Name
Abstract | ||
|---|---|---|
This paper presents an approach to the discovery of association rules for fuzzy spa- tial data. Association rules provide information of value in assessing significant correlations that can be found in large databases. Here we are interested in correlations of spatially related data such as soil types, directional or geometric relationships, etc. We have combined and extended techniques developed in both spatial and fuzzy data mining in order to deal with the uncertainty found in typical spatial data. |
Year | DOI | Venue |
|---|---|---|
2003 | 10.1111/1467-9671.00133 | T. GIS |
DocType | Volume | Issue |
Journal | 7 | 1 |
Citations | PageRank | References |
14 | 0.95 | 26 |
Authors | ||
3 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Roy Ladner | 1 | 87 | 9.46 |
| Frederick E. Petry | 2 | 562 | 69.24 |
| Maria Cobb | 3 | 103 | 12.68 |