• Proceedings of the Korea Information Processing Society Conference
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• 2006.05a
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• pp.35-38
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• 2006

데이터 웨어하우스에서는 OLAP(On-Line Analytical Processing) 연산을 제공하기 위해 다차원 데이터를 큐브의 형태로 관리한다. 특히, 공간 차원과 같이 데이터 큐브의 차원에 개념 계층이 존재하는 경우 사용자는 특정 계층에 대한 집계 결과를 요구한다. 기조의 데이터 큐브의 구조들은 차원의 개념 계층을 지원하지 못하거나 지원하더라도 시간이나 공간적 비용에 대해 비효율적이다. 본 논문에서는 공간 데이터 웨어하우스에서 공간 개념 계층을 이용하여 효율적인 계층별 영역 집계연산을 지원하는 공간 데이터 큐브를 제안한다. 이는 개념 계층을 DAG(Directed Acyclic Graph) 형태로 표현하여 구성된 여러 개의 차원들을 공간차원의 지역성을 기준으로 연결한 구조이다. 이러한 구조를 갖는 큐브를 이용하면, 데이터 검색 시 상위 계층부터 아래 방향으로 탐색하기 때문에 각 차원에 대한 효율적인 검색이 가능하다. 특히, 공간 개념 계층에 대한 DAG를 이용하면, 공간적 지역성에 따른 영역 검색을 지원할 수 있다. 성능평가에서 개념 계층이 적용된 질의에 대한 실험을 통해 제안 기법이 기존 기법들에 비해 저장 공간 효율성 및 질의 응답 성능이 우수함을 증명한다.

• Journal of Korea Multimedia Society
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• v.12 no.10
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• pp.1386-1396
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• 2009

Most decision support functions of spatial data warehouse rely on the OLAP operations upon a spatial cube. Meanwhile, higher performance is always guaranteed by indexing the cube, which stores huge amount of pre-aggregated information. Hierarchical Dwarf was proposed as a solution, which can be taken as an extension of the Dwarf, a compressed index for cube structures. However, it does not consider the spatial dimension and even aggregates incorrectly if there are redundant values at the lower levels. OLAP-favored Searching was proposed as a spatial hierarchy based OLAP operation, which employs the advantages of R-tree. Although it supports aggregating functions well against specified areas, it ignores the operations on the spatial dimensions. In this paper, an indexing approach, which aims at utilizing the concept hierarchy of the spatial cube for decision support, is proposed. The index consists of concept hierarchy trees of all dimensions, which are linked according to the tuples stored in the fact table. It saves storage cost by preventing identical trees from being created redundantly. Also, it reduces the OLAP operation cost by integrating the spatial and aspatial dimensions in the virtual concept hierarchy.

• Journal of Korea Multimedia Society
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• v.9 no.11
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• pp.1421-1434
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• 2006

Spatial data warehouses provide analytical information for decision supports using SOLAP (Spatial On-Line Analytical Processing) operations. Many researches have been studied to reduce analysis cost of SOLAP operations using pre-aggregation methods. These methods use the index composed of fixed size nodes for supporting the concept hierarchy. Therefore, these methods have many unused entries in sparse data area. Also, it is impossible to support the concept hierarchy in dense data area. In this paper, we propose a dynamic pre-aggregation index method based on the spatial hierarchy. The proposed method uses the level of the index for supporting the concept hierarchy. In sparse data area, if sibling nodes have a few used entries, those entries are integrated in a node and the parent entries share the node. In dense data area, if a node has many objects, the node is connected with linked list of several nodes and data is stored in linked nodes. Therefore, the proposed method saves the space of unused entries by integrating nodes. Moreover it can support the concept hierarchy because a node is not divided by linked nodes. Experimental result shows that the proposed method saves both space and aggregation search cost with the similar building cost of other methods.

• Journal of Korea Multimedia Society
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• v.9 no.11
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• pp.1395-1409
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• 2006

A spatial data warehouse has spatial data cube composed of multi-dimensional data for efficient OLAP(On-Line Analytical Processing) operations. A spatial data cube supporting concept hierarchies holds huge amount of data so that many researches have studied a incremental update method for minimum modification of a spatial data cube. The Cube, however, compressed by eliminating prefix and suffix redundancy has coalescing paths that cause update inconsistencies for some updates can affect the aggregate value of coalesced cell that has no relationship with the update. In this paper, we propose incremental batch update method of a spatial data cube. The proposed method uses duplicated nodes and extended node structure to avoid update inconsistencies. If any collision is detected during update procedure, the shared node is duplicated and the duplicate is updated. As a result, compressed spatial data cube that includes concept hierarchies can be updated incrementally with no inconsistency. In performance evaluation, we show the proposed method is more efficient than other naive update methods.

