는 다차원 파일구조의 응용 시스템에서 주어지는 질의 정보를 이용하여 각 구성 애트리뷰트들 사이의 클러스터링 정도를 각각 다르게 반영함으로써 최적이 되는 다차원 파일구조를 구성하는 방안을 제시한다. 먼저 질의처리의 성능이 질의 패턴에 주어진 질의 영역의 모양과 다차원 파일구조의 도메인 공간의 분할 상태를 나타내는 페이지 영역의 모양 사이의 유사성에 따라 크게 영향 받음을 보이고, 이러한 특성을 이용하여 수학적 분석을 통하여 제안된 기법의 이론적인 배경을 증명한다.

• International Journal of Contents
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• v.3 no.2
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• pp.6-17
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• 2007

Emerging modem database applications require multi-dimensional index structures to provide high performance for data retrieval. In order for a multi-dimensional index structure to be integrated into a commercial database system, efficient techniques that provide transactional access to data through this index structure are necessary. The techniques must support all degrees of isolation offered by the database system. Especially degree 3 isolation, called "no phantom read," protects search ranges from concurrent insertions and the rollbacks of deletions. In this paper, we propose a new phantom protection method for multi-dimensional index structures that uses a multi-level grid technique. The proposed mechanism is independent of the type of the multi-dimensional index structure, i.e., it can be applied to all types of index structures such as tree-based, file-based, and hash-based index structures. In addition, it has a low development cost and achieves high concurrency with a low lock overhead. It is shown through various experiments that the proposed method outperforms existing phantom protection methods for multi-dimensional index structures.

• Proceedings of the Korea Information Processing Society Conference
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• 2014.04a
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• pp.77-80
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• 2014

최근 컴퓨터와 인터넷 이용의 확산, 스마트폰을 포함한 스마트 기기의 보급과 소셜 네트워크 이용의 확대, 위치 기반의 다양한 서비스 확대 등으로 처리해야 할 데이터 크기가 증가하는 추세이다. 이에 따라 대용량 데이터에 대한 처리가 큰 이슈로 떠오르고 있다. 그로 인해 대용량 데이터 처리를 위한 큰 규모의 분산 컴퓨팅 환경을 지원하는 프레임워크인 하둡이 개발되었으며 많은 기업에서 이를 활용하고 있는 추세이다. 하지만 대용량 데이터 중 영상, 의료, 센서 데이터 등 다차원 데이터 처리에 관한 연구는 미비한 상태이다. 기존의 다차원 데이터 처리를 위해 다양한 다차원 인덱스가 제안되었지만, 대용량 다차원 데이터 처리는 단일머신에서는 비효율적인 단점이 있다. 본 논문에서는 다차원 인덱스 기법인 그리드 파일을 하둡의 분산 병렬 처리 모델인 맵리듀스를 기반으로 생성하는 기법을 제안한다. 또한 앞서 생성된 그리드 파일을 가지고 맵리듀스를 이용한 질의처리 방법을 제안 한다. 이로 인해 단일머신에서의 그리드 파일 생성을 병렬처리 함으로써 생성 시간을 단축시키고 질의 처리 또한 맵리듀스를 이용하여 병렬 처리 함으로써 질의 시간 단축을 예상한다.

• Journal of KIISE:Computer Systems and Theory
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• v.32 no.1
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• pp.9-20
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• 2005

Recently, the MPEG-7 standard a multimedia content description standard is wide]y used for content based image/video retrieval systems. However, since the descriptors standardized in MPEG-7 are usually multidimensional and the problem called 'Curse of dimensionality', previously proposed indexing methods(for example, multidimensional indexing methods, dimensionality reduction methods, filtering methods, and so on) could not be used to effectively index the multimedia database represented in MPEG-7. This paper proposes an efficient multimedia data indexing mechanism reflecting the characteristics of MPEG-7 visual descriptors. In the proposed indexing mechanism, the descriptor is transformed into a histogram of some attributes. By representing the value of each bin as a binary number, the histogram itself that is a visual descriptor for the object in multimedia database could be represented as a bit string. Bit strings for all objects in multimedia database are collected to form an index file, bitmap index, in the proposed indexing mechanism. By XORing them with the descriptors for query object, the candidate solutions for similarity search could be computed easily and they are checked again with query object to precisely compute the similarity with exact metric such as Ll-norm. These indexing and searching mechanisms are efficient because the filtering process is performed by simple bit-operation and it reduces the search space dramatically. Upon experimental results with more than 100,000 real images, the proposed indexing and searching mechanisms are about IS times faster than the sequential searching with more than 90% accuracy.

• Journal of Korea Multimedia Society
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• v.9 no.3
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• pp.265-278
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• 2006

This paper presents a two-dimensional type inheritance hierarchy index(2D-THI) for XML databases. XML Schema is one of schema models for the XML documents supporting. The type inheritance. The conventional indexing techniques for XML databases can not support XML queries on type inheritance hierarchies. We construct a two-dimensional index structure using multidimensional file organizations for supporting type inheritance hierarchy in XML queries. This indexing technique deals with the problem of clustering index entries in the two-dimensional domain space that consists of a key element domain and a type identifier domain based on the user query pattern. This index enhances query performance by adjusting the degree of clustering between the two domains. For performance evaluation, we have compared our proposed 2D-THI with the conventional class hierarchy indexing techniques in object-oriented databases such as CH-index and CG-tree through the cost model. As the result of the performance evaluations, we have verified that our proposed two-dimensional type inheritance indexing technique can efficiently support the query Processing in XML databases according to the query types.

• Proceedings of the KAIS Fall Conference
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• 2003.11a
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• pp.223-230
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• 2003

Feature-based similarity retrieval has become an important research issue in multimedia database systems. The features of multimedia data are useful for discriminating between multimedia objects (e 'g', documents, images, video, music score, etc.). For example, images are represented by their color histograms, texture vectors, and shape descriptors, and are usually high-dimensional data. The performance of conventional multidimensional data structures(e'g', R- Tree family, K-D-B tree, grid file, TV-tree) tends to deteriorate as the number of dimensions of feature vectors increases. The R＊-tree is the most successful variant of the R-tree. In this paper, we propose a SOM-based R＊-tree as a new indexing method for high-dimensional feature vectors.The SOM-based R＊-tree combines SOM and R＊-tree to achieve search performance more scalable to high dimensionalities. Self-Organizing Maps (SOMs) provide mapping from high-dimensional feature vectors onto a two dimensional space. The mapping preserves the topology of the feature vectors. The map is called a topological of the feature map, and preserves the mutual relationship (similarity) in the feature spaces of input data, clustering mutually similar feature vectors in neighboring nodes. Each node of the topological feature map holds a codebook vector. A best-matching-image-list. (BMIL) holds similar images that are closest to each codebook vector. In a topological feature map, there are empty nodes in which no image is classified. When we build an R＊-tree, we use codebook vectors of topological feature map which eliminates the empty nodes that cause unnecessary disk access and degrade retrieval performance. We experimentally compare the retrieval time cost of a SOM-based R＊-tree with that of an SOM and an R＊-tree using color feature vectors extracted from 40, 000 images. The result show that the SOM-based R＊-tree outperforms both the SOM and R＊-tree due to the reduction of the number of nodes required to build R＊-tree and retrieval time cost.