A fast space-saving algorithm for maximal co-location pattern mining

作者：

Highlights：

• A new algorithm for mining maximal co-location patterns was presented.

• A fast, sparse-graph-based strategy was used for mining candidate co-locations.

• A condensed-tree-based strategy was to reduce the time and space complexities.

• The new algorithm was compared with two other maximal co-location algorithms.

摘要

•A new algorithm for mining maximal co-location patterns was presented.•A fast, sparse-graph-based strategy was used for mining candidate co-locations.•A condensed-tree-based strategy was to reduce the time and space complexities.•The new algorithm was compared with two other maximal co-location algorithms.

论文关键词：Spatial data mining,Maximal co-location patterns,Sparse undirected graph,Condensed tree,Hierarchical verification

论文评审过程：Received 3 March 2016, Revised 5 June 2016, Accepted 3 July 2016, Available online 6 July 2016, Version of Record 16 July 2016.

论文官网地址：https://doi.org/10.1016/j.eswa.2016.07.007