• Journal of Korea Spatial Information System Society
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• v.9 no.3
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• pp.1-16
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• 2007

A spatial data warehouse is a system to support decision making using a spatial data cube. A spatial data cube is composed of a dimension table and a fact table. For decision support using this spatial data cube, the concept hierarchy of spatial dimension and the summarized information of spatial fact should be provided. In the previous researches, however, spatial summarized information is deficient. In this paper, the spatial aggregation for spatial summarized information in a spatial data warehouse is proposed. The proposed spatial aggregation is separated of both the numerical aggregation and the object aggregation. The numerical aggregation is the operation to return a numerical data as a result of spatial analysis and the object aggregation returns the result represented to object. We provide the extended struct of spatial data for spatial aggregation and so our proposed method is efficient.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• 2003.05a
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• pp.291-297
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• 2003

The aim of this research is to propose new framework for taxonomy of various business and its concept, due to the changes in market space. This framework is three-dimension cubic model, based on three concepts, business layer(BL), value chain(VC), and Real/Virtual(R/V) that symbolizes real environment and virtual(or cyber) space. And we showed that this framework is able to describe all expected(or existed) business types in certain industry by the combinations of BL-VC-R/V on three dimension. In addition, we suggested new definition of e-business and e-Logistics from view of BL-VC-R/V. In order to test availability, this framework was applied for logistics related business. and classified typical business types existed (or expected) in logistics area.

• Journal of Navigation and Port Research
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• v.27 no.4
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• pp.389-395
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• 2003

The aim of this research is to propose new framework for taxonomy of various business and its concept. due to the changes in market space. This framework is three-dimension cubic model based on three concepts, business layer(BL), value chain(VC), and Real/Virtual(R/V) that symbolizes real environment and virtual (or cyber) space. We showed that this framework is able to describe all expected(or existed) business types in certain industry by the combinations of BL-VC-R/V on three dimension. In addition, we suggested new definition of e-business and e-Logistics from view of BL-VC-R/V. In order to test availability of framework, this framework was applied for logistics related business, and we classified typical business types existed (or expected) in logistics area.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2021.10a
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• pp.600-601
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• 2021

The cyberspace, which is the fifth battle field, should be utilized for multi-domain maneuvering between the cyberspace and the physical space using an electromagnetic spectrum. This becomes a major concept of cyber electronic warfare that combines the characteristics of cyber warfare and electronic warfare. In this study, the concept of cyber electronic warfare is analyzed by using the OSI reference model and examining the threats of the two-layer data link layer.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.11 no.12
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• pp.5015-5022
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• 2010

Most of the existing pattern mining techniques are capable of searching patterns according to the continuous change of the spatial information of an object but there is no constraint on the spatial information that must be included in the extracted pattern. Thus, the existing techniques are not applicable to the optimal path search between specific nodes or path prediction considering the nodes that a moving object is required to round during a unit time. In this paper, the precision of the path search according to the spatial hierarchy is analyzed using the Spatial-Temporal Optimal Moving Pattern(with Frequency & Weight) (STOPM(FW)) algorithm which searches for the optimal moving path by considering the most frequent pattern and other weighted factors such as time and cost. The result of analysis shows that the database retrieval time is minimized through the reduction of retrieval range applying with the spatial constraints. Also, the optimal moving pattern is efficiently obtained by considering whether the moving pattern is included in each hierarchical spatial scope of the spatial hierarchy or not.

• Proceedings of the Korean Information Science Society Conference
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• 2003.10b
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• pp.214-216
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• 2003

유비쿼터스 상거래의 도래에 따라 개인화 된 서비스를 위한 상황과 환경 정보 즉, 컨텍스트 정보에 기반한 정보 제공의 중요성이 높아지고 있는데, 기존의 연구는 물리적 환경에 국한하여 컨텍스트를 적용하고 있으며. 개인의 선호를 고려하지 않는 타켓 마케팅 개념적 서비스에 기반을 두기 때문에 유비쿼터스 상거래 환경의 컨텍스트 도메인 관점에 부 적합하고, 개인화된 서비스 지원이 어렵다. 따라서 이 연구에서는 유비쿼터스 환경에서의 컨텍스트 개체에 대해 정의하고, 전자공간과 물리공간의 연계를 바탕으로 실세계의 일반화 된 공간 개념과 전자 공간의 카테고리 형태의 구조를 통합한 개념 계층 구조로 컨텍스트 정보 모델링을 제안하고, XML 데이터베이스를 이용하여 설계한다. 아울러 이렇게 확장된 컨텍스트 개념을 기반으로 적용 가능한 개인 상거래 서비스를 설명한다.