SOLAP Based on Novel Spatial Dimensions

被引：0
|
作者：
Xu, ChengZhi [1 ]
Sheu, Phillip C-Y [2 ]
机构：
[1] Hubei Univ Technol, Sch Comp Sci, Wuhan, Peoples R China
[2] Univ Calif Irvine, Dept EECS, Irvine, CA USA
来源：
SOFTWARE ENGINEERING AND KNOWLEDGE ENGINEERING: THEORY AND PRACTICE, VOL 1 | 2012年 / 114卷
基金：
美国国家科学基金会;
关键词：
Auxiliary spatial dimension; data cube; SOLAP; buffering analysis; SQDL-G;
D O I：
暂无
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
The ratio of spatial dimensions to all dimensions in data cube is very small, and spatial dimensions do not contain a wealth of spatial information, all these become a bottleneck of current space online analytical processing (SOLAP). Aiming at these problems, this paper proposed a new method to build novel dimensions, auxiliary spatial dimensions. With the help of SQDL-G, relationships between central theme and neighborhood objects are introduced into the new spatial dimensions, and data cube will contain more spatial information. The case study demonstrates that this method makes full use of topological operations, quantities spatial relationship, and promotes the analytical capacity of SOLAP.
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页码：383 / +
页数：2
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