Name
Abstract | ||
|---|---|---|
Spatial co-location pattern mining is an interesting and important task in spatial data mining which discovers the subsets of spatial features frequently observed together in nearby geographic space. However, the traditional framework of mining prevalent colocation patterns produces numerous redundant co-location patterns, which makes it hard for users to understand or apply. To address this issue... |
Year | DOI | Venue |
|---|---|---|
2018 | 10.1109/TKDE.2017.2759110 | IEEE Transactions on Knowledge and Data Engineering |
Keywords | DocType | Volume |
Redundancy,Data mining,Semantics,Measurement,Spatial databases,Indexes | Conference | 30 |
Issue | ISSN | Citations |
1 | 1041-4347 | 14 |
PageRank | References | Authors |
0.57 | 22 | 3 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Lizhen Wang | 1 | 38 | 7.49 |
| Xuguang Bao | 2 | 39 | 4.75 |
| Lihua Zhou | 3 | 18 | 7.71 |