一种交替搜索空间拓扑关联的挖掘算法

针对现有挖掘算法不能有效提取空间拓扑关联的问题，提出一种交替搜索空间拓扑关联的挖掘算法，适合在海量空间数据中挖掘空间拓扑关联规则。该算法从候选数字区间的两端，用数字递增和递减2种方式产生候选频繁项，实现交替搜索空间拓扑关联规则。在计算支持数时用数字特征减少被扫描的事务数，达到提高挖掘效率的目的。实验结果表明，在空间数据中挖掘空间拓扑关联规则时，该算法比现有算法更快速、有效。

Mining Algorithm of Alternately Search Spatial Topology Association

Aiming at the problem of presented algorithms inefficient extract spatial topology association, this paper proposes a mining algorithm of alternately search spatial topology association, which is suitable for mining spatial topology association rules in large data. From two endpoints of candidate digit interval, the algorithm uses two methods of generating candidate frequent itemsets in digit ascending and digit descending, in order to alternately search spatial topology association rules. The algorithm also uses digit feature to reduce the number of scanned transaction when computing support of itemsets, mining efficiency is improved. Experimental result shows that the algorithm is faster and more efficient than presented algorithms when mining spatial topology association rules in spatial data.