k-邻近空间关系下的空间同位模式挖掘算法

基金项目: 国家自然科学基金资助项目(40601026)

详细信息

A Novel Spatial Co-location Pattern Mining Algorithm Based on k-Nearest Feature Relationship

¹Research Center of Spatial Information and Digital Engineering,Wuhan University,129 Luoyu Road,Wuhan 430079,China

Funds: 国家自然科学基金资助项目(40601026)

摘要: 定义了一种基于k-邻近对象的空间同位模式,探讨了基于k-邻近空间关系的同位模式的特点及其与基于距离阈值的空间同位模式的区别与联系,并开发了k-邻近对象同位模式挖掘算法(KNFCOM)。通过对真实数据的实验结果表明,KNFCOM算法可有效地发现大型空间数据集中存在的各种空间同位模式。
- k-邻近 /
- 空间同位模式 /
- KNFCOM算法 /
- 空间关联规则
Abstract: We define a k-nearest feature based on co-location patterns,and develop k-nearest feature co-location mining(KNFCOM) algorithm to mine this kind of co-location patterns.The experimental results show that KNFCOM algorithm is efficient and scalable for mining spatial co-location patterns from various large spatial datasets.
- k-nearest feature /
- spatial co-location pattern /
- KNFCOM /
- spatial association rule