Name
Title | ||
|---|---|---|
Co-location Detector: A System to Find Interesting Spatial Co-locating Relationships. |
Abstract | ||
|---|---|---|
Data Mining develops from original transactional data to current spatial data, this trend indicates that the data is getting more complex and the mining algorithms require better performances. Co-location patterns describe the subsets of features whose instances are prevalently located together in geographic space. Co-location mining algorithms are to find prevalent (interesting) co-location patterns with some thresholds given by the user. Co-location Detector is a system which improves the join-less algorithm and optimizes some details, it owns friendly interactive interface and good operational experiences, visualizes the co-location patterns for the user to process the next decision, besides, the user can change his input parameters to compare the results in order to mine more valuable information. |
Year | Venue | Field |
|---|---|---|
2016 | APWeb | Spatial analysis,Data mining,Computer science,Transaction data,Detector |
DocType | Citations | PageRank |
Conference | 0 | 0.34 |
References | Authors | |
2 | 3 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Xuguang Bao | 1 | 0 | 0.68 |
| Lizhen Wang | 2 | 153 | 26.16 |
| Qing Xiao | 3 | 7 | 3.52 |