Spatial colocation patterns discovery in fuzzy spatial
Zou Muqua · Computer Engineering and Applications Journal · 2014
The spatial colocation pattern mining in spatial data sets has been extended to the spatially uncertain data sets and spatially fuzzy data sets in recent years. However, for mining from spatially fuzzy data sets, it is studied only about spatially fuzzy objects rather than fuzzy spatial. According to the theory of the spatial colocation pattern mining in traditional spatial data sets, some concepts of spatial colocation pattern mining in fuzzy spatial are defined. An FS basic algorithm is proposed while the function of membership degree is unknown, and as it does not need to check clique instances one by one, the FS basic algorithm works well. Meanwhile, a common method to increase the completeness of spatially data sets is introduced. Finally, the paper proposes an improved algorithm of FS to make spatially fuzzy data sets more integral, and then to transform spatially fuzzy data sets into spatially classic data sets.