计算机工程2011，Vol.37Issue(8)：58-60,3.DOI:10.3969/j.issn.1000-3428.2011.08.020
基于聚类方法的空间度量物化选择算法
Materialized Selection Algorithm for Spatial Measure Based on Clustering Method
摘要
Abstract
In spatial data warehouse, the aggregation results of spatial measures in materialized view require substantial storage space. Parts of spatial measures are selected to materialize. And the existing materialized view selection algorithms are mostly designed for view selection. They can not be applied for handling spatial measures. This paper proposes a spatial measures materialized selection algorithm based on cluster method for spatial region merging operation. All merged groups of spatial object are clustered. In each cluster, the algorithm calculates benefit for every merged group. After the best merged group based on the benefit calculation is selected to materialize, the algorithm only recalculates the benefits of merged groups in the cluster which includes materialized group. Overhead of benefit calculation is greatly reduced. Experimental results show the superiority of the algorithm.关键词
空间数据仓库/空间度量/物化视图/聚类方法Key words
spatial data warehouse/ spatial measure/ materialized view/ clustering method分类
信息技术与安全科学引用本文复制引用
梁银..基于聚类方法的空间度量物化选择算法[J].计算机工程,2011,37(8):58-60,3.基金项目
徐州师范大学自然科学基金资助重点项目(08XLA12) （08XLA12）
