공간 데이터 웨어하우스에서 공간적 의사 결정을 위한 데이터 큐브 색인 기법 = A Data Cube Indexing Method for Spatial Decision Making in Spatial Data Warehouse

다국어 초록 (Multilingual Abstract)

Most decision support functions of spatial data warehouse rely on 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 is supports aggregating functions well against specified areas, it ignores the operations on the aspatial dimension. 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 dimension in the virtual concept hierarchy.

목차 (Table of Contents)

• Ⅰ. 서론
• Ⅱ. 관련 연구
• Ⅲ. 다차원 개념 계층 지원을 위한 데이터 큐브 색인 구조
• Ⅳ. 다차원 개념 계층에 대한 큐브 색인 생성 및 검색 알고리즘
• 4.1 다차원 개념 계층에 대한 통합된 큐브 색인 생성
• 4.2 다차원 개념 계층에 대한 통합된 큐브 색인 검색
• Ⅴ. 결론
• 참고문헌