Spatio-temporal data warehouses using an adaptive cell-based approach
- Authors
- Choi, Wonik; Kwon, Dongseop; Lee, Sangjun
- Issue Date
- Oct-2006
- Publisher
- ELSEVIER SCIENCE BV
- Keywords
- spatio-temporal data warehouses; aggregation query; Hilbert curve; prefix-sum; ST-Cube
- Citation
- DATA & KNOWLEDGE ENGINEERING, v.59, no.1, pp.189 - 207
- Journal Title
- DATA & KNOWLEDGE ENGINEERING
- Volume
- 59
- Number
- 1
- Start Page
- 189
- End Page
- 207
- URI
- http://scholarworks.bwise.kr/ssu/handle/2018.sw.ssu/18597
- DOI
- 10.1016/j.datak.2005.08.001
- ISSN
- 0169-023X
- Abstract
- Most of the framework for supporting OLAP operations over immense amounts of spatio-temporal data is based on multi-tree structures. The multi-tree frameworks, however, are hardly applicable to spatio-temporal OLAP in practice, due mainly to high management costs and low query efficiency. To overcome the limitations of such multi-tree frameworks, we propose a new approach called ST-Cube (spatio- temporal cube), which is an adaptive cell-based, total-ordered and prefix-summed cube for spatio-temporal data warehouses. Our extensive performance studies show that the ST-Cube requires less space and achieves higher query performance than multi-tree frameworks, under various operational conditions. (c) 2005 Elsevier B.V. All rights reserved.
- Files in This Item
- There are no files associated with this item.
- Appears in
Collections - College of Information Technology > School of Software > 1. Journal Articles
![qrcode](https://api.qrserver.com/v1/create-qr-code/?size=55x55&data=https://scholarworks.bwise.kr/ssu/handle/2018.sw.ssu/18597)
Items in ScholarWorks are protected by copyright, with all rights reserved, unless otherwise indicated.